A.
Definition of Quantitative Research
As
we know “ Quantitative “ always conected with numbers and facts. Quantitative
research is about asking people for their opinions in a structured way so that
you can produce hard facts and statistics to guide you.Simply put, it’s about
numbers, objective hard data.
B. Characteristics
of Quantitative Research
1.
The data is usually gathered using structured research
instruments.
Its mean
that the data should stuctured , because if the data structured we will easy to
make a research.
2.
The results are based on larger sample sizes that are
representative of the population.
Its means the result of research representative of population.
Its means the result of research representative of population.
3. The research study can usually be
replicated or repeated, given its high reliability.
Its means we can repeated the
research, bebause if we find out get
problem, we can repeat of research study.
4.
Researcher has a clearly defined research question to
which objective answers are sought.
Its means as
a researcher, we should make a questions that the answeris objective.
5. All aspects
of the study are carefully designed before data is collected.
It’s mean we should prepare and
carefully design everything about aour rsearch like questions, object before
data collected.
6. Data are in
the form of numbers and statistics, often arranged in tables, charts, figures,
or other non-textual forms.
It’s mean quantitative research
always connected with numbers , table or charts.
7. Project can
be used to generalize concepts more widely, predict future results, or
investigate causal relationships.
It’s mean from our reseacrh , we can
predict or make hypothesis in the future from data.
8. Researcher
uses tools, such as questionnaires or computer software, to collect numerical
data.
It’s mean we can uses tools to easy
our research such computer software or questionnaires.
9. The
overarching aim of a quantitative research study is to classify features, count
them, and construct statistical models in an attempt to explain what is
observed.
It’s mean the firts purpose our
research is classify features, count them and explain what is observed .
C.
Quantitative Reasearch Methods Reporting the Result
1.
Explain the data collected and their
statistical treatment as well as all relevant results in
relation to the research problem you are investigating. Interpretation of
results is not appropriate in this section.
2.
Report unanticipated eventsThat
occurred during your data collection. Explain how the actual analysis differs
from the planned analysis. Explain your handling of missing data and why any
missing data does not undermine the validity of your analysis.
3.
Explain the techniques you used to
"clean" your data set.
4.
Choose a minimally
sufficient statistical procedure; provide a rationale for its use
and a reference for it. Specify any computer programs used.
5.
Describe the assumptions for each
procedure and the steps you took to ensure that they were not violated.
6.
When using inferential
statistics, provide the descriptive statistics, confidence intervals, and sample
sizes for each variable as well as the value of the test statistic, its
direction, the degrees of freedom, and the significance level [report the
actual p value].
7.
Avoid inferring causality,
particularly in nonrandomized designs or without further experimentation.
8.
Use tables to provide exact
values; use
figures to convey global effects. Keep figures small in size; include graphic representations
of confidence intervals whenever possible.
9.
Always tell the reader what
to look for in tables and figures.
D. Types of
Quantitative Research Design
1. Descriptive 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 an hypothesis, but
is 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.
2. Correlational research
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 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.
3.
Causal-comparative/quasi-experimental research
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 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.
4.
Experimental research,
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
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
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