QUANTITATIVE RESEARCH

LECTURE :

YUNIK SUSANTI, M.Pd

WRITTEN BY :

Ella Yulita

MAYA FITA LINA (11.1.01.08.0124)

HABIB WIRAWAN (11.1.01.08.0085)

Nova Rinda S.

YOPPY DWUY RISHADY (11.1.01.08.0224)

ENGLISH DEPARTMENT

UNIVERSITY OF NUSANTARA PGRI KEDIRI

2012/20113

PREFACE

Praise be to Allah, the lord of the world and the sustainer of universe, for giving us his

blessing and mercy. Due to those, we can finish this Quantitative research paper on time.

This paper about quantitative researchis compiled to fulfill the quantitative research

presentation assignment lectured by Yunik Susanti, M.Pd. It is necessary for the writer to express

our gratitude to some people who have been so kindly and successfully to handle this program

even more after the writer having a lot of experiences and knowledge during the lecturing

program. We really hope this paper will be very useful for everyone who searches for the

references of Quantitative research subject.

We realize that this paper is far from perfect. So, the constructional critiques and

suggestions are happily welcomed.

Maret 2013

Author

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TABLE OF CONTENTS

COVER .............................................................................................................................. i

PREFACE ......................................................................................................................... ii

TABLE OF CONTENTS ................................................................................................. iii

CHAPTER I INTRODUCTION ..................................................................................... 1

CHAPTER II CONTENT................................................................................................. 2

I. What is Quantitatif Research................................................................................... 2

II. When do we use quantitative methods?................................................................... 4

III. When shouldn’t we use quantitative methods? ....................................................... 5

IV. The Characteristics of Quantitative research .......................................................... 5

V. Types of Quantitative Research .............................................................................. 6

VI. The process of doing Quantitative Research .......................................................... 9

CHAPTER III CONCLUSION........................................................................................ 11

BIBLIOGRAPHY.............................................................................................................. 12

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CHAPTER I

INTRODUCTION

We couldn’t doing everything by nothing. As reality that students in college have to do some research for their final papper, it’s necessary for us to know earlier all about the preparation especially for the basic theory and knowledge for research. Having a lot of knowledge all about research will deliver us into the right and the esier way to do research. Instead, having no basic knowledge about research will make us confuse to do what we should do. This papper is compiled for the purpose to make comprehension about Quantitative Research as a method we can choose for doing research.

Quantitative Reasearch is one of the methods use in researches which relate to the numerical data. To decide using quantitative method for your research, it necesosary to know all about this one. This method using numerical data as the main and the major of the data result from the phenomena we’ve found. This is closely connected to the definition: analysis using mathematically-based methods. And also the characteristics of the Quantitative research will be appeared as related to the undersanding the definition of this method. Beside that in this papper is going explained about wheter we need to use Quantitative Research or not to make us clearly catch and not going fall to the ambigious understanding. In the last part we tried to put the smart steps of doing Quantitative research we need apply. Start from the first step is called Theory to the Writing up your findings by explaining briefly.

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CHAPTER II

CONTENT

I. What is Quantitative research?Quantitative research is the numerical representation and manipulation of observations

for the purpose of describing and explaining the phenomena that those observations reflect. It

is used in a wide variety of natural and social sciences, including physics, biology,

psychology, sociology and geology (Wikipedia Encyclopedia, 2005).

In addition, according to Cohen (1980), quantitative research is defined as social research

that employs empirical methods and empirical statements. He states that an empirical

statement is defined as a descriptive statement about what “is” the case in the “real world”

rather than what “ought” to be the case. Typically, empirical statements are expressed in

numerical terms, another factor in quantitative research is that empirical evaluations are

applied. Empirical evaluations are defined as a form that seeks to determine the degree to

which a specific program or policy empirically fulfills or does not fulfill a particular standard

or norm.

Moreover, Creswell (1994) has given a very concise definition of quantitative research as

a type of research that is `explaining phenomena by collecting numerical data that are

analyzed using mathematically based methods (in particular statistics).'

Let's study this definition step by step. The first element is explaining phenomena. This is

a key element of all research, be it quantitative or qualitative. When we set out to do some

research, we are always looking to explain something. In education this could be questions,

for example, `Does constructivism work for teaching English in an Indonesian context?', or

`What factors influence student achievement in learning English as a foreign language?'

The specificity of quantitative research lies in the next part of the definition. In

quantitative research we collect numerical data. This is closely connected to the final part of

the definition: analysis using mathematically-based methods. In order to be able to use

mathematically based methods our data have to be in numerical form. This is not the case for

qualitative research. Qualitative data are not necessarily or usually numerical, and therefore

cannot be analyzed using statistics.

The last part of the definition refers to the use of mathematically based methods, in

particular statistics, to analyze the data. This is what people usually think about when they

think of quantitative research, and is often seen as the most important part of quantitative

studies. This is a bit of a misconception. While it is important to use the right data analysis

tools, it is even more important to use the right research design and data collection

instruments. However, the use of statistics to analyze the data is the element that puts a lot of

people off doing quantitative research, because the mathematics underlying the methods seem

complicated and frightening.

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Therefore, because quantitative research is essentially about collecting numerical data to

explain a particular phenomenon, particular questions seem immediately suited to being

answered using quantitative methods. For example,

How many students learning Experiential English I get A’s in the first semester?

What percentage of the students learning Experiential English I has negative attitudes

towards the course?

On average, is there any significant difference between the general English proficiency of

the students learning Foundation English and Experiential English courses?

These are all questions we can look at quantitatively, as the data we need to collect are

already available to us in numerical form. However, there are many phenomena we might

want to look at, but which don't seem to produce any quantitative data. In fact, relatively few

phenomena in education actually occur in the form of `naturally' quantitative data.

Luckily, we are far less limited than what might appear above. Many data that do not

naturally appear in quantitative form can be collected in a quantitative way. We do this by

designing research instruments aimed specifically at converting phenomena that don't

naturally exist in quantitative form into quantitative data, which we can analyze statistically.

Examples of this are attitudes and beliefs. We might want to collect data on students' attitudes

to their school and their teachers. These attitudes obviously do not naturally exist in

quantitative form. However, we can develop a questionnaire that asks pupils to rate a number

of statements (for example, `I think school is boring') as either agree strongly, agree, disagree

or disagree strongly, and give the answers a number (e.g. 1 for disagree strongly, 4 for agree

strongly). Now we have quantitative data on pupil attitudes to school. In the same way, we

can collect data on a wide number of phenomena, and make them quantitative through data

collection instruments like questionnaires or tests. We will later look at how we can develop

instruments for this particular purpose.

The number of phenomena we can study in this way is almost unlimited, making

quantitative research quite flexible. However, not all phenomena are best studied using

quantitative methods. While quantitative methods have some notable advantages, they also

have disadvantages. This means that some phenomena are better studied using qualitative

methods.

In short, quantitative research generally focuses on measuring social reality. Quantitative

research and/or questions are searching for quantities in something and to establish research

numerically. Quantitative researchers view the world as reality that can be objectively

determined so rigid guides in the process of data collection and analysis are very important.

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II. When do we use quantitative methods?

If we take a pragmatic approach to research methods, first of all we need to find out what

kinds of questions are best answered using quantitative as opposed to qualitative methods.

There are six main types of research questions that quantitative research is particularly

suited to find an answer to:

1. The first is when we want a quantitative answer.

For example, `If the students have their choice, how many of them choose to study

Experiential English I?' or `How many English teachers in the Language Institute would

like to teach Experiential English courses instead of Foundation English courses?' The

reason why we need to use quantitative research to answer this kind of question is

obvious. Qualitative, non-numerical methods will obviously not provide us with the

numerical answer we want.

2. Numerical change can likewise only accurately be studied using quantitative methods.

For example, ‘Are the numbers of students in our university rising or falling?’ or ‘Is

achievement in English of our students going up or down?’ We would need to do a

quantitative study to find out the answer.

3. Quantitative research is useful for conducting audience segmentation.

It is done by dividing the population into groups whose members are similar to each

other and distinct from other groups. Quantitative research is used to estimate the size of

an audience segment as a follow-up step to a qualitative study to quantify results obtained

in a qualitative study and to verify data obtained from qualitative study.

4. Quantitative research is also useful to quantify opinions, attitudes and behaviors and find

out how the whole population feels about a certain issue.

For example, when we want to find out the exact number of people who think a

certain way, to set baselines (e.g., to measure consumer attitudes regarding an issue prior

to a campaign), and to ensure that the students can share some comments or ideas to a new

course.

5. Quantitative research is suitable to explain some phenomena.

For instance, ‘What factors predict the general English proficiency of the fourth

year students?’ or ‘What factors are related to changes in student English achievement

over time?’ This kind of question can be studied successfully using quantitative methods,

and many statistical techniques have been developed to make us predict scores on one

factor or variable (e.g. student English proficiency) from scores on one or more other

factors or variables (e.g. learning habits, motivation, attitude).

6. The final activity for which quantitative research is especially suited is the testing of

hypotheses.

However, the ultimate goal of any quantitative research is to generalize the “truth” found

in the samples to the population.

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III. When shouldn’t we use quantitative methods?

As mentioned above, while quantitative methods are good at answering these four types

of questions, there are other types of question that are not well suited to quantitative methods:

1. The first situation where quantitative research will fail is when we want to explore a

problem in depth. Quantitative research is good at providing information in breadth from

a large number of units. But when we want to explore a problem or concept in depth,

quantitative methods are too shallow. To get really under the skin of a phenomenon, we

need to go for ethnographic methods, interviews, in-depth case studies and other

qualitative techniques.

2. As mentioned earlier, quantitative research is well-suited for the testing of theories and

hypotheses. What quantitative methods cannot do very well is to develop hypotheses and

theories. The hypotheses to be tested may come from a review of the literature or theory,

but can also be developed using exploratory qualitative research.

3. If issues to be studied are particularly complex, an in-depth qualitative study (a case

study, for example) is more likely to pick up on this than a quantitative study. This is

partly because there is a limit to how many variables can be looked at in any one

quantitative study, and partly because in quantitative research it is the researcher who

defines the variables to be studied. In qualitative research unexpected variables may

emerge.

4. Finally,while quantitative methods are better at looking at cause and effect (causality, as

it is known), qualitative methods are more suited to looking at the meaning of particular

events or circumstances.

What then do we do if we want to look at both breadth and depth, or at both causality and

meaning? In these situations, it is best to use a so-called a mixed method design in which we

use both quantitative (for example, a questionnaire) and qualitative (for example, a number of

case studies) methods. Mixed method research is a flexible approach where the research

design is determined by what we want to find out rather than by any predetermined

epistemological position. In mixed method research, qualitative or quantitative components

can predominate or both can have equal status.

IV. The Characteristics of Quantitative research

CONTROL, this is the most important element because it enables the scientist to identify

the causes of his or her observations. Experiments are conducted in an attempt to answer

certain questions. They represent attempts to identify why something happens, what causes

some event, or under what conditions an event does occur. Control is necessary in order to

provide unambiguous answers to such questions. To answer questions in education and social

science we have to eliminate the simultaneous influence of many variables to isolate the cause

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of an effect. Controlled inquiry is absolutely essential to this because without it the cause of

an effect could not be isolated.

OPERATIONAL DEFINITION, this means that terms must be defined by the steps or

operations used to measure them. Such a procedure is necessary to eliminate any confusion in

meaning and communication. Consider the statement `Anxiety causes students to score poorly

in tests'. One might ask, `What is meant by anxiety?' Stating that anxiety refers to being tense

or some other such term only adds to the confusion. However, stating that anxiety refers to a

score over a criterion level on an anxiety scale enables others to realize what you mean by

anxiety. Stating an operational definition forces one to identify the empirical referents, or

terms. In this manner, ambiguity is minimized. Again, introversion may be defined as a score

ona particular personality scale, hunger as so many hours since last fed, and social class as

defined by occupation.

REPLICATION. To be replicable, the data obtained in an experiment must be reliable.

That is, the same result must be found if the study is repeated. If observations are not

repeatable, our descriptions and explanations are thought to be unreliable.

HYPOTHESIS TESTING: The systematic creation of a hypothesis and subjecting it to

an empirical test.

V. Types of Quantitative Research

Descriptive

research

Correlational

research

Causal-

comparative/quasi-

experimental

research

Experimental

research

Seeks to describe

the current status of

an identified

variable. These

research projects are

designed to provide

systematic

information about a

phenomenon.  The

researcher does not

usually begin with a

hypothesis, but is

Attempts to

determine the

extent of a

relationship

between two or

more variables

using statistical

data.  In this type

of design,

relationships

between and

among a number of

Attempts to establish

cause-effect

relationships among

the variables.  These

types of design are

very similar to true

experiments, but

with some key

differences.  An

independent variable

is identified but not

manipulated by the

Often called true

experimentation,

uses the scientific

method to establish

the cause-effect

relationship among a

group of variables

that make up a

study.  The true

experiment is often

thought of as a

laboratory study, but

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likely to develop

one after collecting

data.  The analysis

and synthesis of the

data provide the test

of the hypothesis. 

Systematic

collection of

information requires

careful selection of

the units studied and

careful measurement

of each variable.

Examples of

Descriptive

Research:

A description of

how second-

grade students

spend their time

during summer

vacation

A description of

the tobacco use

habits of

teenagers  

A description of

how parents

feel about the

twelve-month

school year

A description of

the attitudes of

scientists

regarding

global warming 

A description of

facts are sought

and interpreted.

This type of

research will

recognize trends

and patterns in

data, but it does not

go so far in its

analysis to prove

causes for these

observed patterns.

Cause and effect is

not the basis of this

type of

observational

research. The data,

relationships, and

distributions of

variables are

studied only.

Variables are not

manipulated; they

are only identified

and are studied as

they occur in a

natural setting. 

Sometimes

correlational

research is

considered a type

of descriptive

research, and not as

its own type of

research, as no

variables are

manipulated in the

experimenter, and

effects of the

independent variable

on the dependent

variable are

measured. The

researcher does not

randomly assign

groups and must use

ones that are

naturally formed or

pre-existing groups.

Identified control

groups exposed to

the treatment

variable are studied

and compared to

groups who are not. 

When analyses and

conclusions are

made, determining

causes must be done

carefully, as other

variables, both

known and

unknown, could still

affect the

outcome.   A causal-

comparative

designed study,

described in a

New York Times

article, "The Case

for $320.00

Kindergarten

Teachers," 

illustrates how

this is not always the

case; a laboratory

setting has nothing

to do with it.  A true

experiment is any

study where an effort

is made to identify

and impose control

over all other

variables except

one.  An

independent variable

is manipulated to

determine the effects

on the dependent

variables.  Subjects

are randomly

assigned to

experimental

treatments rather

than identified in

naturally occurring

groups

Examples of

Experimental

Research: 

The effect of a

new treatment

plan on breast

cancer

The effect of

positive

reinforcement

on attitude

toward school

The effect of

teaching with a

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the kinds of

physical

activities that

typically occur

in nursing

homes, and how

frequently each

occurs

A description of

the extent to

which

elementary

teachers use

math

manipulative.

study. 

Examples of

Correlational

Research:

The

relationship

between

intelligence

and self-

esteem 

The

relationship

between diet

and anxiety 

The

relationship

between an

aptitude test

and success in

an algebra

course 

The

relationship

between ACT

scores and the

freshman

grades 

The

relationships

between the

types of

activities used

in math

classrooms

and student

achievement 

causation must be

thoroughly assessed

before firm

relationships

amongst variables

can be made.

Examples of

Correlational

Research:

The effect of

preschool

attendance on

social maturity

at the end of the

first grade

The effect of

taking

multivitamins

on a students’

school

absenteeism

The effect of

gender on

algebra

achievement

The effect of

part-time

employment on

the achievement

of high school

students

The effect of

magnet school

participation on

student attitude

cooperative

group strategy

or a traditional

lecture approach

on students’

achievement

The effect of a

systematic

preparation and

support system

on children who

were scheduled

for surgery on

the amount of

psychological

upset and

cooperation

A comparison

of the effect of

personalized

instruction vs.

traditional

instruction on

computational

skill 

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The

covariance of

smoking and

lung disease

The effect of

age on lung

capacity 

VI. The process of doing Quantitative Research

There are nine parts to the process of conducting quantitative research:

1. Theory

The fact that we start off with theory signifies that a broadly deductive approach

to the relationship between theory and research is taken.

2. Hypothesis

A hypothesis is a tentative explanation that accounts for a set of fact that can be

tested by further investigation. For example, one hypothesis we might want to test could

be that the poverty causes low achievement, or that there is a relationship between

pupils’ self-esteem and the amount of time they spend watching television. Quantitative

researchers will design studies that allow us to test these hypotheses. We will collect the

relevant data (for example, parental income and school achievement) and use statistical

techniques to decide whether or not to reject or provisionally accept the hypothesis.

Accepting a hypothesis is always provisional, as new data may emerge that causes it to

be rejected later on.

3. Operationalization of concepts

This process is often referred to as measures of the concepts, a term that originally

derives from physics to refer to the operations by which a concept (such as temperature

or velocity) is measured (Bridgman 1927).

4. Selection of respondents or cases

This step entail the selection of a research site or sites and then the selection of

subject respondents. (Experimental researchers tend to call the people on whom they

conduct research 'subjects', whereas social survey researchers typically call them

'respondents'.) Thus, in social survey research an investigator must first be concerned to

establish an appropriate setting for his or her research. A number of decisions may be

involved. First, the researchers needed a community that would be appropriate for the

testing of the 'embourgeoisement' thesis (the idea that affluent workers were becoming

more middle class in their attitudes and lifestyles).

5. Research design

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The next step entails the selection of a research design. As we, have seen, the

selection of research design has implications for a variety ofissues, such as the external

validity of findings and researchers' ability to impute causality to their findings.

6. Collection of data

Step 6 simply refers to the fact that, once information has been collected, it must

be transformed into 'data'. In the context of quantitative research, this is likely to mean

that it must be prepared so that it can be quantified. With some information this can be

done in a relatively straightforward way-for example, for information relating to such

things as people's ages, incomes, number of years spent at school, and so on. Far other

variables, quantification will entail coding the information-that is, transforming it into

numbers to facilitate the quantitative analysis of the data, particularly if the analysis is

going to be carried out by computer. Codes act as tags that are placed on data about

people to allow the information to be processed by the computer. This consideration

leads into next Step.

7. Analysis of data

In this step, the researcher is concerned to use a number of techniques of

quantitative data analysis to reduce the amount of data collected, to test for relationships

between variables, to develop ways of presenting the results of the analysis to others,

and so on. On the basis of the analysis of the data, the researcher must interpret the

results of the analysis.

8. Findings

It is at this stage that the 'findings' will emerge. The researcher will consider the

connections between the findings that emerge out of Step 8 and the various

preoccupations that acted as the impetus of the research. If there is a hypothesis, is it

supported? What are the implications of the findings for the theoretical ideas that

formed the background tothe research? Then the research must be written.

9. Write up Findings/Conclusion

Then the research must be written up. It cannot take on significance beyond

satisfying the researcher's personal curiosity until it enters the public domain in some

way by being written up as a paper to be read at a conference or as a report to the

agency that funded the research or as a book or journal article for academic social

researchers. In writing up the findings and on clusions, the researcher is doing more

than simply relaying what has been found to others: readers must be convinced that the

research conclusions are important and that the findings are robust. Thus, a significant

part of the research process entails convincing others of the significance and validity of

one's findings.

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CHAPTER III

CONCLUSION

Quantitative research is the way for representation and manipulation of observations for

the purpose of describing and explaining the phenomena that those observations reflect. With

the types of quantitative research, we can make a presentation with themselves functions.

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BIBLIOGRAPHY

wikipedia.org/wiki/Quantitative_research

www.culi.chula.ac.th/e-journal/bod/suphat%20sukamolson.pdf

Sukamolson, Suphat, Fundamentals of quantitative research, Chulalongkorn University: Language Institute

Hughes, Christina(2006) Qualitative And Quantitative Approache, UK: University of Warwick

Postlethwaite, Neville(2005) Educational research: some basic concepts and terminology,University of Hamburg:Institute of Comparative Education

Cresswell(2008),Chapter Three: The Use of Theory

Bryman, The Nature of Quantitative Research: Chapter 3

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