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Transcript of Quantitative
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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