priya mam notes

7/31/2019 Priya Mam Notes

1/34

15 marks ques & ans

1) Describe briefly how a research report should be presented ?

Ans) Preparing a Research Report

Research has little value if it is not put together into some form of report. We have

said that research represents a scientific method of establishing knowledge that is

cumulative. And therefore, scientific findings must be properly documented and

reported through appropriate media. Effective communication of research findings,

both to scientist and to the general audiences, is a very important component of the

research process. Decisions on writing style and method of presentation must depend

on the intended purposes and prospective readers. Any researcher who hopes to do an

effective report should have some idea of his probable readers or audience, someunderstanding of the needs, interests and capability will help him decide which points

to stress in his presentation.

Effective writing is a tool that helps to insure understanding and use of the results of

the study. It is helpful to have an outline to work with in preparing a research report. It

will assure order in the finished work and it will help to hold down repetition and

guard against omissions. The various points to be included should be given careful

thought before actual writing is started.

Findings should be reported in terms of the objectives and/or hypotheses of the study.Whenever results are not conclusive, some explanation should be made. When a

researcher feels he should express a personal opinion, he should say so. A researcher

has the obligation to make some comments as to what the findings mean. Data do not

speak for themselves but must be analyzed and interpreted. The researcher mustdraw conclusions from the analysis and in the end make recommendations.

Conclusions and recommendations must be made on the basis of the data at hand

because that is the best information that is available within the resource restrictions.

The researcher must assume that his knowledge is vital and that he knows more about

the subject studied than anyone else. The limitations of the study should also be

pointed out, in all fairness to the reader.

Most research reports require a certain amount of substantiation from sources other

than the research findings at hand. Some times, the researcher may want to make

comparisons of the results with those obtained from other sources. These other

sources should be identified by footnotes. All of the sources are assembled in a


2/34

bibliography to accompany the report. The style and form of a research report are

based upon clarity of organization and presentation as practiced in academic circles.

The significance of a research report

As noted above, research findings must be communicated in one way or another. First

and foremost, reports are necessary to account to the funding body the expenditure of

the funds allocated, manpower and other resources. Even more importantly, research

reports make scientific information more accessible to people and social groups or

organizations interested in particular research data. In doing so, the researcher must

have some understanding of the needs, interests and capability of the target audience.

This will help him decide the format and points he needs to elaborate and stress in his

report. If the audience constitutes the scientific community, his emphasis would be the

results, methods, and scientific tools he employed to analyse, interpret, and conclude

from the findings of his study. His work may be published as an article in a journal, orbulletin. If the target audience is made up of extension agents, development workers,

policy makers, etc. his emphasis will be the conclusion and recommendations drawn

from the study.

The nature of scientific writing

Writing is first and foremost analysing, revising, and polishing the text. It is unusual

for one to produce ready-made text right away. Assess your results before starting to

write. In the process of writing, the researcher learns from his mistakes and

comments/ advices he gets from peers, reviewers, or supervisor. These are veryessential during the writing process. Nevertheless, the writer must assume

responsibility and keep his confidence in his own experience and knowledge about the

problem he studied. No one else can know better than himself about the work he did

accomplish.

Also writing a research report is not something left to the end of the research work.

Rather, it is a continuous process. So, you should start writing whenever you have

something to write. The list of contents need to be prepared at an early stage and

continually revised as need be. It will assure order in the finished work and it will help

to hold down repetition and guard against omissions. The various points to beincluded should be given careful thought when preparing the table of contents.

The key to scientific writing is clarity. Scientists are required to write in clear and

simple terms. Ideas should be explained in simple language and short, coherent

sentences. The personal pronouns I, we, you, my, our and us are avoided by the use of

such expressions as the researcher or the investigator. Minimize the use of jargons and


3/34

imprecise words. Concepts and definitions must be sufficiently described depending

upon the type and capability of the target audience. The past tense should be used in

describing research procedures that have been completed.

Generally, a researcher has the obligation to make some comments as to what the data

mean. Data do not always speak for themselves but must be analysed andinterpreted. It is based on these that conclusions and recommendations must be drawn.

Whenever results are not conclusive, some explanations should be made. When a

researcher feels he should express a personal opinion, he should say so very clearly.

Following are some checklist to consider reviewing a scientific report or paper.

Are concepts and definitions described sufficiently?

Are the main points/results clearly spelled out and described?

Has the text a clear focus?

Is the text well organized? Are the different chapters well connected?

Is the text written in clear terms with adequate explanations?

Types of scientific publications

Universities, research organizations and donors require research reports. Usually, such

organizations have their own format for progress, annual, and terminal reports,

respectively.

Research findings should be reported in terms of the objectives and/or hypotheses of

the study. One can use the research questions stated in the proposal.

Effective writing is a tool that helps to insure understanding and use of research

results. If a researcher produces acceptable report, he can be rewarded in many ways.

Finally, research reports are substantiated by references from other published or

unpublished sources. Sometimes, the researcher may want to make comparisons of the

results with those obtained from other sources. Such other sources must be identifies

by footnotes and assembled in the list of references or bibliography placed at the end

of the report.

Format of the Research Report/ Guidelines for preparing

the research report

A. Preliminary section


4/34

1. Title page: Some basic considerations

The title page usually includes:

o The name of the topic

o The name of the authoro The relationship of the report to a course or degree requirement

o The name of the institution where the report is submitted

o The date and place of the presentation

Any research work starts with a title that will almost certainly change before the

research is completed and reported. It is very wise, therefore, to think of an effective

title that will be finally adopted. So it is a good idea to keep notes of alternative titles

or ideas as you proceed in preparing and writing the research report. The title should

catch the readers attention while informing them about the main thesis of the study.

First impressions are strong and can attract attention. The title should be concise andshould give a precise indication of what is to come. It should not claim more than

what the study actually delivers. The title should be typed in capital letters, single

spaced and centered between the right and left margins of the page.

2. Acknowledgement (if any)

An acknowledgement page is included if the writer has received unusual assistance in

the conduct of the study. The author gives credit for external support received during

the conduct of the study. Acknowledgement also expresses gratitude for the use of

copyrighted or otherwise restricted materials. A doctoral candidate may choose todedicate the dissertation to a person(s) who has had significant impact on his work.

3. Table of contents:

A good table of contents serves as an important purpose in providing an outline of the

content of the report. The relationship between principal and minor divisions is

indicated by capitalization of chapter numbers and titles, with subheadings in small

letters and with capitalized principal letters.

B. Main body of the report

1. Introduction

As in the proposal, the introduction presents the problem addressed by the

research.


5/34

Gives sufficient background information to allow readers to understand the

results of the study.

It is written in such a way that readers will know the current status of research

conclusions on the topic, the theoretical implications associated with the results

of previous research on the subject, and the statement of a hypothetical

resolution of the issues to be tested by the research described. As in the proposal, the introduction should describe the nature and purpose of

the study, present the guiding research questions, and explain the significance

of and justification for conducting the study. Terms likely to be used

throughout the paper should be defined in this section.

A statement of objectives is included and a research hypothesis

2. Review of Related literature

A literature review must be organized in relation to research topic you are developing.

In the process you should synthesize results into a summary of what is and is notknown; identify areas of controversy in the literature; formulate questions that need

further research.

3. Materials and Methods (Methodology)

The methodology section is used to describe what the researcher did and how the

study was conducted. One important purpose is to enable others repeat the experiment

and verify the results if they wish to. In doing so, you should summarize the

procedures in the execution of each of the stage of your work. This section should

build on the description of methods outlined in the proposal. You should labelsubsections similar to those in the proposal. It may include subsections describe

participants or subjects, another describing testing or measurement procedures

undertaken with the participants, and a section describing limitations of the

methodology. These are all done in the past tense or past perfect tense.

This section should present the following:

1. Procedures used and kind of design2. Sources of data

3. Methods of gathering data4. Description of data gathering instruments used

4. Analysis of data/Results

This section summarizes the data collected and details the statistical treatment

of that data.


6/34

Present your results in a logical sequence using only observations pertinent to

your stated objectives.

After a brief statement of the main results or findings of the study, the data are

reported in sufficient detail to justify the conclusions.

Tables and illustrations may be used to report data when these methods are

seen to present the data more clearly and economically. Do not replicate observations in your tables. Give only means and measures of

variability.

Use tables to present exact values and figures to show trends and relationships.

All tables and illustrations should be mentioned in the text, with appropriate

titles or captions and enough explanations to make them readily identifiable.

Avoid repetition of numerical data from the tables and figures in the text.

5. Discussion

This section should reflect the implications of the study. Here the researcher evaluatesthe data and interprets the findings in the context of the research questions or

hypothesis. He is guided by questions like the following.

What do my results mean and what are their implications?

Should interpret your results clearly, concisely and logically. For each

objective, describe how your results relate to meeting the objectives.

Here, the major results are picked or summarized, evaluate, and interpreted

with respect to the original research questions and hypotheses and related with

previous works.

Theoretical and practical consequences of the results and the validity of

conclusions may appropriately be discussed in this section.

The limitations of the study and suggestions for future work may also be

included.

Emphasize on new results and suggest new lines of work or further research.

6. Conclusions and Recommendations

In this section you should describe briefly what you did, the main results and

recommendations for further research or applicability. Implications what the findings

of the research imply (consider suggestions).

7. References

At the end of your report you need to list all the sources cited in the text. Details

regarding citations and references are given part four.


7/34

BIBLIOGRAPHIC CITATIONS

Introduction

The principle of fairness and the role of personal recognition within the reward system

of science account for the emphasis given to the proper allocation of credit. In the

standard scientific paper, credit is explicitly acknowledged in three places: in the list

of authors, in the acknowledgments of contributions from others, and in the list of

references or citations. Conflicts over proper attribution can arise in any of these

places. Citations serve many purposes in a scientific paper. They acknowledge the

work of other scientists, direct the reader toward additional sources of information,

acknowledge conflicts with other results, and provide support for the views expressed

in the paper. More broadly, citations place a paper within its scientific context,

relating it to the present state of scientific knowledge. Failure to cite the work of

others can give rise to more than just hard feelings. Citations are part of the rewardsystem of science. They are connected to funding decisions and to the future careers

of researchers. More generally, the misallocation of credit undermines the incentive

system for publication. In addition, scientists who routinely fail to cite the work of

others may find themselves excluded from the fellowship of their peers. This

consideration is particularly important in one of the more intangible aspects of a

scientific career-that of building a reputation. Published papers document a person's

approach to science, which is why it is important that they be clear, verifiable, and

honest. In addition, a researcher who is open, helpful, and full of ideas becomes

known to colleagues and will benefit much more than someone who is secretive or

uncooperative.

Features of citations

(a) Footnoting

Footnotes are very useful devices because they serve a number of purposes

They enable you to substantiate your presentation by citing other authorities

They also enable you to present explanatory statements that would interfere

with the logic of your text

Traditionally, footnote citations are placed at the bottom of the page They are separated from the text by a horizontal line from the text margin.

(b) Abbreviations

o You may use abbreviations in bibliographic and footnote citations if you want

to conserve space. Examples: bk., bks. = book, books.


8/34

(c) Bibliography (Reference/Literature Cited)

Points to consider in preparing the references:

o The reference list at the end of the paper should list all works cited in the paper,

and all items listed as references must have been cited in the text.o Special attention should be given to ensure appropriate citations of less

common sources, such as unpublished manuscripts.

o There are many ways of presenting the bibliography but be accurate and

consistent in the way you list

o Follow guidelines required by the particular journal, proceeding, etc. They do

have their own style of citations.

o Citing a source without having read/seen the original can lead to

embarrassment and loss of credibility if the secondary source from which you

gained the information is in error.

o Again, the APA Manual can provide guidance for ensuring accuracy in thesedetails.

o General rule: Author (s). Year of Publication. Title of Work. Publication data.

(i) In-text references (citations)-References are citations of other works such as books,

journal articles, or private communications. References in text are treated somewhat

differently from references in the complete list at the end of a paper.

Use the author-date format to cite references in text. For example: as Smith

(1990) points out,

For two-author citations, spell out both authors on all occurrences. For multiple-author citations (up to five authors) name all authors the first time,

then use et al., so the first time it is Smith, Jones, Pearson and Sherwin (1990),

but the second time it is Smith et al., with a period after al but no underlining.

For six or more authors, use et al. the first time and give the full citation in

references.

Include page reference after the year, outside quotes but inside the comma, for

example: The author stated, The effect disappeared within minutes (Lopez,1993, p. 311) , but she did not say which effect. Another example would be:

Lopez found that the effect disappeared within minutes (p. 311). Notice alsothat the sentence is capitalized only if presented after a comma, as a complete

sentence.

If two or more multiple-author references which shorten to the same et al.form, making it ambiguous, give as many author names as necessary to make

them distinct, before et al. For example: (Smith, Jones, et al., 1991) to

distinguish it from (Smith, Burke, et al., 1991).


9/34

Join names in a multiple-author citation with and (in text) or an ampersand (&)

in reference lists and parenthetical comments. For example: As Smith and

Sarason (1990) point out, the same argument was made by in an earlier study

(Smith & Sarason, 1990).

If a group is readily identified by its initials, spell it out only the first time. For

example, As reported in a government study (National Institute of MentalHealth [NIMH], 1991), blah blah... and thereafter, The previously cited study

(NIMH, 1991) found that...

If the author is unknown or unspecified, use the first few words of the reference

list entry (usually the title), for example: (Study Finds, 1992).

If citing multiple works by the same author at the same time, arrange dates in

order. In general, use letters after years to distinguish multiple publications by

the same author in the same year. For example: Several studies (Johnson, 1988,

1990a, 1990b, 1995 in press-a, 1995 in press-b) showed the same thing.

For old works cite the translation or the original and modern copyright dates if

both are known, for example: (Aristotle, trans. 1931) or (James, 1890/1983).

Always give page numbers for quotations, for example: (Cheek & Buss, 1981,

p. 332) or (Shimamura, 1989, chap. 3, p. 5).

For e-mail and other unrecoverable data use personal communication, forexample: (V.-G. Nguyen, personal communication, September 28, 1993).

These do not appear in the reference list.

2) Critically evaluate any three methods of sampling and suggest when you use them?

Ans) 1.1 Definition of sampling

Sampling can be defined as selecting part of the elements in a population. It results in

the fact that, conclusions from the sample may be extended to that about the entire

population.

1.2 Advantages of sampling

There are several advantages of sampling over census (i.e. selection of whole

population for analysis).

Firstly, the costs on sampling should be much lower than that on census. For example,

for the government by-census (note: population census is usually conducted once

every ten years and a by-census is conducted in the middle of the intercensal period),


10/34

one fifth of the population is large enough to declare what the government wants to

know. There is no need to spend several times of dollars to interview the entire

population in the society.

Secondly, a quality guru (Deming, 1960) argued that the quality of a study was often

better with sampling than with a census. He suggested that, Sampling possesses the

possibility of better interviewing(testing), more thorough investigation of missing,

wrong , or suspicious information, better supervision, and better processing than is

possible with complete coverage. Research findings substantiate this opinion. More

than 90% of survey error in one study was from non-sampling error, and 10% or less

was from sampling error. (Donald et al., 1995)

Thirdly, sampling can save the time. The speed of execution reduces the time between

the recognition of a need for information and the availability of that information.

1.3 Importance to learn sampling

Statistical application is mainly concerned with the collection, presentation of data,

analysis and interpretation of information. Data collection is the first step. Most

statistical analysis methods are derived based on the assumption of the randomization

used in data collection. When the assumption of the randomization/representation of

sampling cannot hold, the applications of the statistical analysis and the respective

interpretation from the analysis are meaningless. Therefore, it is necessary to acquire

the knowledge on sampling before learning the statistical analysis.

Probability and nonprobability sampling

A probability sampling scheme is one in which every unit in the population has a chance (greater than

zero) of being selected in the sample, and this probability can be accurately determined. The combination

of these traits makes it possible to produce unbiased estimates of population totals, by weighting sampled

units according to their probability of selection.


11/34

Example: We want to estimate the total income of adults living in a given street. We visit each household

in that street, identify all adults living there, and randomly select one adult from each household. (For

example, we can allocate each person a random number, generated from auniform distributionbetween

0 and 1, and select the person with the highest number in each household). We then interview the

selected person and find their income.People living on their own are certain to be selected, so we simply

add their income to our estimate of the total. But a person living in a household of two adults has only a

one-in-two chance of selection. To reflect this, when we come to such a household, we would count the

selected person's income twice towards the total. (The person whois selected from that household can

be loosely viewed as also representing the person who isn't selected.)

In the above example, not everybody has the same probability of selection; what makes it a probability

sample is the fact that each person's probability is known. When every element in the

population doeshave the same probability of selection, this is known as an 'equal probability of selection'

(EPS) design. Such designs are also referred to as 'self-weighting' because all sampled units are given

the same weight.

Probability sampling includes:Simple Random Sampling,Systematic Sampling,Stratified Sampling,

Probability Proportional to Size Sampling, andClusterorMultistage Sampling. These various ways of

probability sampling have two things in common:

1. Every element has a known nonzero probability of being sampled and

2. involves random selection at some point.

Nonprobability sampling is any sampling method where some elements of the population

have nochance of selection (these are sometimes referred to as 'out of coverage'/'undercovered'), or

where the probability of selection can't be accurately determined. It involves the selection of elements

based on assumptions regarding the population of interest, which forms the criteria for selection. Hence,because the selection of elements is nonrandom, nonprobability sampling does not allow the estimation

of sampling errors. These conditions give rise toexclusion bias, placing limits on how much information a

sample can provide about the population. Information about the relationship between sample and

population is limited, making it difficult to extrapolate from the sample to the population.

Example: We visit every household in a given street, and interview the first person to answer the door. In

any household with more than one occupant, this is a nonprobability sample, because some people are

more likely to answer the door (e.g. an unemployed person who spends most of their time at home is

more likely to answer than an employed housemate who might be at work when the interviewer calls) and

it's not practical to calculate these probabilities.

Nonprobability sampling methods includeaccidental sampling,quota samplingandpurposive sampling.

In addition, nonresponse effects may turn anyprobability design into a nonprobability design if the

characteristics of nonresponse are not well understood, since nonresponse effectively modifies each

element's probability of being sampled.

[edit]Sampling methods
http://en.wikipedia.org/wiki/Uniform_distribution_(continuous)http://en.wikipedia.org/wiki/Uniform_distribution_(continuous)http://en.wikipedia.org/wiki/Uniform_distribution_(continuous)http://en.wikipedia.org/wiki/Simple_random_samplehttp://en.wikipedia.org/wiki/Simple_random_samplehttp://en.wikipedia.org/wiki/Simple_random_samplehttp://en.wikipedia.org/wiki/Systematic_samplinghttp://en.wikipedia.org/wiki/Systematic_samplinghttp://en.wikipedia.org/wiki/Systematic_samplinghttp://en.wikipedia.org/wiki/Stratified_Samplinghttp://en.wikipedia.org/wiki/Stratified_Samplinghttp://en.wikipedia.org/wiki/Stratified_Samplinghttp://en.wikipedia.org/wiki/Cluster_samplinghttp://en.wikipedia.org/wiki/Cluster_samplinghttp://en.wikipedia.org/wiki/Cluster_samplinghttp://en.wikipedia.org/wiki/Multistage_samplinghttp://en.wikipedia.org/wiki/Multistage_samplinghttp://en.wikipedia.org/wiki/Multistage_samplinghttp://en.wikipedia.org/wiki/Selection_biashttp://en.wikipedia.org/wiki/Selection_biashttp://en.wikipedia.org/wiki/Selection_biashttp://en.wikipedia.org/wiki/Accidental_samplinghttp://en.wikipedia.org/wiki/Accidental_samplinghttp://en.wikipedia.org/wiki/Accidental_samplinghttp://en.wikipedia.org/wiki/Quota_samplinghttp://en.wikipedia.org/wiki/Quota_samplinghttp://en.wikipedia.org/wiki/Quota_samplinghttp://en.wikipedia.org/wiki/Purposive_samplinghttp://en.wikipedia.org/wiki/Purposive_samplinghttp://en.wikipedia.org/wiki/Purposive_samplinghttp://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=5http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=5http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=5http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=5http://en.wikipedia.org/wiki/Purposive_samplinghttp://en.wikipedia.org/wiki/Quota_samplinghttp://en.wikipedia.org/wiki/Accidental_samplinghttp://en.wikipedia.org/wiki/Selection_biashttp://en.wikipedia.org/wiki/Multistage_samplinghttp://en.wikipedia.org/wiki/Cluster_samplinghttp://en.wikipedia.org/wiki/Stratified_Samplinghttp://en.wikipedia.org/wiki/Systematic_samplinghttp://en.wikipedia.org/wiki/Simple_random_samplehttp://en.wikipedia.org/wiki/Uniform_distribution_(continuous)


12/34

Within any of the types of frame identified above, a variety of sampling methods can be employed,

individually or in combination. Factors commonly influencing the choice between these designs include:

Nature and quality of the frame

Availability of auxiliary information about units on the frame

Accuracy requirements, and the need to measure accuracy

Whether detailed analysis of the sample is expected

Cost/operational concerns

[edit]Simple random sampling

In asimple random sample('SRS') of a given size, all such subsets of the frame are given an equal

probability. Each element of the frame thus has an equal probability of selection: the frame is not

subdivided or partitioned. Furthermore, any given pairof elements has the same chance of selection as

any other such pair (and similarly for triples, and so on). This minimises bias and simplifies analysis of

results. In particular, the variance between individual results within the sample is a good indicator of

variance in the overall population, which makes it relatively easy to estimate the accuracy of results.

However, SRS can be vulnerable to sampling error because the randomness of the selection may result

in a sample that doesn't reflect the makeup of the population. For instance, a simple random sample of

ten people from a given country will on averageproduce five men and five women, but any given trial is

likely to overrepresent one sex and underrepresent the other. Systematic and stratified techniques,

discussed below, attempt to overcome this problem by using information about the population to choose a

more representative sample.

SRS may also be cumbersome and tedious when sampling from an unusually large target population. In

some cases, investigators are interested in research questions specific to subgroups of the population.

For example, researchers might be interested in examining whether cognitive ability as a predictor of job

performance is equally applicable across racial groups. SRS cannot accommodate the needs of

researchers in this situation because it does not provide subsamples of the population. Stratifiedsampling, which is discussed below, addresses this weakness of SRS.

Simple random sampling is always an EPS design (equal probability of selection), but not all EPS designs

are simple random sampling.

[edit]Systematic sampling

Systematic samplingrelies on arranging the target population according to some ordering scheme and

then selecting elements at regular intervals through that ordered list. Systematic sampling involves a

random start and then proceeds with the selection of every kth element from then onwards. In this

case, k=(population size/sample size). It is important that the starting point is not automatically the first in

the list, but is instead randomly chosen from within the first to the kth element in the list. A simple examplewould be to select every 10th name from the telephone directory (an 'every 10th' sample, also referred to

as 'sampling with a skip of 10').

As long as the starting point israndomized, systematic sampling is a type ofprobability sampling. It is

easy to implement and thestratificationinduced can make it efficient, ifthe variable by which the list is

ordered is correlated with the variable of interest. 'Every 10th' sampling is especially useful for efficient

sampling fromdatabases.
http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=6http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=6http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=6http://en.wikipedia.org/wiki/Simple_random_samplehttp://en.wikipedia.org/wiki/Simple_random_samplehttp://en.wikipedia.org/wiki/Simple_random_samplehttp://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=7http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=7http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=7http://en.wikipedia.org/wiki/Systematic_samplinghttp://en.wikipedia.org/wiki/Systematic_samplinghttp://en.wikipedia.org/wiki/Randomizationhttp://en.wikipedia.org/wiki/Randomizationhttp://en.wikipedia.org/wiki/Randomizationhttp://en.wikipedia.org/wiki/Probability_samplinghttp://en.wikipedia.org/wiki/Probability_samplinghttp://en.wikipedia.org/wiki/Probability_samplinghttp://en.wikipedia.org/wiki/Stratified_samplinghttp://en.wikipedia.org/wiki/Stratified_samplinghttp://en.wikipedia.org/wiki/Stratified_samplinghttp://en.wikipedia.org/wiki/Databaseshttp://en.wikipedia.org/wiki/Databaseshttp://en.wikipedia.org/wiki/Databaseshttp://en.wikipedia.org/wiki/Databaseshttp://en.wikipedia.org/wiki/Stratified_samplinghttp://en.wikipedia.org/wiki/Probability_samplinghttp://en.wikipedia.org/wiki/Randomizationhttp://en.wikipedia.org/wiki/Systematic_samplinghttp://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=7http://en.wikipedia.org/wiki/Simple_random_samplehttp://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=6


13/34

For example, suppose we wish to sample people from a long street that starts in a poor area (house No.

1) and ends in an expensive district (house No. 1000). A simple random selection of addresses from this

street could easily end up with too many from the high end and too few from the low end (or vice versa),

leading to an unrepresentative sample. Selecting (e.g.) every 10th street number along the street ensures

that the sample is spread evenly along the length of the street, representing all of these districts. (Note

that if we always start at house #1 and end at #991, the sample is slightly biased towards the low end; byrandomly selecting the start between #1 and #10, this bias is eliminated.

However, systematic sampling is especially vulnerable to periodicities in the list. If periodicity is present

and the period is a multiple or factor of the interval used, the sample is especially likely to

be unrepresentative of the overall population, making the scheme less accurate than simple random

sampling.

For example, consider a street where the odd-numbered houses are all on the north (expensive) side of

the road, and the even-numbered houses are all on the south (cheap) side. Under the sampling scheme

given above, it is impossible to get a representative sample; either the houses sampled will allbe from the

odd-numbered, expensive side, or they will allbe from the even-numbered, cheap side.

Another drawback of systematic sampling is that even in scenarios where it is more accurate than SRS,

its theoretical properties make it difficult to quantifythat accuracy. (In the two examples of systematic

sampling that are given above, much of the potential sampling error is due to variation between

neighbouring houses - but because this method never selects two neighbouring houses, the sample will

not give us any information on that variation.)

As described above, systematic sampling is an EPS method, because all elements have the same

probability of selection (in the example given, one in ten). It is not'simple random sampling' because

different subsets of the same size have different selection probabilities - e.g. the set {4,14,24,...,994} has

a one-in-ten probability of selection, but the set {4,13,24,34,...} has zero probability of selection.

Systematic sampling can also be adapted to a non-EPS approach; for an example, see discussion of

PPS samples below.

[edit]Stratified sampling

Main article:Stratified sampling

Where the population embraces a number of distinct categories, the frame can be organized by these

categories into separate "strata." Each stratum is then sampled as an independent sub-population, out of

which individual elements can be randomly selected.[1]

There are several potential benefits to stratified

sampling.

First, dividing the population into distinct, independent strata can enable researchers to draw inferences

about specific subgroups that may be lost in a more generalized random sample.

Second, utilizing a stratified sampling method can lead to more efficient statistical estimates (provided

that strata are selected based upon relevance to the criterion in question, instead of availability of the

samples). Even if a stratified sampling approach does not lead to increased statistical efficiency, such a

tactic will not result in less efficiency than would simple random sampling, provided that each stratum is

proportional to the group's size in the population.
http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=8http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=8http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=8http://en.wikipedia.org/wiki/Stratified_samplinghttp://en.wikipedia.org/wiki/Stratified_samplinghttp://en.wikipedia.org/wiki/Stratified_samplinghttp://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-Canonical-0http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-Canonical-0http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-Canonical-0http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-Canonical-0http://en.wikipedia.org/wiki/Stratified_samplinghttp://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=8


14/34

Third, it is sometimes the case that data are more readily available for individual, pre-existing strata within

a population than for the overall population; in such cases, using a stratified sampling approach may be

more convenient than aggregating data across groups (though this may potentially be at odds with the

previously noted importance of utilizing criterion-relevant strata).

Finally, since each stratum is treated as an independent population, different sampling approaches can

be applied to different strata, potentially enabling researchers to use the approach best suited (or most

cost-effective) for each identified subgroup within the population.

There are, however, some potential drawbacks to using stratified sampling. First, identifying strata and

implementing such an approach can increase the cost and complexity of sample selection, as well as

leading to increased complexity of population estimates. Second, when examining multiple criteria,

stratifying variables may be related to some, but not to others, further complicating the design, and

potentially reducing the utility of the strata. Finally, in some cases (such as designs with a large number of

strata, or those with a specified minimum sample size per group), stratified sampling can potentially

require a larger sample than would other methods (although in most cases, the required sample size

would be no larger than would be required for simple random sampling.

A stratified sampling approach is most effective when three conditions are met

1. Variability within strata are minimized

2. Variability between strata are maximized

3. The variables upon which the population is stratified are strongly correlated with the desired

dependent variable.

Advantages over other sampling methods

1. Focuses on important subpopulations and ignores irrelevant ones.

2. Allows use of different sampling techniques for different subpopulations.

3. Improves the accuracy/efficiency of estimation.

4. Permits greater balancing of statistical power of tests of differences between strata by sampling

equal numbers from strata varying widely in size.

Disadvantages

1. Requires selection of relevant stratification variables which can be difficult.

2. Is not useful when there are no homogeneous subgroups.

3. Can be expensive to implement.

Poststratification

Stratification is sometimes introduced after the sampling phase in a process called

"poststratification".[1]This approach is typically implemented due to a lack of prior knowledge of an

appropriate stratifying variable or when the experimenter lacks the necessary information to create a

stratifying variable during the sampling phase. Although the method is susceptible to the pitfalls of post

hoc approaches, it can provide several benefits in the right situation. Implementation usually follows a

simple random sample. In addition to allowing for stratification on an ancillary variable, poststratification

can be used to implement weighting, which can improve the precision of a sample's estimates.[1]

Oversampling
http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-Canonical-0http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-Canonical-0http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-Canonical-0http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-Canonical-0http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-Canonical-0http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-Canonical-0http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-Canonical-0http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-Canonical-0


15/34

Choice-based sampling is one of the stratified sampling strategies. In choice-based sampling,[2]

the data

are stratified on the target and a sample is taken from each stratum so that the rare target class will be

more represented in the sample. The model is then built on thisbiased sample. The effects of the input

variables on the target are often estimated with more precision with the choice-based sample even when

a smaller overall sample size is taken, compared to a random sample. The results usually must be

adjusted to correct for the oversampling.

[edit]Probability-proportional-to-size sampling

In some cases the sample designer has access to an "auxiliary variable" or "size measure", believed to

be correlated to the variable of interest, for each element in the population. These data can be used to

improve accuracy in sample design. One option is to use the auxiliary variable as a basis for stratification,

as discussed above.

Another option is probability-proportional-to-size ('PPS') sampling, in which the selection probability for

each element is set to be proportional to its size measure, up to a maximum of 1. In a simple PPS design,

these selection probabilities can then be used as the basis forPoisson sampling. However, this has the

drawback of variable sample size, and different portions of the population may still be over- or under-

represented due to chance variation in selections. To address this problem, PPS may be combined with a

systematic approach.

Example: Suppose we have six schools with populations of 150, 180, 200, 220, 260, and 490 students

respectively (total 1500 students), and we want to use student population as the basis for a PPS sample

of size three. To do this, we could allocate the first school numbers 1 to 150, the second school 151 to

330 (= 150 + 180), the third school 331 to 530, and so on to the last school (1011 to 1500). We then

generate a random start between 1 and 500 (equal to 1500/3) and count through the school populations

by multiples of 500. If our random start was 137, we would select the schools which have been allocated

numbers 137, 637, and 1137, i.e. the first, fourth, and sixth schools.

The PPS approach can improve accuracy for a given sample size by concentrating sample on large

elements that have the greatest impact on population estimates. PPS sampling is commonly used for

surveys of businesses, where element size varies greatly and auxiliary information is often available - for

instance, a survey attempting to measure the number of guest-nights spent in hotels might use each

hotel's number of rooms as an auxiliary variable. In some cases, an older measurement of the variable of

interest can be used as an auxiliary variable when attempting to produce more current estimates.[3]

[edit]Cluster sampling

Sometimes it is more cost-effective to select respondents in groups ('clusters'). Sampling is often

clustered by geography, or by time periods. (Nearly all samples are in some sense 'clustered' in time -

although this is rarely taken into account in the analysis.) For instance, if surveying households within a

city, we might choose to select 100 city blocks and then interview every household within the selected

blocks.

Clustering can reduce travel and administrative costs. In the example above, an interviewer can make a

single trip to visit several households in one block, rather than having to drive to a different block for each

household.
http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-1http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-1http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-1http://en.wikipedia.org/wiki/Sampling_biashttp://en.wikipedia.org/wiki/Sampling_biashttp://en.wikipedia.org/wiki/Sampling_biashttp://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=9http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=9http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=9http://en.wikipedia.org/wiki/Poisson_samplinghttp://en.wikipedia.org/wiki/Poisson_samplinghttp://en.wikipedia.org/wiki/Poisson_samplinghttp://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-MySwedeLohr-2http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-MySwedeLohr-2http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-MySwedeLohr-2http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=10http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=10http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=10http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=10http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-MySwedeLohr-2http://en.wikipedia.org/wiki/Poisson_samplinghttp://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=9http://en.wikipedia.org/wiki/Sampling_biashttp://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-1


16/34

It also means that one does not need asampling framelisting all elements in the target population.

Instead, clusters can be chosen from a cluster-level frame, with an element-level frame created only for

the selected clusters. In the example above, the sample only requires a block-level city map for initial

selections, and then a household-level map of the 100 selected blocks, rather than a household-level

map of the whole city.

Cluster sampling generally increases the variability of sample estimates above that of simple random

sampling, depending on how the clusters differ between themselves, as compared with the within-cluster

variation. For this reason, cluster sampling requires a larger sample than SRS to achieve the same level

of accuracy - but cost savings from clustering might still make this a cheaper option.

Cluster samplingis commonly implemented asmultistage sampling. This is a complex form of cluster

sampling in which two or more levels of units are embedded one in the other. The first stage consists of

constructing the clusters that will be used to sample from. In the second stage, a sample of primary units

is randomly selected from each cluster (rather than using all units contained in all selected clusters). In

following stages, in each of those selected clusters, additional samples of units are selected, and so on.

All ultimate units (individuals, for instance) selected at the last step of this procedure are then surveyed.

This technique, thus, is essentially the process of taking random subsamples of preceding randomsamples.

Multistage sampling can substantially reduce sampling costs, where the complete population list would

need to be constructed (before other sampling methods could be applied). By eliminating the work

involved in describing clusters that are not selected, multistage sampling can reduce the large costs

associated with traditional cluster sampling.[3]

[edit]Quota sampling

In quota sampling, the population is first segmented intomutually exclusivesub-groups, just as

instratified sampling. Then judgement is used to select the subjects or units from each segment based on

a specified proportion. For example, an interviewer may be told to sample 200 females and 300 males

between the age of 45 and 60.

It is this second step which makes the technique one of non-probability sampling. In quota sampling the

selection of the sample is non-random. For example interviewers might be tempted to interview those

who look most helpful. The problem is that these samples may be biased because not everyone gets a

chance of selection. This random element is its greatest weakness and quota versus probability has been

a matter of controversy for many years.

[edit]Accidental sampling

Accidental sampling(sometimes known as grab, convenience or opportunity sampling) is a type of

nonprobability sampling which involves the sample being drawn from that part of the population which is

close to hand. That is, a population is selected because it is readily available and convenient. It may bethrough meeting the person or including a person in the sample when one meets them or chosen by

finding them through technological means such as the internet or through phone. The researcher using

such a sample cannot scientifically make generalizations about the total population from this sample

because it would not be representative enough. For example, if the interviewer were to conduct such a

survey at a shopping center early in the morning on a given day, the people that he/she could interview

would be limited to those given there at that given time, which would not represent the views of other

members of society in such an area, if the survey were to be conducted at different times of day and
http://en.wikipedia.org/wiki/Sampling_framehttp://en.wikipedia.org/wiki/Sampling_framehttp://en.wikipedia.org/wiki/Sampling_framehttp://en.wikipedia.org/wiki/Cluster_samplinghttp://en.wikipedia.org/wiki/Cluster_samplinghttp://en.wikipedia.org/wiki/Multistage_samplinghttp://en.wikipedia.org/wiki/Multistage_samplinghttp://en.wikipedia.org/wiki/Multistage_samplinghttp://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-MySwedeLohr-2http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-MySwedeLohr-2http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-MySwedeLohr-2http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=11http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=11http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=11http://en.wikipedia.org/wiki/Mutually_exclusivehttp://en.wikipedia.org/wiki/Mutually_exclusivehttp://en.wikipedia.org/wiki/Mutually_exclusivehttp://en.wikipedia.org/wiki/Stratified_samplinghttp://en.wikipedia.org/wiki/Stratified_samplinghttp://en.wikipedia.org/wiki/Stratified_samplinghttp://en.wikipedia.org/wiki/Randomhttp://en.wikipedia.org/wiki/Randomhttp://en.wikipedia.org/wiki/Randomhttp://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=12http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=12http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=12http://en.wikipedia.org/wiki/Accidental_samplinghttp://en.wikipedia.org/wiki/Accidental_samplinghttp://en.wikipedia.org/wiki/Accidental_samplinghttp://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=12http://en.wikipedia.org/wiki/Randomhttp://en.wikipedia.org/wiki/Stratified_samplinghttp://en.wikipedia.org/wiki/Mutually_exclusivehttp://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=11http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-MySwedeLohr-2http://en.wikipedia.org/wiki/Multistage_samplinghttp://en.wikipedia.org/wiki/Cluster_samplinghttp://en.wikipedia.org/wiki/Sampling_frame


17/34

several times per week. This type of sampling is most useful for pilot testing. Several important

considerations for researchers using convenience samples include:

1. Are there controls within the research design or experiment which can serve to lessen the impact

of a non-random convenience sample, thereby ensuring the results will be more representative

of the population?2. Is there good reason to believe that a particular convenience sample would or should respond or

behave differently than a random sample from the same population?

3. Is the question being asked by the research one that can adequately be answered using a

convenience sample?

In social science research,snowball samplingis a similar technique, where existing study subjects are

used to recruit more subjects into the sample. Some variants of snowball sampling, such as respondent

driven sampling, allow calculation of selection probabilities and are probability sampling methods under

certain conditions.

[edit]Line-intercept sampling

Line-intercept samplingis a method of sampling elements in a region whereby an element is sampled if

a chosen line segment, called a "transect", intersects the element.

[edit]Panel sampling

Panel sampling is the method of first selecting a group of participants through a random sampling

method and then asking that group for the same information again several times over a period of time.

Therefore, each participant is given the same survey or interview at two or more time points; each period

of data collection is called a "wave". Thislongitudinalsampling-method allows estimates of changes in the

population, for example with regard to chronic illness to job stress to weekly food expenditures. Panel

sampling can also be used to inform researchers about within-person health changes due to age or to

help explain changes in continuous dependent variables such as spousal interaction.[4]

There have been

several proposed methods of analyzingpanel data, includingMANOVA,growth curves, andstructural

equation modelingwith lagged effects.

3) Explain in detail the methods of data collection for a research study?

Ans) UNIT 6

Methods of data collection
http://en.wikipedia.org/wiki/Snowball_samplinghttp://en.wikipedia.org/wiki/Snowball_samplinghttp://en.wikipedia.org/wiki/Snowball_samplinghttp://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=13http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=13http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=13http://en.wikipedia.org/wiki/Line-intercept_samplinghttp://en.wikipedia.org/wiki/Line-intercept_samplinghttp://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=14http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=14http://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=14http://en.wikipedia.org/wiki/Longitudinal_studyhttp://en.wikipedia.org/wiki/Longitudinal_studyhttp://en.wikipedia.org/wiki/Longitudinal_studyhttp://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-SM-3http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-SM-3http://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-SM-3http://en.wikipedia.org/wiki/Panel_datahttp://en.wikipedia.org/wiki/Panel_datahttp://en.wikipedia.org/wiki/Panel_datahttp://en.wikipedia.org/wiki/MANOVAhttp://en.wikipedia.org/wiki/MANOVAhttp://en.wikipedia.org/wiki/MANOVAhttp://en.wikipedia.org/wiki/Growth_curveshttp://en.wikipedia.org/wiki/Growth_curveshttp://en.wikipedia.org/wiki/Growth_curveshttp://en.wikipedia.org/wiki/Structural_equation_modelinghttp://en.wikipedia.org/wiki/Structural_equation_modelinghttp://en.wikipedia.org/wiki/Structural_equation_modelinghttp://en.wikipedia.org/wiki/Structural_equation_modelinghttp://en.wikipedia.org/wiki/Structural_equation_modelinghttp://en.wikipedia.org/wiki/Structural_equation_modelinghttp://en.wikipedia.org/wiki/Growth_curveshttp://en.wikipedia.org/wiki/MANOVAhttp://en.wikipedia.org/wiki/Panel_datahttp://en.wikipedia.org/wiki/Sampling_(statistics)#cite_note-SM-3http://en.wikipedia.org/wiki/Longitudinal_studyhttp://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=14http://en.wikipedia.org/wiki/Line-intercept_samplinghttp://en.wikipedia.org/w/index.php?title=Sampling_(statistics)&action=edit&section=13http://en.wikipedia.org/wiki/Snowball_sampling


18/34

The search for answers to research questions calls of collection of data. Data are facts,

figures and other relevant materials, past and present, serving as bases for study and

analysis.

Types of Data

The data needed for a social science research may be broadly classified into (a) Data

pertaining to human beings, (b) Data relating to organisations, and (c) Data pertaining

to territorial areas.

Personal data or data related to human beings consist of Demographic and socio-

economic characteristics of individuals like age, sex, race, social class, religion,

marital status, education, occupation, income, family size, location of the household,

life style, etc. and Behavioural variables like attitudes, opinions, awareness,

knowledge, practice, intentions, etc.

Organisational dataconsist of data relating to an organisations origin, ownership,objectives, resources, functions, performance and growth.

Territorial data are related to geophysical characteristics, resources endowment,

population, occupational pattern, infrastructure, economic structure, degree of

development, etc. of spatial divisions like villages, cities, Tabias, Woredas, state/

regions and the nation.

Importance of data

The data serve as the bases or raw materials for analysis. Without an analysis of

factual data, no specific inferences can be drawn on the ques-tions under study.

Inferences based on imagination or guesswork cannot provide correct answers to

research questions. The relevance, adequacy and reliability of data determine the

quality of the findings of a study.

Data form the basis for testing the hypotheses formulated in a Study. Data also

provide the facts and figures required for constructing measure-ment scales and tables,

which are analysed with statistical techniques. Inferences on the results of statistical,

analysis and tests of significance provide the answers to research questions. Thus thescientific process of measurement, analysis, testing and inferences depends on the

availability of relevant data and their accuracy. Hence the importance of data for any

research studies.

SOURCES OF DATA


19/34

The sources of data may be classified into (a) primary sources and (b) secondary

sources.

Primary Sources

Primary sources are original sources from which the researcher directly collects datathat have not been previously collected, e.g., collection of data directly by the

researcher on brand awareness, brand preference, brand loyalty and other aspects of

consumer behaviour from a sample of consumers by interviewing them. Primary data

are first-hand information collected through various methods such as observation,

interviewing, mailing etc.

Secondary Sources

These are sources containing data that have been collected and compiled for another

purpose. The secondary sources consist of readily available compendia and alreadycompiled statistical statements and reports whose data may be used by researches for

their studies, e.g., census reports, annual reports and financial statements of

companies, Statistical statements, Reports of Government Departments, Annual

Reports on currency and finance published by the National Bank for Ethiopia,

Statistical Statements relating to Cooperatives, Federal Cooperative Commission,

Commercial Banks and Micro Finance Credit Institutions published by the National

Bank for Ethiopia, Reports of the National Sample Survey Organisation, Reports of

trade associations, publications of international organisations such as UNO, IMF,

World Bank, ILO, WHO, etc., Trade and Financial Journals, newspapers, etc.

Secondary sources consist of not only published records and reports, but also

unpublished records. The latter category includes various records and registers

maintained by firms and organisations, e.g., accounting and financial records,

personnel records, register of members, minutes of meetings, inventory records, etc.

Features of Secondary Sources: Though secondary sources are diverse and consist of

all sorts of materials, they have certain common charac-teristics.

First, they are readymade and readily available, and do not require the trouble of

constructing tools and administering them.

Second, they consist of data over which a researcher has no original control over

collection and classification. Others shape both the form and the content of secondary

sources. Clearly, this is a feature, which can limit the research value of secondary

sources.


20/34

Finally, secondary sources are not limited in time and space. That is, the researcher

using them need not have been present when and where they were gathered.

USE OF SECONDARY DATA

Uses

The secondary data may be used in three ways by a researcher. First, some specific

information from secondary sources may be used for refer-ence purposes.

Second, secondary data may be used as bench marks against which the findings of a

research may be tested.

Finally, secondary data may be used as the sole source of information for a research

project. Such studies as Securities Market Behaviour, Financial Analysis of

Companies, and Trends in credit allocation in commercial banks, Sociological Studieson crimes, historical studies, and the like depend primarily on secondary data. Year

books, Statistical reports of government departments, reports of public organisations

like Bureau of Public Enterprises, Census Reports etc. serve as major data sources for

such research studies.

Advantages

1. Secondary data, if available, can be secured quickly and cheaply.2. Wider geographical area and longer reference period may be covered without

much cost. Thus the use of secondary data extends the researcher's space andtime reach.

3. The use of secondary data broadens the database from which scientificgeneralizations can be made.

4. The use of secondary data enables a researcher to verify the findings based onprimary data.

Disadvantages/limitations

1. The most important limitation is the available data may not meet, our specific

research needs.2. The available data may not be as accurate as desired.3. The secondary data are not up-to-date and become obsolete when they appear

in print, because of time lag in producing them.

4. Finally information about the whereabouts of sources may not be available toall social scientists.


21/34

METHODS OF COLLECTING PRIMARY DATA:

GENERAL

The researcher directly collects primary data from their original sources. In this case,

the researcher can collect the required data precisely according to his research needs,he can collect them when he wants them and in the form he needs them. But the

collection of Primary data is costly and time consuming. Yet, for several types of

social science research such as socio-economic surveys, social anthropological studies

of rural communities and tribal communities, sociological studies of social problems

and social institutions, marketing research, leadership studies, opinion polls,

attitudinal surveys, readership, radio listening and T.V. viewing surveys, knowledge-

awareness practice (KAP) studies, farm management studies, business management

studies, etc., required data are not available from secondary sources and they have to

be directly gathered from the primary sources.

In all cases where the available data are inappropriate, inadequate or obsolete, primary

data have to be gathered. .

Methods of Primary Data Collection

There are various methods of data collection. A Method is different from a Tool.While a method refers to the way or mode of gathering data, a tool is an instrument

used for the method. For example, a schedule is used for interviewing. The important

methods are (a) observation, (b) interviewing, (c) mail survey, (d) experimentation,

(e) simulation, and (f) projective technique.

Observation involves gathering of data relating to the selected research by viewing

and/or listening. Interviewing involves face-to-face con-versation between the

investigator and the respondent. Mailing is used for collecting data by getting

questionnaires completed by respondents. Ex-perimentation involves a study of

independent variables under controlled conditions. Experiment may be conducted in a

laboratory or in field in a natural setting. Simulation involves creation of an artificial

situation similar to the actual life situation. Projective methods aim at drawing

inferences on the characteristics of respondents by presenting to them stimuli. Each

method has its advantages and disadvantages.

Choice of Methods of Data Collection

Which of the above methods of data collection should be selected for a proposed

research project? This is one of the questions to be considered while designing the

research plan. One or More methods has/have to be chosen. No method is universal.


22/34

Each method's unique features should be compared with the needs and conditions of

the study and thus the choice of the methods should be decided.

OBSERVATION

Meaning and Importance

Observation means viewing or seeing. We go on observing some thing or other while

we are awake. Most of such observations are just casual and have no specific purpose.

But observation as a method of data collection is different from such casual viewing.

Observation may be defined as a systematic viewing of a specific phenomenon in its

proper setting or the specific purpose of gathering data for a particular study.

Observation as a method includes both 'seeing' and 'hearing.' It is accompanied by

perceiving as well.

Observation also plays a major role in formulating and testing hypothesis in social

sciences. Behavioural scientists observe interactions in small groups; anthropologists

observe simple societies, and small com-munities; political scientists observe the

behaviour of political leaders and political institutions.

Types of Observation

Observation may be classified in different ways. With reference to the investigatorsrole, it may be classified into (a) participant observation, and (b) non-participant

observation. In terms of mode of observation, it may be classified into (c) directobservation, and (d) indirect observation. With reference to the rigour of the system

adopted, observation is classified into (e) controlled observation, and (f) uncontrolled

observation

EXPERIMENTATION

Experimentation is a research process used to study the causal relationships betweenvariables. It aims at studying the effect of an inde-pendent variable on a dependent

variable, by keeping the other inde-pendent variables constant through some type ofcontrol. For example, a -social scientist may use experimentation for studying the

effect of a method of family planning publicity on people's awareness of family plan-

ning techniques.

Why Experiment?


23/34

Experimentation requires special efforts. It is often extremely difficult to design, and

it is also a time consuming process. Why should then one take such trouble? Why not

simply observe/survey the phenomenon? The fundamental weakness of any non-

experimental study is its inability to specify causes and effect. It can show only

correlations between variables, but correlations alone never prow causation. The

experiment is the only method, which can show the effect of an independent variableon dependent variable. In experimentation, the researcher can manipulate the

independent variable and measure its effect on the dependent variable. For example,

the effect of various types of promotional strategies on the sale of a given product can

be studies by using different advertising media such as T.V., radio and Newspapers.

Moreover, experiment provides the opportunity to vary the treatment (experimentalvariable) in a systematic manner, thus allowing for the isolation and precise

specification of important differences.

Applications

The applications of experimental method are Laboratory Experiment, and Field

Experiment.

SIMULATION

Meaning

Simulation is one of the forms of observational methods. It is a process of conducting

experiments on a symbolic model representing a phenomenon. Abelson defines

simulation as the exercise of a flexible imitation of processes and outcomes for thepurpose of clarifying or explaining the underlying mechanisms involved. It is asymbolic abstrac-tion, simplification and substitution for some referent system. In

other words, simulation is a theoretical model of the elements, relations and processes

which symbolize some referent system, e.g., the flow of money in the economic

system may be simulated in a operating model consisting of a set of pipes through

which liquid moves. Simulation is thus a techni-que of performing sampling

experiments on the model of the systems. The experiments are done on the model

instead of on the real system, because the latter would be too inconvenient and

expensive.

Simulation is a recent research technique; but it has deep roots in history. Chess has

often been considered a simulation of medieval warfare.

INTERVIEWING


24/34

Definition

Interviewing is one of the major methods of data collection. It may be defined as two-

way systematic conversation between an investigator and an informant, initiated for

obtaining information relevant to as a specific study.

It involves not only conversation, but also learning from the respondents gestures,facial expressions and pauses, and his environment. Interviewing requires face-to-face

contact or contact over telephone and calls for interviewing skills. It is done by using

a structured schedule or an unstructured guide.

Importance

Interviewing may be us either as a main method or as a supplemen-tary one in studies

of persons. Interviewing is the only suitable method for gathering information from

illiterate or less educated respondents. It is useful for collecting a wide range of datafrom factual demographic data to highly personal and intimate information relating to

a person's opinions, attitudes, values, beliefs, past experience and future intentions.

When qualitative information is required or probing is necessary to draw out fully,

then interviewing is required. Where the area covered for the survey is a compact, or

when a sufficient number of qualified interviewers are available, personal interview is

feasible.

Interview is often superior to other data-gathering methods. People are usually more

willing to talk than to write. Once rapport is established, even confidential information

may be obtained. It permits probing into the context and reasons for answers toquestions.

Interview can add flesh to statistical information. It enables the inves-tigator to grasp

the behavioural context of the data furnished by the respondents. It permits the

investigator to seek clarifications and brings to the forefront those questions, that, for

one reason or another, respondents do not want to answer.

Types of Interviews

The interviews may be classified into: (a) structured or directive interview, (b)unstructured or non-directive interview, (c) focused inter-view, and (d) clinical

interview and (e) depth interview.

Telephone Interviewing

Telephone interviewing is a non-personal method of data collection.


25/34

Group Interviews

Group interview may be defined as a method of collecting primary data in which a

number of individuals with a common interest interact with each other. In a personal

interview, the flow of information is multidimensional.

Interviewing Process

The interviewing process consists of the following stages:

Preparation.

Introduction

Developing rapport

Carrying the interview forward

Recording the interview, and

Closing the interview

PANEL METHOD

The panel method is a method of data collection, by which data is collected from the

same sample respondents at intervals either by mail or by personal interview. This is

used for longitudinal studies on economic conditions, expenditure pattern; consumer

behaviour, recreational pattern, effectiveness of advertising, voting behaviour, and so

on. The period, over which the panel members are contacted for information may

spread over several months or years. The time interval at which they are contacted

repeatedly may be 10 or 15 days, or one or two months depending on the nature of the

study and the memory span of the respondents.

Characteristics

The basic characteristic of the panel method is successive collection of data on the

same items from the same persons over a period of time. The type of information to

be collected should be such facts that can be accurately and completely furnished by

the respondent without any reservation. The number of item should be as few as

possible so that they could be furnished within a few minutes, especially when mail

survey is adopted. The average amount of time that a panel member has to spend each

time for reporting can be determined in a pilot study. The panel method requires

carefully selected and well-trained field workers and effective supervision over their

work.-

Types of Panels


26/34

The panel may be static or dynamic. A static or continuous panel is one in which the

membership remains the same throughout the life of the panel, except for the

members who drop out. The dropouts are not replaced.

MAIL SURVEY

Definition

The mail survey is another method of collecting primary data. This method involves

sending questionnaires to the respondents with a request to complete them and return

them by post. This can be used in the case of educated respondents only. The mail

questionnaire should be simple so that the respondents can easily understand the

questions and answer them. It should preferably contain mostly closed-end and

multiple-choice questions so that it could be completed within a few Minutes.

The distinctive feature of the mail survey is that the questionnaire is self-administered

by the respondents themselves and the responses are recorded by them, and not by the

investigator as in the case of personal interview method. It does not involve face-to-

face conversation between the investigator and the respondent. Communication is

carried out only in writing and this requires more cooperation from the respondents

than does verbal communication.

Alternative modes of sending questionnaires

There are some alternative methods of distributing questionnaires to the respondents.

They are: (1) personal delivery, (2) attaching question-naire to a, product, (3)

advertising questionnaire in a newspaper or magazine, and (4) newsstand inserts.

PROJECTIVE TECHNIQUES

The direct methods of data collection, viz., personal interview, telephone interview

and mail survey rely on respondents' own report of their behaviour, beliefs, attitudes,

etc. But respondents may be unwilling to discuss controversial issues or to reveal

intimate information about themselves or may be reluctant to express their true views

fearing that they are generally disapproved. In order to overcome these limitations,indirect methods have been developed. Projective Techniques are such indirect

methods. They become popular during 1950s as a part of motivation research.

Meaning

Projective techniques involve presentation of ambitious stimuli to the respondents for

interpretation. In doing so, the respondents reveal their inner characteristics. The


27/34

stimuli may be a picture, a photograph, an inkblot or an incomplete sentence. The

basic assumption of projective techniques is that a person projects his own thoughts,

ideas and attributes when he perceives and responds to ambiguous or unstructured

stimulus materials. Thus a person's unconscious operations of the mind are brought to

a conscious level in a disguised and projected form, and the person projects his inner

characteristics.

Types of Projective Techniques

Projective Techniques may be divided into three broad categories: (a) visual

projective techniques (b) verbal projective techniques, and (c) Expressive techniques.

SOCIOMETRY

Sociometry is a method for discovering, describing and evaluating social status,structure, and development through measuring the extent of acceptance or rejection

between individuals in groups. Franz defines sociometry as a method used for thediscovery and manipulation of social configurations by measuring the attractions and

repulsions between in-dividuals in a group. It is a means for studying the choice,communication and interaction patterns of individuals in a group. It is concerned with

attractions and repulsions between individuals in a group. In this method, a person is

asked to choose one or more persons according to specified criteria, in order to find

out the person or persons with whom he will like to associate.

Sociometry Test

The basic technique in sociometry is the sociometric test. This is a test under which

each member of a group is asked to choose from all other members those with whom

he prefers to associate in a specific situation. The situation must be a real one to the

group under study, e.g., 'group study', 'play', 'class room seating' for students of a

public school.

A specific number of choices, say two or three to be allowed is determined with

reference to the size of the group, and different levels of preferences are designated

for each choice.

Suppose we desire to find out the likings and disliking of persons in a work group

consisting of 8 persons. Each person is asked to select 3 persons in order or preference

with whom he will like to work on a group assignment. The levels of choices are

designated as: the first choice by the' number 1, the second by 2, and the third by 3.


28/34

4) How should a conceptual model relevant to the problem under study be selected?

Ans) Unit-03-Selection and Formulation of a Research Problem

Structure:

3.1 Meaning of Research Problem

Objectives

3.2 Choosing the Problem

3.3 Review of Literature

3.4 Formulating the Problem

3.4.1 Internal Criteria

3.4.2 External Criteria

3.5 Objective of Formulating the Problem

3.6 Techniques involved in Formulating the Problem

3.7 Criteria of Good Research Problem

Self Assessment Questions I

3.8 Summary

3.1 Meaning of Research Problem

Research really begins when the researcher experiences some difficulty, i.e., a problemdemanding a solution within the subject-are of his discipline. This general area of interest,however, defines only the range of subject-matter within which the researcher would see andpose a specific problem for research. Personal values play an important role in the selection of atopic for research. Social conditions do often shape the preference of investigators in a subtle andimperceptible way.

The formulation of the topic into a research problem is, really speaking the first step in ascientific enquiry. A problem in simple words is some difficulty experienced by the researcher in atheoretical or practical situation. Solving this difficulty is the task of research.

R. L. Ackoffs analysis affords considerable guidance in identifying problem for research. Hevisualizes five components of a problem.

1) Research-consumer: There must be an individual or a group which experiences some difficulty.


29/34

2) Research-consumers Objectives: The research-consumer must have available, alternativemeans for achieving the objectives he desires.

3) Alternative Means to Meet the Objectives: The research-consumer must have available,alternative means for achieving the objectives he desires.

4) Doubt in Regard to Selection of Alternatives: The existence of alternative courses of action innot enough; in order to experience a problem, the research consumer must have some doubt as towhich alternative to select.

5) There must be One or More Environments to which the Difficulty or Problem Pertains: A changein environment may produce or remove a problem. A research-consumer may have doubts as towhich will be the most efficient means in one environment but would have no such doubt inanother.

Objectives:

After studying this unit you should be able to understand:

The meaning of Research Problem

Choosing the problem

Review of Literature

Criteria for formulating the problem

Objective of Formulating the Problem

Techniques involved in Formulating the Problem

Criteria of Good Research Problem

3.2 Choosing the Problem

The selection of a problem is the first step in research. The term problem means a question orissue to be examined. The selection of a problem for research is not an easy task; it self is aproblem. It is least amenable to formal methodological treatment. Vision, an imaginative insight,plays an important role in this process. One with a critical, curious and imaginative mind and issensitive to practical problems could easily identify problems for study.

The sources from which one may be able to identify research problems or develop problems

awareness are:

Review of literature

Academic experience

Daily experience

Exposure to field situations


30/34

Consultations

Brain storming

Research

Intuition

3.3 Review of Literature

Frequently, an exploratory study is concerned with an area of subject matter in which explicithypothesis have not yet been formulated. The researchers task then is to review the availablematerial with an eye on the possibilities of developing hypothesis from it. In some areas of thesubject matter, hypothesis may have been stated by previous research workers. The researcherhas to take stock of these various hypotheses with a view to evaluating their usefulness for furtherresearch and to consider whether they suggest any new hypothesis. Sociological journals,economic reviews, the bulletin of abstracts of current social sciences research, directory ofdoctoral dissertation accepted by universities etc afford a rich store of valuable clues. In addition

to these general sources, some governmental agencies and voluntary organizations publish listingsof summaries of research in their special fields of service. Professional organizations, researchgroups and voluntary organizations are a constant source of information about unpublished worksin their special fields.

3.4 Formulating the Problem

The selection of one appropriate researchable problem out of the identified problems requiresevaluation of those alternatives against certain criteria, which may be grouped into:

3.4.1 Internal Criteria

Internal Criteria consists of:

1) Researchers interest: The problem should interest the researcher and be a challenge to him.Without interest and curiosity, he may not develop sustained perseverance. Even a small difficultymay become an excuse for discontinuing the study. Interest in a problem depends upon theresearchers educational background, experience, outlook and sensitivity.

2) Researchers competence: A mere interest in a problem will not do. The researcher must becompetent to plan and carry out a study of the problem. He must have the ability to grasp anddeal with int. he must possess adequate knowledge of the subject-matte

priya mam notes

Documents