Practical Research 2 Week 1 Overview

Practical Research 2
Week 1
CS_RS12-Ia-c-1

Good day everyone ☺ ,
Let’s start the class!

Learning Objectives:
The learners shall be able to:
1. Define quantitative research
2. Describe the characteristics of quantitative research
3. Know the strengths and weaknesses of quantitative
research
4. Be familiar with the kinds of quantitative research
MELCS Code: CS_RS12-Ia-c-1

Part 1:
Quantitative Research
Quantitative Research is defined as a systematic
investigation of phenomena by gathering quantifiable
data and performing statistical, mathematical, or
computational techniques (Bhat, Adi, 2000).
It highlights numerical analysis of data hoping the
number yield unbiased results.
________________________________________________
Systematic - a definite set of procedures and steps which you will follow. A process
which are always done in order to get the most accurate results. Organized in that
there is a structure or method in going about doing research.
Phenomena – a fact, occurrence, or circumstance observed

Activity #1
Describe Quantitative research in 1-2 sentences
using your understanding about its definition.
Use a separate sheet of paper for your answers

Part 2:
6 Characteristics of Quantitative Research
1. Objective – it seeks accurate measurement and
analysis of the target concept. It is not based on
mere intuitions and guesses.
2. Clearly Defined Research Questions – research
questions are well-defined, for which objective
answers are sought. All aspects of the study are
carefully designed before data are gathered.

Part 2:
3. Structured Instruments – data are gathered using
structured research tools such as questionnaires
(with close-ended questions) to collect measurable
characteristics of the population (age, socio-
economic status, number of children, etc.)
4. Numerical in Nature – It relies primarily on data and
numerical analysis, organized, and presented using
tables, charts, graphs, and figures that consolidate
large numbers of data to show trends, relationships,
or differences among variables.

Part 2:
5. Large Sample Sizes – this requires a large sample
size, depending on how the characteristics of the
population vary.
6. Replication – It can be repeated to verify or
confirm the correctness of the result in another
setting. This strengthens the validity of the
findings.

Part 3:
Strengths and Weaknesses of
Quantitative research
STRENGTHS OF QUANTITATIVE RESEARCH
1. It is objective. The most reliable and valid way of
concluding results, giving way to a new hypothesis or to
disproving it. Because of bigger number of the sample of
a population, the results or generalizations are more
reliable and valid. Since it provides numerical data, it
can’t be easily misinterpreted.
2. The use of statistical techniques facilitates sophisticated
analyses and allows you to comprehend a huge amount
of vital characteristics of data.

Part 3:
3. It is real and unbiased. If the research is properly
designed it filters out external factors, and so can be
seen as real and unbiased.
4. The numerical data can be analyzed in a quick and
easy way. By employing statistically valid random
models, findings can be generalized to the
population about which information is necessary.

Part 3:
5. Quantitative studies are replicable. Standardized
approaches allow the study to be replicated in
different areas or over time with formulation of
comparable findings.
6. Quantitative experiments are useful for testing the
results gained by a series of qualitative
experiments, leading to a final answer, and
narrowing down of possible directions to follow

Part 3:
WEAKNESSES OF QUANTITATIVE RESEARCH
1. Quantitative research requires a large number of
respondents. It is assumed that the larger the
sample is, the more statistically accurate the
findings are.
2. It is costly. Since, there are more respondents
compared to qualitative research, the expenses will
be greater in reaching out to these people and in
reproducing questionnaires.

Part 3:
WEAKNESSES OF QUANTITATIVE RESEARCH
3. The information is contextual factors to help interpret
the results or to explain variations are usually ignored. It
does not consider the distinct capacity of the
respondents to share and elaborate further information
unlike the qualitative research.
4. Much information are difficult to gather using structured
research instruments, specifically on sensitive issues like
pre-marital sex, domestic violence, among others.

Activity #3
Write S if Strength and W if Weaknesses of Quantitative Research
1. Costly
2. Objective
3. Replicable
4. Limit to contextual information
5. Uses Statistical Techniques
6. Real and Unbiased
7. Difficulty in gathering information
8. Quick and Easy
9. Need a large respondent
10. Are useful for testing the results gained by a series of
experiments

Part 4:
Quantitative Research Designs

Part 4:
Non-Experimental Designs
Are used when the researcher wishes to:
❑ Explore events, people, situations as they naturally occur
❑ Test relationships and differences among variables
The independent variable is not manipulated
Subjects are not randomized
There is no control group

Part 4:
Types of Descriptive Research Designs
Descriptive Research Design
1. Survey
A research design used when the researcher intends to provide a quantitative or
numeric description of trends, attitudes, opinions of a population by studying a sample
of that population (Creswell, 2003).
❑ a design in which data are collected with questionnaires or through personal
interviews with members of an identified population
❑ It may be descriptive, exploratory, or comparative surveys
❑ It uses the data to justify and assess current conditions and practices
❑ Example:
Hours Spent by Grade 12 Senior High School Students on Social Media

Part 4:
2. Correlational
❑ Explores, examines and observes the association or relationships between two or more
variables; variables is not controlled
❑ Intends to estimate the extent to which the different variables are related to one another
❑ Establishes or explores relationships, associations, or interdependence between two or more
variables without investigating causal reasons underlying them
❑ It has three types: Bivariate correlational studies, prediction studies, and multiple regression
prediction studies
❑ Example:
A Correlational Study of the Relationship Between Sense of Humor and Positive Psychological
Capacities
Liver Regeneration in Acute Severe Liver Impairment: A Clinicopathological Correlation Study
A Correlation Study of Personal Entrepreneurial Competency and the Academic Performance
in Operations Management of Business Administration Students
A Study of the Relationship between IQ and Clinical Depression

Part 4:
Types of Correlational Research
Bivariate Correlational Studies – obtain scores from two variables for each subject, then use 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: Children of wealthier (variable #1), better educated (variable #2) parents earn higher
salaries as adults
Prediction studies use correlation co-efficient 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 – suppose the high school GPA is not the sole predictor of
college GPA, what might be other good predictors? All of these variables can contribute to the
over-all production in an equation that adds together the predictive power of each identified
variable.

Part 4:
3. 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.
❑ Example:
A Comparative Study on the Health Problems among Rural and Urban Older People
from District Mehsana, Gujarat.
A Comparative Study on the Pricing Strategy of Jollibee Foods Corporation and
Golden Arches Development Corporation (Mc Donalds)

Part 4:
4. Evaluation
❑ It is a research conducted to elicit useful feedback from a variety of respondents
from various fields to aid in decision-making or policy formulation.
❑ Formative and Summative evaluation types are the most commonly used in
research
❑ Formative evaluation is used to determine the quality of implementation of a
project, the efficiency and effectiveness of a program, assessment of
organizational processes like procedures, policies, guidelines, human resource
development, etc.
❑ Summative evaluation is undertaken to determine whether the program or
intervention achieved its goals, objectives, or outcomes; how the program's impact
compares to different programs; and to better understand the process of change,
what works, what doesn't, and why.
❑ Example:
Effectiveness of the implementation of the K-12 Program in Lagro High School S.Y.
2016-2017

Part 4:
5. Methodological
❑ In this approach, the implementation of a variety of methodologies forms
critical part of achieving the goal of developing a scaled-match approach,
where data from different disciplines can be integrated

Part 4:
Experimental
❑ Utilizes the scientific method to test cause and effect
relationships under conditions controlled by the
researcher/ treatment is given to a controlled group

Part 4:
Pre-Experimental Research Designs
❑ A. PRE-EXPERIMENTAL DESIGN. It is carried out before the main
experiment. In a pre-experiment either a single group or multiple groups
are observed subsequent to some agent or treatment presumed to cause
change. Among the experimental designs, it has the least internal validity
❑ Types of Pre-Experimental Design
1. One-shot case study design
2. One-group pretest-posttest design
3. Static-group comparison
❑ One-shot case study design
A single group is studied at a single point in time after some treatment that is
presumed to have caused change. The carefully studied single instance is
compared to general expectations of what the case would have looked like
had the treatment not occurred and to other events casually observed. No
control or comparison group is employed.

Part 4:
Types of Pre-Experimental Research Design
Experiment (Intervention/ Treatment/ Program/ Services)
Observation (Post-Test)

Part 4:
❑ One-group pretest-posttest design
A single case is observed at two time points, one before
the treatment and one after the treatment. Changes in
the outcome of interest are presumed to be the result of
the intervention or treatment. No control or comparison
group is employed.
❑ Example: One group is given intervention/treatment
for depression and afterwards given post-test

Part 4:
Observation (Post-Test)
Observation (Pre-Test)

Part 4:
❑ Static-group comparison
A group that has experienced some treatment is
compared with one that has not. Observed differences
between the two groups are assumed to be a result of the
treatment.
❑ Example: There are two groups. One group is given
intervention/treatment for depression and the
other group is not given intervention and
treatment. Afterwards both groups are given
post-test

Part 4:
Observation 1st Group (Post-Test)
Observation 2nd Group (Post-Test)

Part 4:
Quasi-Experimental Research Design
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 (Non-Equivalent Control Group Design, Time
Series Design).
Used for test of causality with sub-optimal variable control; independent variable
is not manipulated. Quasi-Experimental design differs from True Experimental
design by the absence of random assignments of subjects to different conditions.
What Quasi-experiments have in common with true experiments is that some
subjects receive an intervention and provide data likely to reflect its impact.
❑ Example: A Study on the Effect of an After School Physical Activity Program
on Childhood Obesity Rates

Part 4:
Types of Quasi-Experimental Research Design
Two Types of Quasi-Experimental Design
1. Non-equivalent Control Group Design – refers to the chance failure of
random assignment to equalize the conditions by converting a true
experiment into this kind of design, for purposes of analysis.
2. Interrupted Time Series Design – employs measures before and after the
experimental intervention. It differs from the single-group pre-
experiment that has only one pre-test and one post-test. User of this
design assume that the time threats such as history or maturation appear
as regular changes in the measures prior to the intervention.

Part 4:
Types of Quasi-Experimental Research Designs
Ex Post Facto” Latin for “after the fact” or Causal-comparative
❑ A category of research design in which the investigation starts after the fact has occurred without
interference from the researcher.
❑ A quasi-experimental study examining how an independent variable, present prior to the study,
affects a dependent variable. So like we just said, there is something about the participant that
we're going to study that we don't have to alter in the participant. We will make this a little clearer
a little later with some examples and descriptions.
❑ Ex post facto designs are different from true experiments because ex post facto designs do not use
random assignment. In ex post facto, you are looking at a prior variable present in the participant.
n an ex post facto design, you are not randomly assigning people to an experimental group or
control group. You are purposefully putting people in a particular group based on some prior thing
they have. I say 'thing' because it could be 'must have glasses,' or 'must be overweight.' There is no
limit to the ways you could divide up the population.
❑ Why is ex post facto design considered a quasi-experimental? Also known as "after the fact"
research, an ex post facto design is considered quasi-experimental because the subjects are not
randomly assigned - they are grouped based on a particular characteristic or trait.
❑ Example:
What is the effect of home schooling on the social skills of adolescents?

Part 4:
True Experimental Research Design
❑ C. TRUE-EXPERIMENTAL DESIGN. The true experimental research design relies on statistical
analysis to approve or disprove a hypothesis. It is the most accurate type of experimental
design or internal validity and may be carried out with or without a pretest on at least 2
randomly assigned dependent subjects.
❑ True experimental designs require random assignment. Control groups do not receive an
intervention, and experimental groups receive an intervention. The basic components of a
true experiment include a pretest, posttest, control group, and experimental group. Testing
effects may cause researchers to use variations on the classic experimental design.
❑ Example:
The Effect of Facebook Marketing on Brand Engagement: The Role of Demographics and
Psychographics An Empirical Study on Smartphone Users in Egypt
Impact of Remote Learning on Student Performance in the Face of COVID 19 among Senior
High School Students in Miami
The effectiveness of family planning programs evaluated with true experimental designs.

Part 4:
Types of True Experimental Research Design
❑ The pretest-posttest Control Group Design: For this control group design,
subjects are randomly assigned to the 2 groups, both are presented, but
only the experimental group is treated. After close observation, both
groups are post-tested to measure the degree of change in each group.
❑ The posttest-only Control Group Design: In this design, subjects are
randomly selected and assigned to the 2 groups (control and
experimental), and only the experimental group is treated. After close
observation, both groups are post-tested, and a conclusion is drawn from
the difference between these groups.
❑ Solomon four-group Design: This is the combination of the pretest-only and
the pretest-posttest control groups. In this case, the randomly selected
subjects are placed into 4 groups. The first two of these groups are tested
using the posttest-only method, while the other two are tested using the
pretest-posttest method.

Part 4:
True Experimental vs. Quasi Experimental

References:
Baraceros, E. (2016). Practical Research 2. Rex Book Store, Inc.
Bhat, A. (2020). Quantitative Research. Retrieved from
https://www.questionpro.com/blog/quantitative-research/
Prieto, N.,Naval, V & Carey, T. (2017). Practical Research 2 for Senior High
School. Lorimar Publishing, Inc.

Part 1:
Describe Quantitative research.
(Answer Key)
Quantitative research is the process of collecting and
analyzing numerical data. It can be used to find patterns and
averages, make predictions, test causal relationships, and
generalize results to wider populations.
Quantitative research is widely used in the natural and social
sciences: biology, chemistry, psychology, economics, sociology,
marketing, etc.

Part 2:
Characteristics of Quantitative Research
(Link Me Answer Key)
1. Costly - B
2. Large Respondents - D
3. Limit to contextual information - A
4. Difficulty in gathering information - C

Part 3:
Quantitative research (Answer Key)
STRENGTHS WEAKNESSES
1. Objective 1. Need a large respondent
2. Uses Statistical Techniques 2. Costly
3. Real and Unbiased 3. Limit to contextual info
4. Quick and Easy 4. Difficulty in gathering info
5. Replicable
6. Useful for testing the results

Part 4:
Kinds of Quantitative Research (Answer Key)
A. Survey K. Experiment
B. Survey L. Survey
C. Survey M. Survey
D. Experiment N. Experiment
E. Survey O. Survey
F. Survey P
. Survey
G. Survey
H. Survey
I. Survey
J. Survey

Practical Research 2 Week 1 Overview

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