Bachelor of Arts in Psychology: Methodical & Stats Analysis 1 Flashcards
6 cards from real BAPSY practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 Bachelor of Arts in Psychology: Methodical & Stats Analysis 1 flashcards as text
A researcher sets alpha at 0.05 and fails to reject a null hypothesis that is actually false. What type of error has occurred?
Answer: Type II error
A Type II error (beta error) occurs when a researcher fails to reject a false null hypothesis — a 'miss.' A Type I error is the opposite: rejecting a true null hypothesis.
A multiple regression model yields R² = 0.64. A researcher adds a second predictor and R² increases to 0.65. What should the researcher most likely conclude?
Answer: The increase in R² is likely due to chance and the predictor adds little value
An R² increase of only 0.01 (1%) is trivially small. Researchers should examine adjusted R² and the predictor's significance before concluding the new variable meaningfully improves the model.
Cohen's d is calculated as 0.20 for a study comparing two group means. How is this effect size conventionally interpreted?
Answer: Small effect
By Cohen's conventions, d = 0.20 is a small effect, d = 0.50 is medium, and d = 0.80 or above is large. A small effect can still be meaningful depending on the research context.
A psychologist measures anxiety levels in the same group of participants before therapy, after 4 weeks, and after 8 weeks. Which statistical test is most appropriate?
Answer: Repeated-measures ANOVA
Repeated-measures ANOVA is used when the same participants are measured at three or more time points, accounting for within-subject correlation. An independent-samples t-test or between-subjects ANOVA would be inappropriate because the groups are not independent.
A scale measuring depression produces very similar scores when administered to the same participants two weeks apart. This scale demonstrates high:
Answer: Test-retest reliability
Test-retest reliability refers to the consistency of scores over time when the measured construct has not changed. Validity addresses whether the scale measures what it is intended to measure — a separate property.
In a normal distribution, approximately what percentage of scores fall within one standard deviation above and below the mean?
Answer: 68%
The empirical rule states that approximately 68% of data fall within ±1 SD, 95% within ±2 SD, and 99.7% within ±3 SD of the mean in a normal distribution. This is foundational to interpreting z-scores and confidence intervals.