RESEARCH
METHODS
Hypotheses • Variables • Sampling • Experiments • Ethics • Exam Tips
Core Psychology | For Examination Use
Core Psychology| IGCSE Research Methods Page 1
, Table of Contents
1. Hypotheses — Null and Alternative
2. Variables: IV, DV, Extraneous and Confounding
3. Sampling Methods
4. Experimental Method and Designs
5. Types of Experiments
6. Other Research Methods
7. Quantitative vs Qualitative Data
8. Correlation
9. Controls in Research
10. Reliability and Validity
11. Ethics in Psychology
12. Extra Concepts
13. Practice Questions
Core Psychology| IGCSE Research Methods Page 2
, Research is a purposeful, systematic inquiry designed to discover
new facts, verify existing knowledge, or develop new theories.
1. Hypotheses — Null and Alternative
A hypothesis is a clear, testable statement about the relationship between variables. Researchers write two
hypotheses before conducting any study.
1.1 Alternative Hypothesis (H1)
Alternative Hypothesis (H1): Predicts that there IS a significant difference or relationship between variables.
Types of Alternative Hypothesis
• Directional (one-tailed) — predicts the direction of the effect.
– Example: 'Children who sleep more than 9 hours will score significantly HIGHER on memory tests than those
sleeping fewer than 7 hours.'
• Non-directional (two-tailed) — predicts a difference but NOT its direction.
– Example: 'There will be a significant difference in memory test scores between children who sleep more than 9
hours and those sleeping fewer than 7 hours.'
1.2 Null Hypothesis (H0)
Null Hypothesis (H0): Predicts there is NO significant difference or relationship. Any result is due to chance.
This is what statistical tests attempt to disprove.
• Example: 'There will be no significant difference in memory test scores between children who sleep more than
9 hours and those sleeping fewer than 7 hours. Any difference will be due to chance.'
✎ EXAM TIP: Always write hypotheses BEFORE the study. The null hypothesis must mention 'chance'. Include the
IV and DV clearly — never just write 'there will be a difference'.
Feature Alternative Hypothesis (H1) Null Hypothesis (H0)
What it predicts A significant difference or relationship EXISTS NO difference or relationship — result is due
to chance
Mentions chance? No Yes — must say 'due to chance'
Accepted when… Results ARE statistically significant Results are NOT statistically significant
Directional? Can be one-tailed or two-tailed Always non-directional
■ Summary: H1 = prediction of a real effect; H0 = prediction of no effect (chance only). Statistical tests decide which
to accept.
Core Psychology| IGCSE Research Methods Page 3
, 2. Variables: IV, DV, Extraneous and Confounding
2.1 Independent Variable (IV)
Independent Variable (IV): The variable deliberately changed or manipulated by the researcher to observe its
effect.
• Example: Amount of sleep (7 hours vs 9 hours per night) •
The IV is in full control of the researcher.
2.2 Dependent Variable (DV)
Dependent Variable (DV): The variable that is measured by the researcher. It 'depends' on the IV.
• Example: Score on a standardised memory test (0–20 points)
• The DV must be operationalised — defined in a precise, measurable way.
2.3 Extraneous Variables (EVs)
Extraneous Variable: Any variable other than the IV that could potentially affect the DV. Not of interest but
must be controlled.
• Examples: room temperature, noise level, time of day, participant anxiety, lighting
• When controlled properly, EVs do NOT distort results.
2.4 Confounding Variables
Confounding Variable: An extraneous variable that was NOT controlled and HAS actually affected the DV,
making results unreliable and hard to interpret.
• Example: If some participants consumed caffeine before a memory test, caffeine becomes a confounding
variable.
• Confounding variables threaten internal validity and can lead to false conclusions.
Variable Definition Example Controlled?
IV Manipulated by researcher Hours of sleep per night Yes — by researcher
DV Outcome that is measured Memory test score (0–20) Measured carefully
Extraneous Could affect DV; not of primary Room temperature Should be controlled
interest
Confounding Has affected DV; was not Caffeine intake Was NOT controlled — ruins results
controlled
Internal validity is the degree of confidence that a causal relationship established in
a study is trustworthy and not influenced by outside factors.
Core Psychology| IGCSE Research Methods Page 4
METHODS
Hypotheses • Variables • Sampling • Experiments • Ethics • Exam Tips
Core Psychology | For Examination Use
Core Psychology| IGCSE Research Methods Page 1
, Table of Contents
1. Hypotheses — Null and Alternative
2. Variables: IV, DV, Extraneous and Confounding
3. Sampling Methods
4. Experimental Method and Designs
5. Types of Experiments
6. Other Research Methods
7. Quantitative vs Qualitative Data
8. Correlation
9. Controls in Research
10. Reliability and Validity
11. Ethics in Psychology
12. Extra Concepts
13. Practice Questions
Core Psychology| IGCSE Research Methods Page 2
, Research is a purposeful, systematic inquiry designed to discover
new facts, verify existing knowledge, or develop new theories.
1. Hypotheses — Null and Alternative
A hypothesis is a clear, testable statement about the relationship between variables. Researchers write two
hypotheses before conducting any study.
1.1 Alternative Hypothesis (H1)
Alternative Hypothesis (H1): Predicts that there IS a significant difference or relationship between variables.
Types of Alternative Hypothesis
• Directional (one-tailed) — predicts the direction of the effect.
– Example: 'Children who sleep more than 9 hours will score significantly HIGHER on memory tests than those
sleeping fewer than 7 hours.'
• Non-directional (two-tailed) — predicts a difference but NOT its direction.
– Example: 'There will be a significant difference in memory test scores between children who sleep more than 9
hours and those sleeping fewer than 7 hours.'
1.2 Null Hypothesis (H0)
Null Hypothesis (H0): Predicts there is NO significant difference or relationship. Any result is due to chance.
This is what statistical tests attempt to disprove.
• Example: 'There will be no significant difference in memory test scores between children who sleep more than
9 hours and those sleeping fewer than 7 hours. Any difference will be due to chance.'
✎ EXAM TIP: Always write hypotheses BEFORE the study. The null hypothesis must mention 'chance'. Include the
IV and DV clearly — never just write 'there will be a difference'.
Feature Alternative Hypothesis (H1) Null Hypothesis (H0)
What it predicts A significant difference or relationship EXISTS NO difference or relationship — result is due
to chance
Mentions chance? No Yes — must say 'due to chance'
Accepted when… Results ARE statistically significant Results are NOT statistically significant
Directional? Can be one-tailed or two-tailed Always non-directional
■ Summary: H1 = prediction of a real effect; H0 = prediction of no effect (chance only). Statistical tests decide which
to accept.
Core Psychology| IGCSE Research Methods Page 3
, 2. Variables: IV, DV, Extraneous and Confounding
2.1 Independent Variable (IV)
Independent Variable (IV): The variable deliberately changed or manipulated by the researcher to observe its
effect.
• Example: Amount of sleep (7 hours vs 9 hours per night) •
The IV is in full control of the researcher.
2.2 Dependent Variable (DV)
Dependent Variable (DV): The variable that is measured by the researcher. It 'depends' on the IV.
• Example: Score on a standardised memory test (0–20 points)
• The DV must be operationalised — defined in a precise, measurable way.
2.3 Extraneous Variables (EVs)
Extraneous Variable: Any variable other than the IV that could potentially affect the DV. Not of interest but
must be controlled.
• Examples: room temperature, noise level, time of day, participant anxiety, lighting
• When controlled properly, EVs do NOT distort results.
2.4 Confounding Variables
Confounding Variable: An extraneous variable that was NOT controlled and HAS actually affected the DV,
making results unreliable and hard to interpret.
• Example: If some participants consumed caffeine before a memory test, caffeine becomes a confounding
variable.
• Confounding variables threaten internal validity and can lead to false conclusions.
Variable Definition Example Controlled?
IV Manipulated by researcher Hours of sleep per night Yes — by researcher
DV Outcome that is measured Memory test score (0–20) Measured carefully
Extraneous Could affect DV; not of primary Room temperature Should be controlled
interest
Confounding Has affected DV; was not Caffeine intake Was NOT controlled — ruins results
controlled
Internal validity is the degree of confidence that a causal relationship established in
a study is trustworthy and not influenced by outside factors.
Core Psychology| IGCSE Research Methods Page 4
