AP Statistics study plan
AP Statistics · Give each week a clear focus.
8 weeks · About 6 hours per week
Exploring One-Variable Data and Collecting Data
Distinguish categorical vs. quantitative variables and identify the correct graphical display (bar chart, histogram, boxplot, dotplot) for each
Compute and interpret measures of center, spread, and position (mean, median, range, IQR, standard deviation, z-scores, percentiles)
Apply the 1.5×IQR rule to flag outliers and describe distribution shape, center, and spread in context
Read and compare cumulative relative frequency graphs and ogives
Your checkpoint
A one-page reference sheet of summary-statistic formulas plus 15 solved free-response-style description items scored against a rubric you write
Exploring One-Variable Data and Collecting Data
Design and critique sampling methods (SRS, stratified, cluster, systematic, convenience) and identify sources of bias
Distinguish observational studies from experiments and identify confounding variables
Explain the purpose of randomization, control, blocking, and replication in experimental design
Match a study description to its design and state the scope of inference
Your checkpoint
A written critique of 6 study scenarios (3 sampling, 3 experimental design) each with bias source, improvement, and scope of inference
Probability, Random Variables, and Probability Distributions
Apply addition, multiplication, complement, and conditional probability rules to two-way tables and tree diagrams
Test independence using P(A|B) = P(A) and interpret the result in context
Compute means and variances of sums and differences of random variables
Use the binomial and geometric settings to compute probabilities and identify when each applies
Your checkpoint
A 20-item problem set covering probability rules, independence, and binomial/geometric models with full worked solutions
Probability, Random Variables, and Probability Distributions
Apply the normal distribution to compute probabilities and find cutoffs using z-scores and inverse normal
State and apply the central limit theorem to sampling distributions of sample means and proportions
Compute standard errors for sample means and proportions and describe the effect of sample size
Distinguish the distribution of a population, a sample, and a sample statistic
Your checkpoint
A timed 25-minute quiz (10 items) on normal calculations and sampling distributions, self-graded with a written error log
Inference for Categorical Data: Proportions
Check the conditions (random, 10%, large counts) for constructing a one-proportion z-interval
Construct and interpret a one-proportion z-interval and a confidence level in context
Perform a one-proportion z-test: state hypotheses, compute the test statistic and p-value, and conclude in context
Distinguish a significance level from a p-value and interpret both correctly
Your checkpoint
Two complete FRQ-style responses (one interval, one significance test) written under 15-minute time limits and scored against the AP scoring guidelines structure
Inference for Categorical Data: Proportions
Construct and interpret a two-proportion z-interval and perform a two-proportion z-test
Identify Type I and Type II errors and describe the effect of significance level, sample size, and effect size on power
Explain the relationship between confidence intervals and two-sided tests
Recognize common misinterpretations of p-values and confidence levels
Your checkpoint
A comparison table of one- vs. two-proportion inference (conditions, formulas, interpretation sentences) plus 8 error-identification items
Inference for Quantitative Data: Means
Check conditions and construct a one-sample t-interval and perform a one-sample t-test
Construct and interpret a two-sample t-interval and perform a two-sample t-test
Distinguish paired vs. two-sample designs and analyze matched-pairs data with a t-procedure
Use t-tables and technology output to find critical values and p-values
Your checkpoint
Three fully written t-procedure solutions (one-sample, two-sample, paired) with conditions, mechanics, and conclusions in context
Regression Analysis & Inference for Quantitative Data: Means
Interpret slope, y-intercept, r, r², and the standard deviation of residuals in context
Construct and interpret a confidence interval and significance test for a regression slope
Examine residual plots to assess linearity and identify influential points and outliers
Review weak spots across all five domains and practice mixed-topic FRQs under time
Your checkpoint
A full-length timed practice exam (40 MC + 6 FRQ) with a scored error analysis identifying the two highest-priority review areas
Milestones
Week 2: Score at least 80% on a self-made 15-item quiz on describing distributions and study design, with every missed item rewritten correctly
Week 4: Achieve 80%+ on the timed probability and sampling-distribution quiz and correctly explain the CLT in writing without notes
Week 6: Write both one- and two-proportion inference conclusions in context with all conditions checked, verified against a scoring rubric
Week 8: Complete the full-length practice exam within time and score at or above your target AP score, with an error log covering every missed item