⋆
⋆
PYC3704: Psychological Research
May/June Examination 2026 Preparation
Covers Past Papers: May/June 2023, 2024 & 2025
⋆ ⋄ ⋆ ⋄ ⋆ ⋄ ⋆ ⋄ ⋆
[ Psychology – Quantitative Research Methods [
_ Exam Revision Guide
PYC3704
Module Code:
Psychological Research
Module Name:
May/June Examination 2026
Paper / Exam:
2023, 2024 & 2025 (May/June)
Years Covered:
70 Multiple-Choice Questions (MCQs)
Format:
This revision guide covers all six topics tested in the PYC3704 examination. Work
through each question carefully and focus on understanding the logic, not just the
answer.
Exam Revision Notes | PYC3704 | 2023–2025
,PYC3704 | Psychological Research – Exam Revision May/June 2023–2025
How to Use This Revision Guide
Key Concept
This document covers all six topics of PYC3704 as tested in the May/June 2023,
2024 and 2025 examinations, reconstructed from the established UNISA PYC3704 cur-
riculum, tutorial letter feedback, and consistent exam patterns. Each question reflects
the scenario-based MCQ style used in the actual 70-item exam. The correct answer
is identified and explained. Distractors are addressed where they commonly mislead
students.
Topic distribution in the 70-item exam (per UNISA Tutorial Letter guid-
ance):
• Topic 1 – Inferential Statistics: approx. 12 items
• Topic 2 – Research Design: approx. 12 items
• Topic 3 – Statistical Tests (t-tests, ANOVA, Chi-square, Correlation): approx. 20
items
• Topic 4 – Effect Size & Power: approx. 6 items
• Topic 5 – Non-parametric Tests: approx. 10 items
• Topic 6 – Reporting & Interpreting Results: approx. 10 items
Page 2 of 19
,PYC3704 | Psychological Research – Exam Revision May/June 2023–2025
Topic 1 – Inferential Statistics ≈12 items
Q1 1 mark
Question: Which of the following best describes inferential statistics?
1. Describing the characteristics of a sample using numbers.
2. Organising data into frequency distributions and graphs.
3. Using sample data to draw conclusions about a population.
4. Calculating the mean, mode and median of a dataset.
Answer: Correct answer: 3
Inferential statistics is the branch of statistics concerned with using data collected
from a sample to make inferences (conclusions) about the population from which that
sample was drawn. Options 1, 2 and 4 all describe descriptive statistics, which
summarise or organise sample data without making broader generalisations.
Key Concept
Descriptive statistics describe what the data show. Inferential statistics answer
what the data imply about the wider population.
Q2 1 mark
Question: A researcher sets her level of significance at α = .05. What does this
mean?
1. She is 95% confident that the null hypothesis is true.
2. There is a 5% chance of rejecting a true null hypothesis.
3. There is a 5% chance that the alternative hypothesis is false.
4. The probability of a Type II error is 5%.
Answer: Correct answer: 2
The level of significance (α) is the probability of committing a Type I error – rejecting
the null hypothesis when it is actually true (a false positive). Setting α = .05 means the
researcher accepts a 5% risk of making this error. Options 3 and 4 confuse Type I with
Page 3 of 19
, PYC3704 | Psychological Research – Exam Revision May/June 2023–2025
Type II errors; option 1 misinterprets confidence intervals.
⋆ Exam Tip
Type I error = false positive (rejecting a true H0 ). Type II error (β) = false
negative (failing to reject a false H0 ). Know both for the exam.
Q3 1 mark
Question: In statistical hypothesis testing, the test statistic is used to determine the
, which is compared to the chosen to make an inference about the
hypotheses.
1. p-value; test statistic
2. test statistic; p-value; level of significance
3. p-value; level of significance
4. level of significance; p-value
Answer: Correct answer: 3
The test statistic (e.g. t, F , χ2 ) is computed from sample data. It is used to determine
the p-value (the probability of observing results at least as extreme as those found,
assuming H0 is true). The p-value is then compared to the level of significance (α) to
decide whether to reject H0 .
Compute Obtain Reject / Fail
Compare to α
Test Statistic p-value to Reject H0
Q4 1 mark
Question: A researcher obtains a p-value of .003. The level of significance is α = .05.
What conclusion should the researcher draw?
1. Fail to reject the null hypothesis because .003 < .05.
2. Reject the null hypothesis because .003 < .05.
3. Reject the alternative hypothesis because .003 is very small.
4. The results are statistically non-significant.
Page 4 of 19
⋆
PYC3704: Psychological Research
May/June Examination 2026 Preparation
Covers Past Papers: May/June 2023, 2024 & 2025
⋆ ⋄ ⋆ ⋄ ⋆ ⋄ ⋆ ⋄ ⋆
[ Psychology – Quantitative Research Methods [
_ Exam Revision Guide
PYC3704
Module Code:
Psychological Research
Module Name:
May/June Examination 2026
Paper / Exam:
2023, 2024 & 2025 (May/June)
Years Covered:
70 Multiple-Choice Questions (MCQs)
Format:
This revision guide covers all six topics tested in the PYC3704 examination. Work
through each question carefully and focus on understanding the logic, not just the
answer.
Exam Revision Notes | PYC3704 | 2023–2025
,PYC3704 | Psychological Research – Exam Revision May/June 2023–2025
How to Use This Revision Guide
Key Concept
This document covers all six topics of PYC3704 as tested in the May/June 2023,
2024 and 2025 examinations, reconstructed from the established UNISA PYC3704 cur-
riculum, tutorial letter feedback, and consistent exam patterns. Each question reflects
the scenario-based MCQ style used in the actual 70-item exam. The correct answer
is identified and explained. Distractors are addressed where they commonly mislead
students.
Topic distribution in the 70-item exam (per UNISA Tutorial Letter guid-
ance):
• Topic 1 – Inferential Statistics: approx. 12 items
• Topic 2 – Research Design: approx. 12 items
• Topic 3 – Statistical Tests (t-tests, ANOVA, Chi-square, Correlation): approx. 20
items
• Topic 4 – Effect Size & Power: approx. 6 items
• Topic 5 – Non-parametric Tests: approx. 10 items
• Topic 6 – Reporting & Interpreting Results: approx. 10 items
Page 2 of 19
,PYC3704 | Psychological Research – Exam Revision May/June 2023–2025
Topic 1 – Inferential Statistics ≈12 items
Q1 1 mark
Question: Which of the following best describes inferential statistics?
1. Describing the characteristics of a sample using numbers.
2. Organising data into frequency distributions and graphs.
3. Using sample data to draw conclusions about a population.
4. Calculating the mean, mode and median of a dataset.
Answer: Correct answer: 3
Inferential statistics is the branch of statistics concerned with using data collected
from a sample to make inferences (conclusions) about the population from which that
sample was drawn. Options 1, 2 and 4 all describe descriptive statistics, which
summarise or organise sample data without making broader generalisations.
Key Concept
Descriptive statistics describe what the data show. Inferential statistics answer
what the data imply about the wider population.
Q2 1 mark
Question: A researcher sets her level of significance at α = .05. What does this
mean?
1. She is 95% confident that the null hypothesis is true.
2. There is a 5% chance of rejecting a true null hypothesis.
3. There is a 5% chance that the alternative hypothesis is false.
4. The probability of a Type II error is 5%.
Answer: Correct answer: 2
The level of significance (α) is the probability of committing a Type I error – rejecting
the null hypothesis when it is actually true (a false positive). Setting α = .05 means the
researcher accepts a 5% risk of making this error. Options 3 and 4 confuse Type I with
Page 3 of 19
, PYC3704 | Psychological Research – Exam Revision May/June 2023–2025
Type II errors; option 1 misinterprets confidence intervals.
⋆ Exam Tip
Type I error = false positive (rejecting a true H0 ). Type II error (β) = false
negative (failing to reject a false H0 ). Know both for the exam.
Q3 1 mark
Question: In statistical hypothesis testing, the test statistic is used to determine the
, which is compared to the chosen to make an inference about the
hypotheses.
1. p-value; test statistic
2. test statistic; p-value; level of significance
3. p-value; level of significance
4. level of significance; p-value
Answer: Correct answer: 3
The test statistic (e.g. t, F , χ2 ) is computed from sample data. It is used to determine
the p-value (the probability of observing results at least as extreme as those found,
assuming H0 is true). The p-value is then compared to the level of significance (α) to
decide whether to reject H0 .
Compute Obtain Reject / Fail
Compare to α
Test Statistic p-value to Reject H0
Q4 1 mark
Question: A researcher obtains a p-value of .003. The level of significance is α = .05.
What conclusion should the researcher draw?
1. Fail to reject the null hypothesis because .003 < .05.
2. Reject the null hypothesis because .003 < .05.
3. Reject the alternative hypothesis because .003 is very small.
4. The results are statistically non-significant.
Page 4 of 19
