Quantitative Research
course
mastery
PRACRE2-3
rookie
Table of Contents
Files
Types of Quantitative Research
Descriptive
Correlation
Ex part facto
Quasi-Experimental
Experimental
Difference Between Quasi and Experimental
Files
Pros
Cons
Evidence-Based It can be replicated and repeated
Provides findings that are generalizable through a
huge population Establish causally more
conclusively Make predictions based o numerical
data Has help through statistical software Low
degree of subjectivity
Full of tabulation May not be accurate
Types of Quantitative Research
Descriptive
Phenomenon, behavior, or trait
It describes a status
It searches for existing questions
But is unable to make a causal relationship ( it only describes)
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Descriptive quantitative research is used to describe a phenomenon, behavior, or
trait and searches for existing questions, but is unable to make a causal
relationship. This type of research only describes a status and doesn't attempt to
establish cause-and-effect relationships. Descriptive research can be useful for
identifying patterns or trends in data, but it is limited in its ability to draw
conclusions about why those patterns or trends exist.
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Correlation
It extends relationships between 2 or more variables
Trends and patterns only, not causes
Variables aren’t manipulated
Help predict the score and explains relationships
ex. cigarette and vape
For example, a correlational study might investigate the relationship
between cigarette smoking and vaping. Researchers would collect data on
smoking and vaping habits and look for patterns in the data. If they
find a strong correlation between smoking and vaping, they might
conclude that people who smoke are more likely to vape, but they would
not be able to determine whether smoking causes vaping or vice versa.
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Correlational quantitative research extends relationships between two or more
variables. This type of research identifies trends and patterns and helps predict
scores and explain relationships, but it does not establish causation. Unlike in
experimental research, variables in correlational research are not manipulated, and
researchers have no control over the variables. Instead, they observe the
relationship between variables as they naturally occur.
Ex part facto
It infers a cause from an already existing effect
Doesn’t use experimental manipulation
And has no control over the variables
For example, a researcher might investigate whether people who have been
exposed to high levels of air pollution are more likely to develop
respiratory problems. The researcher would identify a group of people
who have been exposed to high levels of air pollution and compare them
to a group of people who have not been exposed. If the group exposed to
air pollution has a higher incidence of respiratory problems, the
researcher might infer that air pollution causes respiratory problems.
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Ex post facto research infers a cause from an existing effect. This type of research
is often used when it is unethical or impractical to manipulate variables in an
experiment. Researchers identify a group of people who have already been exposed to a
particular variable (the "effect") and compare them to a group of people who have not
been exposed. They then look for differences between the two groups and infer a cause
based on those differences.
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Quasi-Experimental
Establish a causal relationship but the effects have occurred during the study itself
Some experimental manipulation / limited manipulation
ex. same subjects, different methods
Toothache:
Group A
Group B
Tawas
Supplements
Experimental
Cause-Effect Relationship
Variable manipulation extensively
Specific Variables as well as individuals and not only groups
Difference Between Quasi and Experimental
ex.
Quasi - Effects of using your phone while exercising (general)
Experimental - Effects of using your phone while walking (specific)
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