1. 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
2. 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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3. 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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4. 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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5. 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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6. 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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7. 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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8. 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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9. 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 Correlational Causal- Experimental
research research comparative/quasi- research
experimental
research
Seeks to describe Attempts to Attempts to establish Often called true
the current status of determine the cause-effect experimentation,
an identified extent of a relationships among uses the scientific
variable. These relationship the variables. These method to establish
research projects are between two or types of design are the cause-effect
designed to provide more variables very similar to true relationship among a
systematic using statistical experiments, but group of variables
information about a data. In this type with some key that make up a
phenomenon. The of design, differences. An study. The true
researcher does not relationships independent variable experiment is often
usually begin with a between and is identified but not thought of as a
hypothesis, but is among a number of manipulated by the laboratory study, but
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10. likely to develop facts are sought experimenter, and this is not always the
one after collecting and interpreted. effects of the case; a laboratory
data. The analysis This type of independent variable setting has nothing
and synthesis of the research will on the dependent to do with it. A true
data provide the test recognize trends variable are experiment is any
of the hypothesis. and patterns in measured. The study where an effort
Systematic data, but it does not researcher does not is made to identify
collection of go so far in its randomly assign and impose control
information requires analysis to prove groups and must use over all other
careful selection of causes for these ones that are variables except
the units studied and observed patterns. naturally formed or one. An
careful measurement Cause and effect is pre-existing groups. independent variable
of each variable. not the basis of this Identified control is manipulated to
type of groups exposed to determine the effects
Examples of
observational the treatment on the dependent
Descriptive
research. The data, variable are studied variables. Subjects
Research:
relationships, and and compared to are randomly
distributions of groups who are not. assigned to
A description of
variables are experimental
how second-
When analyses and
studied only. treatments rather
grade students
conclusions are
Variables are not than identified in
spend their time
made, determining
manipulated; they naturally occurring
during summer
causes must be done
are only identified groups
vacation
carefully, as other
and are studied as
A description of
variables, both Examples of
they occur in a
the tobacco use
known and Experimental
natural setting.
habits of
unknown, could still Research:
teenagers
Sometimes affect the
A description of The effect of a
correlational outcome. A causal-
how parents new treatment
research is comparative
feel about the plan on breast
considered a type designed study,
twelve-month cancer
of descriptive described in a
school year The effect of
research, and not as
A description of New York Times positive
its own type of
the attitudes of article, "The Case reinforcement
research, as no
scientists for $320.00 on attitude
variables are
regarding global Kindergarten toward school
manipulated in the
warming Teachers," The effect of
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11. A description of study. illustrates how teaching with a
the kinds of causation must be cooperative
Examples of
physical thoroughly assessed group strategy
Correlational
activities that before firm or a traditional
Research:
typically occur relationships lecture approach
in nursing amongst variables on students‟
The
homes, and how can be made. achievement
relationship
frequently each The effect of a
between
Examples of
occurs systematic
intelligence
Correlational
A description of preparation and
and self-
Research:
the extent to support system
esteem
which on children who
The The effect of
elementary were scheduled
relationship preschool
teachers use for surgery on
between diet attendance on
math the amount of
and anxiety social maturity
manipulative. psychological
The at the end of the
upset and
relationship first grade
cooperation
between an The effect of
A comparison
aptitude test taking
of the effect of
and success in multivitamins
personalized
an algebra on a students‟
instruction vs.
course school
traditional
The absenteeism
instruction on
relationship The effect of
computational
between ACT gender on
skill
scores and the algebra
freshman achievement
grades The effect of
The part-time
relationships employment on
between the the achievement
types of of high school
activities used students
in math The effect of
classrooms magnet school
and student participation on
achievement student attitude
8
12. The The effect of
covariance of age on lung
smoking and capacity
lung disease
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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13. 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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14. 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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