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AP courses

AP Statistics

Data, chance, and the reasoning that turns samples into honest conclusions about the world.

11 units · 91 lessons · 292 practice items · 148 videos

AP Statistics moves through the full statistical story: describing one- and two-variable data, designing studies and experiments that can actually answer a question, building probability and sampling-distribution intuition, and then the inference arc, confidence intervals and significance tests for proportions, means, counts, and regression slopes. Every procedure is taught through the same four-step frame, so by the end the course reads as one method applied many ways.

The practice is unusually hands-on for a statistics course: you compute conditional frequencies inside live two-way tables, drag a boundary along a shaded normal curve to find cutoffs, fit regression lines to scatterplots by hand, run seeded sampling simulations and watch the central limit theorem assemble itself, and work chi-square tests cell by cell. Skill practice deals randomized problems until you have mastered each idea, and unit tests plus semester exams draw from the same pools.

This course follows the College Board's published AP Statistics framework.

Syllabus

Every published lesson in this course, by unit.

1Exploring one-variable data11 lessons
  1. 1Introducing statistics: what can we learn from data?
  2. 2The language of variation: variables
  3. 3Representing a categorical variable with tables
  4. 4Representing a categorical variable with graphs
  5. 5Representing a quantitative variable with graphs
  6. 6Describing the distribution of a quantitative variable
  7. 7Summary statistics for a quantitative variable
  8. 8Graphical representations of summary statistics
  9. 9Comparing distributions of a quantitative variable
  10. 10The normal distribution
  11. 11Unit 1 test
2Exploring two-variable data10 lessons
  1. 1Introducing statistics: are variables related?
  2. 2Representing two categorical variables
  3. 3Statistics for two categorical variables
  4. 4Representing the relationship between two quantitative variables
  5. 5Correlation
  6. 6Linear regression models
  7. 7Residuals
  8. 8Least-squares regression
  9. 9Analyzing departures from linearity
  10. 10Unit 2 test
3Collecting data8 lessons
  1. 1Introducing statistics: do the data we collected tell the truth?
  2. 2Introduction to planning a study
  3. 3Random sampling and data collection
  4. 4Potential problems with sampling
  5. 5Introduction to experimental design
  6. 6Selecting an experimental design
  7. 7Inference and experiments
  8. 8Unit 3 test
4Probability, random variables, and probability distributions13 lessons
  1. 1Introducing statistics: random and non-random patterns?
  2. 2Estimating probabilities using simulation
  3. 3Introduction to probability
  4. 4Mutually exclusive events
  5. 5Conditional probability
  6. 6Independent events and unions of events
  7. 7Introduction to random variables and probability distributions
  8. 8Mean and standard deviation of random variables
  9. 9Combining random variables
  10. 10Introduction to the binomial distribution
  11. 11Parameters for a binomial distribution
  12. 12The geometric distribution
  13. 13Unit 4 test
ExamSemester 1 midterm1 lesson
  1. 1Semester 1 midterm
5Sampling distributions9 lessons
  1. 1Introducing statistics: why is my sample not like yours?
  2. 2The normal distribution, revisited
  3. 3The central limit theorem
  4. 4Biased and unbiased point estimates
  5. 5Sampling distributions for sample proportions
  6. 6Sampling distributions for differences in sample proportions
  7. 7Sampling distributions for sample means
  8. 8Sampling distributions for differences in sample means
  9. 9Unit 5 test
6Inference for categorical data: proportions12 lessons
  1. 1Introducing statistics: why be normal?
  2. 2Constructing a confidence interval for a population proportion
  3. 3Justifying a claim based on a confidence interval for a population proportion
  4. 4Setting up a test for a population proportion
  5. 5Interpreting p-values
  6. 6Concluding a test for a population proportion
  7. 7Potential errors when performing tests
  8. 8Confidence intervals for the difference of two proportions
  9. 9Justifying a claim based on a confidence interval for a difference of population proportions
  10. 10Setting up a test for the difference of two population proportions
  11. 11Carrying out a test for the difference of two population proportions
  12. 12Unit 6 test
7Inference for quantitative data: means11 lessons
  1. 1Introducing statistics: should I worry about error?
  2. 2Constructing a confidence interval for a population mean
  3. 3Justifying a claim about a population mean based on a confidence interval
  4. 4Setting up a test for a population mean
  5. 5Carrying out a test for a population mean
  6. 6Confidence intervals for the difference of two means
  7. 7Justifying a claim about the difference of two means based on a confidence interval
  8. 8Setting up a test for the difference of two population means
  9. 9Carrying out a test for the difference of two population means
  10. 10Skills focus: selecting, implementing, and communicating inference procedures
  11. 11Unit 7 test
8Inference for categorical data: chi-square8 lessons
  1. 1Introducing statistics: are my results unexpected?
  2. 2Setting up a chi-square goodness of fit test
  3. 3Carrying out a chi-square test for goodness of fit
  4. 4Expected counts in two-way tables
  5. 5Setting up a chi-square test for homogeneity or independence
  6. 6Carrying out a chi-square test for homogeneity or independence
  7. 7Skills focus: selecting an appropriate inference procedure for categorical data
  8. 8Unit 8 test
9Inference for quantitative data: slopes7 lessons
  1. 1Introducing statistics: do those points align?
  2. 2Confidence intervals for the slope of a regression model
  3. 3Justifying a claim about the slope of a regression model based on a confidence interval
  4. 4Setting up a test for the slope of a regression model
  5. 5Carrying out a test for the slope of a regression model
  6. 6Skills focus: selecting an appropriate inference procedure
  7. 7Unit 9 test
ExamSemester 2 final1 lesson
  1. 1Semester 2 final