6. KINDS OF QUANTITATIVE
RESEARCH
1. EXPERIMENTAL RESEARCH DESIGN. This allows the researcher
to control the situation. In doing so, it allows the researcher to answer
the question, “What causes something to occur?” This kind of research
also allows the researcher to identify cause and effect relationships
between variables and to distinguish placebo effects from treatment
effects. Further, this research design supports the ability to limit
alternative explanations and to infer direct causal relationships in the
study; the approach provides the highest degree level of evidence for
single studies.
A. PRE-EXPERIMENTAL DESIGN. A type of research applied to
experimental design with least internal validity. One type of pre-
experiment, the simple group, pre-test-post-test design, measures the
group two times, before and after the intervention.
7. KINDS OF QUANTITATIVE
RESEARCH
Instead of comparing the pretest with the posttest within one group,
the posttest of the treated groups is compared with that of an untreated
group. Measuring the effect as the difference between groups marks
this as between-subjects design. Assuming both groups experienced
the same time-related influences, the comparison group feature should
protect this design from the rival explanations that threaten the within-
subject design. Two classes of experimental design that can provide
better internal validity than pre-experimental designs are: quasi-
experimental and true experimental design (Dooly, 1999).
8. KINDS OF QUANTITATIVE
RESEARCH
B. QUASI – EXPERIMENTAL DESIGN. In this design, the researcher can
collect more data, either by scheduling more observations or finding more
existing measures. Quasi-experimental design involves selecting groups, upon
which a variable is tested, without any random pre-selection processes. For
example, to perform an educational experiment, a class might be arbitrarily
divided by alphabetical selection or by seating arrangement. The division is
often convenient and, especially in an educational situation, causes as little
disruption as possible. After this selection, the experiment proceeds in a very
similar way to any other experiment, with a variable being compared between
different groups, or over a period of time.
There are two types of quasi-experimental design, these are:
a. Non-Equivalent Control Group. This refers to the chance failure
of random assignment to equalize the conditions by converting a
true experiment into this kind of design, for purpose of analysis.
9. KINDS OF QUANTITATIVE
RESEARCH
a.Interrupted Time Series Design. It employs multiple
measures before and after the experimental intervention. It
differs from the single-group pre-experiment that has only
one pretest and one posttest. Users of this design assume
that the time threats such as history or maturation appear as
regular changes in the measures prior to the intervention.
C. TRUE-EXPERIMENTAL DESIGN. It controls for both time-
related and group-related threats. Two features mark true
experiments: 1. two or more differently treated groups; 2.
random assignment to these groups. These features require that
the researchers have control over the experimental treatment and the
power to place subjects in groups.
True experimental design employs both treated and control groups to
deal with time-related rival explanations.
10. KINDS OF QUANTITATIVE
RESEARCH
2. NON-EXPERIMENTAL DESIGN. In this kind of design, the
researcher observes the phenomena as they occur naturally and no
external variables are introduced. In this research design, the variables
are not deliberately manipulated nor is the setting controlled.
Researchers collect data without making changes or introducing
treatments. This may also called as DESCRIPTIVE RESEARCH
DESIGN because it is only one under non-experimental design.
DESCRIPTIVE RESEARCH DESIGN’s main purpose is to observe,
describe and document aspects of a situation as it naturally occurs and
sometimes to serve as a starting point for hypothesis generation or theory
development.
The types of descriptive design are as follows:
11. KINDS OF QUANTITATIVE
RESEARCH
1. SURVEY – a research design used when the researcher intends to
provide a quantitative or numeric description of trends, attitudes or
opinions of a population by studying a sample of that population.
2. CORRELATIONAL – Correlational has three types
Bivariate Correlational Studies – It obtains score from two
variables for each subject, and then uses them to calculate a
correlation coefficient. The term bivariate implies that the two
variables are correlated (variables are selected because they are
believed to be related).
Example: Which high school applicants should be admitted to
college?
Example: Children of wealthier (variable one), better educated
(variable 2) parents earn higher salaries as adults.
12. KINDS OF QUANTITATIVE
RESEARCH
3. EX-POST FACTO or CAUSAL-COMPARATIVE. This kind of research
derives conclusion from observations and manifestations that already occurred
in the past and now compared to some dependent variables. It discusses why and
how a phenomenon occurs.
Example 1: A researcher is interested in how weight influences stress-coping
level of adults. Here the subjects would be separated into different groups
(underweight, normal, overweight) and their stress-coping levels measured. This
is an ex post facto design because a pre-existing characteristic (weight) was used
to form the groups.
Example 2: What is the Effect of Home Schooling on the Social Skills of
Adolescents?
4. COMPARATIVE. It involves comparing and contrasting two or more samples
of study subjects on one or more variables, often at a single point of time.
Specifically, this design is used to compare two distinct groups on the basis of
selected attributes such as knowledge level, perceptions, and attitudes, physical
or psychological symptoms.
13. KINDS OF QUANTITATIVE
RESEARCH
Prediction Studies – It uses correlation coefficient to show how one
variable (the predictor variable) predicts another (the criterion
variable).
Example: Which high school applicants should be admitted to
college?
Multiple Regression Prediction Studies – All variables in the
study can contribute to the over-all prediction in an equation that
adds together the predictive power of each identified variable.
Example: Suppose the High School GPA is not the sole predictor
of college GPA, what might be other good predictors?
14. KINDS OF QUANTITATIVE
RESEARCH
Example: A comparative Study on the Health Problems among Rural and
Urban People in Ilocos Region, Philippines.
5. NORMATIVE. It describes the norm level of characteristics for a
given behavior. For example: If you are conducting a research on the
study habits of the high school students you are to use the range of
score to describe the level of their study habits. The same true is
when you would want to describe their academic performance.
6. EVALUATIVE. It is a process used to determine what has happened
during a given activity or in an institution. The purpose of evaluation is
to see if a given program is working, an institution is successful
according to the goals set for it, or the original intent was successfully
attained. In other words, in evaluation judgments can be in the forms of
social utility, desirability, or effectiveness of a process.
15. KINDS OF QUANTITATIVE
RESEARCH
For example, we can cite here a situation. In evaluation study, it will not
just be considering the performance of the students who were taught under
modular instruction; instead, it is the rate of progress that happened among
the students who were exposed to modular instruction.
Example: A test of children in school is used to assess the effectiveness
of teaching or the deployment.
7. METHODOLOGICAL. In this approach, the implementation of a
variety of methodologies forms a critical part of achieving the goal of
developing a scale-matched approach, where data from different
disciplines can be integrated.
17. VARIABLES
INDEPENDENT VARIABLES
- Those that probably cause, influence, or affect outcomes.
Examples of independent variables are age, gender, what people eat,
how much time they spend using gadgets, how much television they
watch or how much time youngsters spend on computer games.
EXAMPLE: A study is on the relationship of study habits and
academic performance of ICST senior high school students. STUDY
HABITS is the independent variable because it influenced the outcome
or the performance of the students.
DEPENDENT VARIABLES
- those that depend on the independent variables; they are the outcomes or
results of the influence of the independent variable. That is why it is also
called outcome variable.
EXAMPLE: A study is on the relationship of study habits and
academic performance of UTNHS senior high school students.
ACADEMIC PERFORMANCE is the dependent variable because it is
depending on the study habits of the students; if the students change
their study habit the academic performance also change.
18. VARIABLES
EXAMPLE: A study is on the relationship of study habits and
academic performance of ICST senior high school students.
ACADEMIC PERFORMANCE is the dependent variable because it is
depending on the study habits of the students; if the students change
their study habit the academic performance also change.
INTERVENING OR MEDLING VARIABLES – Variables that “stand
between” the independent and dependent variables, and they show the
effects of the independent variable on the dependent variable.
EXAMPLE: Consider the given below. Even if farm production is
good, if the attitude towards payment is negative, loan repayment
would be low, whereas, if the attitude towards repayment is positive or
favorable, loan repayment would be high.
19. VARIABLES
CONTROL VARIABLES – A special types of independent variables that
are measured in the study because they potentially influence the dependent
variable. Researchers use statistical procedures (e.g. analysis of covariance)
to control these variables. They may be demographic or personal variables
that need to be “controlled” so that the true influence of the independent
variable on the dependent variable can be determined.
20. VARIABLES
CONFOUNDING VARIABLES – Variables that are not actually
measured or observed in a study. They exist but their influence cannot be
directly detected in a study. Researchers comment on the influence of
confounding variables after the study has been completed, because these
variables may have operated to explain the relationship between the
independent variables and dependent variable, but they were not or could
not be easily assessed.
EXAMPLE:
Patrick Regoniel (2012) advances these examples of variables:
Phenomenon A: Climate Change
Examples of variables related to climate change:
1. sea level
2. temperature
3. the amount of carbon emission
4. the amount of rainfall
21. VARIABLES
Phenomenon B: Crime and violence on streets
Examples of variables related to crime and violence in streets
1. number of robberies
2. number of attempted murder
3. number of prisoners
4. number of crime victims
5. number of law enforcers
6. number of convictions
7. number of car napping incidents
Phenomenon C: Poor performance of students in college entrance exams
Examples of variables related to poor academic performance:
1. Entrance exam score
2. Number of hours devoted to studying
3. Student-teacher ratio
4. Number of students in the class
5. Educational attainment
6. Teaching style
7. The distance of school from home
8. Number of hours devoted by parents in providing tutorial support
