One quantitative group
Use a one-sample t-test when comparing one sample mean with a hypothesized mean.
Practice choosing the right statistical test for common homework and research scenarios. Review t-tests, ANOVA, chi-square tests, regression, correlation, proportions, repeated measures, and nonparametric alternatives with explanations after every answer.
Reviewed for Statskan: original practice scenarios, visible answer explanations, and calculator links. Last reviewed: July 2026.
Many statistics assignments become easier once the test-selection logic is clear. A test is not chosen only because a topic appears in the chapter. It is chosen because the research question, variables, sample design, and assumptions match the method.
Use the filters to focus on a topic or difficulty level, then answer each scenario.
Use this quick guide before reading software output or calculating a p-value.
Use a one-sample t-test when comparing one sample mean with a hypothesized mean.
Use an independent t-test for separate groups and a paired t-test for matched or repeated observations.
Use ANOVA for independent group means and repeated-measures ANOVA for the same participants across conditions.
Use chi-square independence for two categorical variables and goodness-of-fit for one categorical variable versus expected counts.
Use correlation for association, linear regression for quantitative prediction, and logistic regression for binary outcomes.
Consider rank-based methods such as Mann-Whitney, Wilcoxon signed-rank, Kruskal-Wallis, or Spearman correlation.
Send the research question, variable list, sample design, data file or summary statistics, software requirement, and deadline. Statskan can help explain the correct test and next steps.
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A researcher wants to know whether the average study time for one class differs from 10 hours per week. The sample has 28 students and the population standard deviation is unknown. Which test fits best?
Answer: One-sample t-test
Use a one-sample t-test when one sample mean is compared with a known or hypothesized population mean and the population standard deviation is unknown.
A teacher compares final exam scores for students in an online class and an in-person class. The two groups contain different students. Which test fits best?
Answer: Independent-samples t-test
Use an independent-samples t-test when comparing the means of two separate groups on a quantitative outcome.
The same 18 students take a statistics quiz before and after a tutoring session. Which test fits best for comparing the two scores?
Answer: Paired-samples t-test
Use a paired-samples t-test when the same participants are measured twice or observations are naturally matched.
A researcher compares mean anxiety scores across three therapy groups. The outcome is quantitative and each participant belongs to only one group. Which test fits best?
Answer: One-way ANOVA
Use one-way ANOVA when comparing a quantitative outcome across three or more independent groups defined by one factor.
A study compares mean test scores by teaching method and by grade level. There are two categorical predictors and one quantitative outcome. Which test fits best?
Answer: Two-way ANOVA
Use two-way ANOVA when a quantitative outcome is compared across combinations of two categorical factors, often including an interaction.
A survey asks students whether they prefer online or in-person classes, then compares preferences across majors. Both variables are categorical. Which test fits best?
Answer: Chi-square test of independence
Use a chi-square test of independence to test whether two categorical variables are associated.
A store expects customers to choose four product colors equally often. Actual purchases are counted for each color. Which test fits best?
Answer: Chi-square goodness-of-fit test
Use a chi-square goodness-of-fit test when one categorical variable is compared with expected category counts or proportions.
A student wants to measure the linear relationship between hours studied and exam score. Both variables are quantitative. Which method fits best?
Answer: Pearson correlation
Use Pearson correlation to measure the strength and direction of a linear relationship between two quantitative variables.
A researcher wants to predict exam score from hours studied. Exam score is quantitative and hours studied is one quantitative predictor. Which method fits best?
Answer: Simple linear regression
Use simple linear regression when predicting a quantitative outcome from one predictor.
A study predicts first-year GPA from study hours, high-school GPA, attendance, and sleep. The outcome is quantitative and there are several predictors. Which method fits best?
Answer: Multiple linear regression
Use multiple linear regression when predicting a quantitative outcome from two or more predictors.
A researcher predicts whether a student passes or fails a course using attendance, prior GPA, and study time. The outcome has two categories. Which method fits best?
Answer: Logistic regression
Use logistic regression when the outcome is binary and predictors are used to estimate the probability of one outcome category.
A poll finds that 58% of 400 students support a new campus policy. The researcher wants to test whether support differs from 50%. Which test fits best?
Answer: One-proportion z-test
Use a one-proportion z-test when one sample proportion is compared with a hypothesized population proportion and sample-size conditions are reasonable.
A researcher compares the percentage of students who pass in two independent sections of the same course. Which test fits best?
Answer: Two-proportion z-test
Use a two-proportion z-test when comparing proportions from two independent groups.
Two independent groups rate satisfaction on an ordinal 1-to-5 scale, and the instructor wants a rank-based comparison. Which test fits best?
Answer: Mann-Whitney U test
Use the Mann-Whitney U test as a rank-based alternative for comparing two independent groups when ordinal data or non-normality makes a t-test less suitable.
The same students rate confidence before and after a workshop on an ordinal scale. Which rank-based test fits best?
Answer: Wilcoxon signed-rank test
Use the Wilcoxon signed-rank test for paired or repeated ordinal measurements when a paired t-test is not appropriate.
Four independent groups give ordinal ratings of a new app. The researcher wants to compare group distributions using ranks. Which test fits best?
Answer: Kruskal-Wallis test
Use the Kruskal-Wallis test as a rank-based alternative to one-way ANOVA for three or more independent groups.
The same participants complete a memory test after no caffeine, low caffeine, and high caffeine. The outcome is quantitative. Which test fits best?
Answer: Repeated-measures ANOVA
Use repeated-measures ANOVA when the same participants are measured under three or more conditions on a quantitative outcome.
A researcher examines whether class rank is related to stress rank. Both variables are ordinal ranks. Which method fits best?
Answer: Spearman rank correlation
Use Spearman rank correlation when measuring a monotonic relationship between ordinal or ranked variables.
A small 2 by 2 table has several expected counts below 5. The researcher wants to test association between two categorical variables. Which test fits best?
Answer: Fisher exact test
Use Fisher exact test for small-sample 2 by 2 categorical tables when chi-square expected-count assumptions are not met.
The same voters are asked before and after a campaign whether they support a policy. The outcome is yes or no at two paired time points. Which test fits best?
Answer: McNemar test
Use McNemar test for paired binary outcomes, such as yes/no responses measured before and after an intervention.
A researcher compares post-test scores across three teaching methods while adjusting for pre-test score. Which method fits best?
Answer: ANCOVA
Use ANCOVA when comparing group means on a quantitative outcome while adjusting for one or more quantitative covariates.
A researcher compares two independent group means but the assignment asks for a normality-resistant method because the data are strongly skewed. Which test is usually considered?
Answer: Mann-Whitney U test
For two independent groups with ordinal or strongly non-normal quantitative data, Mann-Whitney U is a common nonparametric alternative.
Use this quiz to study test selection, prepare questions for tutoring, and understand why a method fits a scenario. For graded work, follow your institution academic-integrity rules.
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