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Explore data, probability, and statistical inference
This AP Statistics course on Study Mondo covers 34 topics organized across 6 categories. Each topic includes detailed written explanations, worked examples, practice problems with step-by-step solutions, flashcards for review, and interactive lessons to help you master the material.
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Analyzing distributions of data
Learn to identify categorical vs. quantitative data, and understand different sampling methods.
Create and interpret histograms, dotplots, stemplots, bar graphs, and pie charts.
Describe the shape, center, spread, and outliers of a distribution using SOCS.
Calculate and interpret mean, median, and mode as measures of central tendency.
Calculate and interpret range, IQR, variance, and standard deviation.
Study design and data collection
Compare simple random sampling, stratified, cluster, and systematic sampling methods.
Distinguish between observational studies and experiments, and understand causation vs. association.
Design experiments using control, randomization, replication, and blocking.
Identify sources of bias in sampling and surveys including voluntary response and convenience sampling.
Basic probability and random variables
Apply addition and multiplication rules, and understand complements and mutually exclusive events.
Calculate conditional probabilities using formulas and two-way tables.
Test for independence using probability rules and understand its implications.
Define discrete random variables, calculate expected value, variance, and standard deviation.
Apply the binomial distribution to count successes in fixed trials with conditions BINS.
Use the geometric distribution to model the number of trials until the first success.
Understand continuous random variables, probability density functions, and uniform distributions.
Estimating population parameters
Understand sampling distributions and the variability of sample statistics.
Apply the Central Limit Theorem to approximate sampling distributions as Normal.
Construct and interpret confidence intervals for a population proportion.
Construct and interpret confidence intervals for a population mean using the t-distribution.
Correctly interpret confidence intervals and understand confidence level meaning.
Testing claims about populations
Set up hypothesis tests with null and alternative hypotheses, significance level, and p-values.
Understand Type I and Type II errors, their probabilities, and the concept of power.
Perform one-sample and two-sample z-tests for proportions.
Perform one-sample and two-sample t-tests for means.
Analyze paired data using the paired t-test and matched pairs designs.
Perform chi-square tests for goodness of fit, homogeneity, and independence.
Analyzing relationships between variables
Create scatterplots and calculate the correlation coefficient r to describe linear relationships.
Find and interpret the least-squares regression line (LSRL) and make predictions.
Analyze residual plots to assess the fit of a regression model.
Interpret r² as the proportion of variability explained by the regression model.
Use power, logarithmic, and exponential transformations to achieve linearity.
Perform inference for the slope of a regression line using t-tests and confidence intervals.