AP Psychology — statistics and data interpretation

Data Interpretation is one of the four science practices in the AP Psychology course framework. It asks for less mathematics than a statistics course but more precision than most students bring to it: calculate a mean or a median from a handful of scores, say what a standard deviation or a percentile rank means, read a correlation coefficient for direction and strength, and interpret a result reported as an effect size or as statistically significant. The Article Analysis Question in the free-response section always includes a statistic from a study, and one point depends on describing correctly what it shows.

This material covers every item on that list with small invented data sets written into the questions themselves, so nothing depends on a chart you cannot see. It trains calculating the mean, median, mode and range; choosing the median when an extreme score pulls the mean; recognizing a bimodal distribution; comparing spread through the standard deviation; the normal curve, with about 68 percent of scores within one standard deviation of the mean and about 95 percent within two; percentile rank as relative standing, not percent correct; positive and negative skew and what they do to the mean; reading correlation coefficients, where the sign gives direction and the absolute value gives strength; describing a scatterplot in words; effect sizes, read with the convention the course framework states (about 0.2 small, 0.3 to 0.7 medium, 0.8 or more large); statistical significance, which means a result is unlikely to be due to chance and not that it is large or important; and regression toward the mean.

Every calculation in the quiz explanations is shown step by step, so a wrong answer can be traced to the step where it went wrong.

Four formats are offered. The quiz has twelve questions, each with its own data. The flashcards drill the terms. The oral exam begins with a short data set to summarize out loud and continues one question at a time through spread, the normal curve, correlation and the difference between significance and effect size, ending with brief feedback. The written work is a printable sheet of eight tasks to answer by hand, from computing and comparing measures of central tendency to explaining why a statistically significant result can still be too small to matter.

The material is based on the Data Interpretation practice in the published AP Psychology course framework, including its October 2025 clarification on effect size and statistical significance. The companion material on research design covers methods and ethics.

• Calculate the mean, median, mode and range and choose the right measure when there is an outlier
• Interpret standard deviation, the normal curve and percentile rank
• Recognize bimodal, positively skewed and negatively skewed distributions
• Read correlation coefficients and described scatterplots for direction and strength
• Interpret effect sizes and statistical significance and explain regression toward the mean

Practice material written by Zestly, based on the College Board AP Psychology Course and Exam Description (effective fall 2024, with the October 2025 clarifications), Science Practice 3, Data Interpretation (skills 3.A to 3.C). The effect-size convention (about 0.2 small, 0.3 to 0.7 medium, 0.8 or more large) follows that framework. All data sets are invented.