3 .RESEARCH METHODOLOGY

3.1 RESEARCH

“Research means a search for knowledge”, sometimes, it may refer to scientific and

systematic search, pertinent information on a specific topic, in fact research is an art or a

scientific investigation. Morey defines” research as a` systemized effort to gain new

knowledge”.

According to Clifford research comprises, “defining and redefining problem,

formulating hypothesis or suggested solution; collecting organizing a devaluating data

making deductions and reaching conclusion an at last carefully testing the conclusion to

determine whether they fit the formulating hypothesis”.

LOCATION OF THE STUDY

“Study on quality of work life” was conducted in Leather Crafts India Pvt Ltd

Mahindra city.

3.2 RESEARCH PROCESS

In research process, the first and foremost step is defining and selecting a research

problem. A researcher should find the problem first, and then he should formulate it so that it

becomes susceptible to research. For a systematic presentation, the process of research may

be classified under three stages- primary stage, secondary stage, and the tertiary stage.

THE PRIMARY STAGE INCLUDES

Observation

Formulating research problems

Documentation

Research design

THE SECONDARY STAGE INCLUDES

Project planning

Data collection

Questionnaire preparation

Analysis of data

Testing of hypothesis

Inference

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THE TERTIARY STAGE INCLUDES

Report writing

Observation, suggestion and conclusion

Preparation of bibliography

OBSERVATION

Research starts with observation, which leads to curiosity to learn more about what

has been observed. The observation method is mainly used because of simplicity, usefulness

in the framing of hypothesis, its accuracy; the possibility of getting convincing results, the

possibility of rest of validity etc, to be precise observation tends to the basis of any research.

FORMULATING RESEARCH PROBLEM

The research problem undertaken for study must be carefully selected. The problem

must be defined thoroughly and should be framed in to meaningful terms from the analytical

point of view. The area of working must be decided.

DOCUMENTATION

The documentary source is an important source of information for a researcher. A

document is anything in writing a record, files or diaries, published or unpublished which can

be extracted and used in research. It is very valuable source of information for a research.

Documentation is the process of collecting and extracting the documents which are relevant

to research.

3.3 RESEARCH DESIGN

After identifying the variables in the problem situation we can create the theoretical

framework of the study, the next step is to design the research in the way that the requisite

data can be gathered and analyzed to arrive at a solution. Preparation of research design

involves selection of means of obtaining information, time available for research and

selection of method of tabulation and presentation of data. The various method and

techniques that are adopted to extract the most reliable information given below.

Type of research : Descriptive research.

Research approach : Survey method.

Source of data : Primary and Secondary data.

Sample size : 120.

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Mode of data collection : Personal interview method.

Data collection instrument : Questionnaire.

Sampling design : Simple random sampling.

This research design is arrangement of condition for collection and analysis of data in

the manner that aim to combine relevance to the research purpose and the procedure.

3.4 TYPE OF RESEARCH

DESCRIPTIVE RESEARCH DESIGN

Descriptive research includes surveys and fact, findings, enquiries. It is a descriptive

of affairs existing at present. The important characteristic of is method is that the researcher

has no control over the variables. He can report about what is happening and what has

happened.

The term descriptive research refers to the type of research question, design, and data

analysis that will be applied to a given topic. Descriptive statistics tell what is, while

inferential statistics try to determine cause and effect.

METHODS OF DATA COLLECTION

The study involves collection of both primary data and secondary data for making a

meaningful inference on the topic of the study.

PRIMARY DATA

The primary data has collected for the study was through interviews and

questionnaire.

METHODS OF PRIMARY DATA COLLECTION

There are 2 methods for collecting primary data

Questionnaire survey method

Experiments

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SECONDARY DATA

The secondary data refer to the information gathered by researcher from the sources

already existing.

METHODS OF SECONDARY DATA COLLECTION

Secondary data was collected through the following

Websites/search engines

Books

Company previous records

QUESTIONNAIRE PREPARATION

The basic requisite of any research study is the appropriate data which can be

collected with the help of a schedule or questionnaire. With the help of questionnaire it is

easy to determine the involvement level of so many employees in the organisation.

PILOT SURVEY

Before collecting the relevant data to test the hypothesis, it is essential to ascertain the

applicability of the instrument to the population being studied. Hence, a pilot study was

undertaken with an objective to evaluate the tools prepared for the study and to find whether

they are providing the information required.

The sample size for the pilot study is 10 in number. The result of the pilot study

required certain changes in the questionnaire. This resulted in shifting of a few dimension

from the original order.

PRE-TESTING

Initially a questionnaire was prepared comprising of open and closed ended to study

the problem. The questionnaire was distributed and tested among respondents to check for its

effectiveness. That is the effectiveness was checked with the respect to the following:

Correct wordings

Understanding of phrases

Sequence of questions

Any inclusion of jargons

The time factor of respondents

To pre-test these aspects of the questionnaire it was distributed to the actual target

group i.e, to one person from each department. After testing the questionnaire the areas of

difficulties faced by respondent were spotted and necessary changes were made.

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TYPE OF QUESTIONS

Linker’s scaling questions

Satisfaction scaling questions

Rank questions

Rating questions

HYPOTHESIS TESTING

Ho – Null hypothesis (there is no significant relationship between the variables)

Ha – Alternate hypothesis (there is significant relationship between the variables)

After analyzing the data, hypothesis testing is done. It will result in either accepting or

rejecting the hypothesis.

INFERENCE

After testing the hypothesis, the researcher comes out with his conclusion. The

explanation of theory can also be considered as inference.

PREPARATION OF REPORT AND PRESENTATION OF REPORT

Finally, the researcher has to prepare a final report along with conclusion and

suggestion.

3.5 SAMPLE SIZE

N=10, P=0.8, Q=0.2

Therefore Sample S.D = √ (pq/n)

= √ (0.8*0.2)/15

= 0.1032

Sample size (n) = Z²*(S.D) ²/e²

Z=Standard normal value

e = Error limit

The organisation preferred limit error to 2% at 95% confidence limit

Z = 1.96

N = Z²*(S.D) ²/e²

= (1.96)²*(0.1032)²/(0.02)²

= 102.0

Therefore Sample size = 110

3.6 STATISTICAL TOOLS USED FOR ANALYSIS

The data collected are classified, analyzed and collected. The statistical tools are

applied for the analysis of the data. The tools used are percentage analysis, chi – square test,

ANOVA, k-s test and line test.

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1) PERCENTAGE ANALYSIS

Percentage refer is a special kind ratio. Percentage is used in making comparison

between two or more series of data. They are used to describe relationship. More over

percentages can be use to compare the relative terms of the distribution of two or more

series of data.

FORMULAS

Percentage of respondents = no. of respondents*100/total no. Of respondents

2) CHI – SQUARE TEST

Chi –square is a non-parametric technique; most commonly used for a research to test

the analysis. The main objective of chi-square is to determine whether significant difference

exist among group of data. The chi square test provides a method testing the association

between the row and column in a two way table.

Formula:

CHI-SQUARE TEST = ∑[(Oi – Ei)2]/Ei

Oi=Observed frequency

Ei=Expected frequency

Degree of freedom= (r-1)(c-1)

Where r represents the number of rows in two way table and c represent the number

of columns.

3) ANOVA

In statistics, analysis of variance (ANOVA) is a collection of statistical models, and

their associated procedures, in which the observed variance in a particular variable is

portioned into components attributable to different sources of variance. In its simplest form

ANOVA provides a statistical test of whether or not the means of several groups are all

equal, and therefore generalizes t-test to more than two groups. Doing multiple two-sample

t-tests would result in an increased chance of committing a type I error. For this reason,

ANOVAs as useful in comparing two, three or more means.

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a) ONE WAY ANOVA

In the one-way ANOVA, there is just one factor, and the null hypothesis is that the

population means are equal for the respective treatments, or factor levels. Treatments are

randomly assigned to the persons or test units in the experiment, so this method is also

referred to as the components: an overall mean, the effect of a treatment, and a random error

due to sampling.

SOURCES

OF

VARIATION

SUM OF

SQUARE

DEGREE

OF

FREEDOM

MEAN SUM

OF SQUARE

VARIANCE

RATIO

BETWEEN

SAMPLESSSB C-1 MSB=SSB/C-1

F=MSB/MSWWITHIN

SAMPLESSSW N-C MSW=SSW/N-C

TOTAL

SAMPLESSST N-1 MST=SST/NO -1

The variance ratio is

F = Between column variance/ Within column variance

(Or)

= Greater variance/ smaller variances

b) TWO-WAY ANOVA

In two-way ANOVA, there are two factors, each of which operates on two or more

levels. In this design, it is no longer appropriate to refer to the factor levels as treatments,

since each combination of their levels constitutes a separate treatment. The two-way

ANOVA examines the main effects of the level of both factors as well as interactive effects

associated with the combinations of their levels. Accordingly, significance tests include

those for the main effects of each factor and for interactive effects between the

combinations of factor levels. The numerator degrees of freedom comes from each effect,

and the denominator degrees of freedom is the degree of freedom for the within variance in

each case.

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SOURCES

OF

VARIATION

SUM OF

SQUARES

DEGREE

OF

FREEDOM

MEAN

SUM OF SQUARE

VARIANCE

RATIO

BETWEEN

COLUMNSSSC C-1 MSC=SSC/C-1

FC=MSC/MSEBETWEEN

ROWSSSR R-1 MSR=SSR/R-1

RESIDUAL

(ERROR) SSE (C-1)(R-1) MSE=SSE/(C-1)(R-1)FR=MSR/MSE

TOTAL SST N-1

4) KOLMOGOROV-SMIRNOV TEST FOR NORMALITY

The Kolmogorov-Smirnov test for normality is an alternative to the chi-square test for

normality. Compared to the chi-square method, this test does not require any minimum

values for expected frequencies and can be used with small as well as large sample sizes. The

data must be a random sample from the population, and the variable being observed or

measured has to be at least interval in its scale of measurement. This test involves two

cumulative relative frequencies: one that is derived from the actual data observed, the other

constructed under the assumption that the null hypothesis is true, and relying on the mean and

standard deviation of the sample data. A comparison is made between these cumulative

relative frequencies, and the test statistic is the maximum amount of divergence between

them.

The formula for calculating Kolmogorov-Smirnov test is

Calculated value = maximum | Oi – Ei |

Where Oi = observed cumulative frequency

Ei = expected observed cumulative relative frequency.

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