2. Hypothesis
This is a tentative explanation or prediction that
can be tested through research and
experimentation.
Purpose:
To provide a direction for research
To test theories and concepts
◦ Example: "If I increase the amount of water plants
receive, then they will grow taller."
3. Types of Hypotheses
Null Hypothesis (H ):
₀
This states there is no effect or relationship
between variables.
Example: "There is no relationship between
exercise and weight loss.“
Alternative Hypothesis (H ):
₁
This Proposes that there is a significant effect or
relationship between variables.
Example: "Exercise leads to weight loss.
4. Directional Hypothesis:
Specifies the direction of the expected
relationship between variables.
Example: "Increased study time improves test
scores.“
Non-Directional Hypothesis:
This does not specify the direction but only that
there is a relationship.
Example: "There is a relationship between sleep
and cognitive performance.
5. Characteristics of a Good Hypothesis
Testable:
A hypothesis should be formulated in a way that
it can be tested and measured.
Falsifiable:
A hypothesis must be stated in a way that it can
be proven false.
Clear and Specific:
The hypothesis should be well-defined and
specific.
Relevant:
It should be based on previous knowledge or
theory and be relevant to the research question.
6. Consistent with Existing Knowledge:
A good hypothesis aligns with what is already
known in the field but may provide new insights.
Replicable:
The experiment or research method should be
reproducible by others to confirm the results.
How to Formulate a Hypothesis
Step 1: Start with a research question.
Step 2: Review existing literature to find gaps or
patterns.
Step 3: Create a statement that predicts the
relationship between variables.
Step 4: Ensure it is testable and falsifiable.
7. Examples of Hypotheses
Example 1:Research Question: Does the
amount of study time affect exam performance?
Hypothesis: "Increased study time leads to
better exam performance.
"Example 2:Research Question: Does caffeine
consumption improve reaction time?
Hypothesis: "Caffeine consumption improves
reaction time in adults.“
Importance of Hypothesis in Research
Guides Research Design:
Directs how the research is conducted and
what variables are important.
8. Helps with Data Interpretation:
Provides a framework for understanding
research results.
Contributes to Scientific Knowledge:
Confirms or refutes existing theories or
provides new insights.
Common Mistakes in Hypothesis
Vague or General Statements:
Avoid hypotheses that are too broad or unclear.
Non-Testable Hypotheses:
Make sure the hypothesis is measurable.
Overly Complicated Hypotheses:
Keep it simple and direct.
9. Variables in research
Variables are factors or characteristics that can
vary or change within a study.
They are used to test hypotheses and
understand relationships between different
elements.
Importance of understanding variables:
Proper identification and management of
variables help ensure the validity of study
results.
10. Types of variables
Independent Variable (IV)
This is the factor that is manipulated or
changed by the researcher.
Purpose: It is presumed to have an effect on
the dependent variable.
Examples: In a drug efficacy study, the
independent variable might be the dosage of the
drug.
In a study on exercise, the type of exercise is
the independent variable.
Key Point:The researcher controls the IV to
observe changes in the DV.
11. Dependent Variables (DV)
This is what is measured or observed in
response to changes in the independent
variable.
Purpose: It reflects the effect of the
independent variable.
Examples: In a drug study, the dependent
variable could be the change in patient health or
symptoms.
In a study on exercise, the dependent variable
might be physical fitness or body weight.
Key Point:The DV depends on the variations in
the IV.
12. Control Variables
These are factors that are kept constant
throughout the experiment to prevent them
from influencing the dependent variable.
Purpose: To isolate the relationship between
the independent and dependent variables.
Examples:In a study on sleep deprivation,
control variables could include age, gender, or
baseline health.
Key Point: Control variables help ensure the
experiment is fair and accurate.
13. Confounding Variables
This is an outside influence that affects both the
independent and dependent variables,
potentially leading to a false conclusion.
Purpose: These variables can distort the
perceived relationship between IV and DV.
Examples:In a study on the effectiveness of a
drug, a confounding variable could be a
participant’s pre-existing health condition.
Key Point: Researchers need to identify and
control for confounding variables to improve
study validity.
14. Moderator Variables
This variable affects the strength or direction of
the relationship between the independent and
dependent variables.
Purpose: It can either enhance or reduce the
effect of the IV on the DV.
Examples:In a study on stress and job
performance, the type of job might moderate
the relationship.
Key Point: Moderator variables help explain
when or for whom certain effects will occur.
15. Mediator Variables
This variable explains the process or
mechanism through which the independent
variable influences the dependent variable.
Purpose: It shows how or why an effect occurs.
Examples:In a study on sleep and cognitive
function, a mediator variable might be brain
activity.
Key Point: Mediators help to understand the
pathway from IV to DV.
16. ExtraneousVariables
These are any variables that are not of primary
interest but could still influence the dependent
variable.
Purpose: They need to be controlled for to
prevent them from becoming confounding
variables.
Examples: In a lab study on reaction time,
extraneous variables could include ambient
temperature or noise level.
Key Point: Extraneous variables are unwanted
but are not necessarily confounding unless they
correlate with IV and DV.
17. The research process
Identify and Define the Research Problem:
Ensure the problem is clear, focused, and
researchable.
Review of Literature:
Conduct a literature review to understand what
has already been researched on the topic.
This helps you to identify gaps, theories, and
methodologies that can inform your own study.
Formulate Hypothesis or Research
Questions:
18. Based on your research problem and literature
review, you develop hypotheses (if you're
conducting quantitative research) or research
questions (if your approach is qualitative).
Design the Research Methodology:
This stage involves deciding on the methods and
techniques you'll use to collect data.
Will it be qualitative, quantitative, or mixed
methods?
You'll also determine your research tools,
sample size, and data collection methods
(surveys, interviews, experiments, etc.).
19. Data Collection:
You gather the data necessary to answer your
research questions or test your hypothesis.
This could involve experiments, surveys,
fieldwork, interviews, or secondary data
collection.
Data Analysis:
After collecting your data, you analyze it to
identify patterns, relationships, or trends.
Depending on your approach, this could involve
statistical analysis, coding qualitative data, or
applying other techniques to interpret the
information.
20. Interpretation of Results:
In this stage, you interpret the meaning of your
findings.
Do they support or contradict your hypothesis
or answer your research question?
You also discuss the implications of your
findings.
Draw Conclusions and Make
Recommendations:
Based on your analysis and interpretation, you
draw conclusions about the research problem.
You may also make recommendations for future
research or practical applications.
21. Writing and Presenting the Research:
• This document typically includes an
introduction, literature review, methodology,
results, discussion and conclusion.
• You might also present your findings through
presentations or publications.
Review and Revision:
• Before finalizing your research, you should
review your work to ensure it's accurate, clear,
and well-supported.
• Peer review or feedback from advisors can be
helpful at this stage.
• These stages are often iterative,
