Free multiple-choice practice exams for undergraduate and graduate students in psychology and the health sciences, across five subjects: psychometrics, descriptive statistics, inferential statistics, SPSS and medical data analysis. Pick a topic or a whole subject, answer questions drawn at random from the bank, see your overall and by-topic score on screen, and receive the full correction — every question with your answer, the correct one and a teaching explanation — in your academic inbox.
Worked example: a 20-item questionnaire with a Cronbach alpha of .62 cannot be called valid just for exceeding .60; alpha measures internal consistency, not validity, and .62 sits below the .70 research guideline (Nunnally & Bernstein, 1994), so the justified decision is to review the items before using the total score.
Is it free? Yes: no sign-up, no card; only an email at the end, to send the correction. Does it have to be my university email? No, any address works: the answer key never travels to the browser, which is why an email is needed. If you use your university, hospital or research-center address, your center counts on the adoption map, which is what keeps the exams free.
Free practice exams in psychometrics, statistics, SPSS and medical data analysis. Instant score, fully explained correction sent to your academic email.
Five subjects, random questions on every attempt and your score on the spot. Each exam covers the topics that show up in undergraduate and master’s courses, and the correction explains every answer.
Reliability, validity, classical test theory, item analysis, factor analysis, IRT and norms: the eight topics that show up in any undergraduate or graduate Psychometrics exam. Take the Psychometrics exam
Topics: Classical reliability, Validity, CTT and measurement error, Item analysis, Exploratory factor analysis (EFA), CFA and invariance, Basic IRT, Norms and transformed scores.
Mean, median and mode; variance and standard deviation; percentiles and z scores; distribution shape; correlation and simple regression. The foundation everything else rests on. Take the Descriptive statistics exam
Topics: Central tendency, Variability, Relative position and transformed scores, Distributions and skewness, Correlation, Simple linear regression.
The heart of data analysis: what a p-value really means, how to keep Type I and Type II errors straight, and when to use t, ANOVA, chi-square or their non-parametric alternatives. With numeric scenarios you can solve in your head. Take the Inferential statistics exam
Topics: Hypothesis testing logic and the p-value, Type I and Type II errors and power, Confidence intervals, The t-test, ANOVA, Chi-square, Non-parametric tests, Effect size.
Interpreting real SPSS output: from the Data Editor to reliability, through descriptives, t tests, ANOVA, correlation and regression. Every question comes with a table just like the ones you will meet in your lab sessions. Take the Data analysis with SPSS exam
Topics: Data Editor and Transform, Descriptives and Explore, t tests, ANOVA, Correlation and regression, Reliability.
Study designs, risk measures, diagnostic tests, ROC curves, survival analysis and critical appraisal: the statistics used (and misread) every day in medicine and the health sciences. Take the Medical data analysis exam
Topics: Study designs, OR, RR and NNT, Sensitivity, specificity and predictive values, ROC curve, Survival and Kaplan-Meier, Bias and critical appraisal.