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AP®︎/College Statistics (K-A)

Exploring categorical data (K-A)

Representing a categorical variable with graphs (K-A)

Representing two categorical variables (K-A)

Statistics for two categorical variables (K-A)

The language of variation: Variables (K-A)

Exploring one-variable quantitative data: Displaying and describing (K-A)

Comparing distributions of a quantitative variable (K-A)

Describing the distribution of a quantitative variable (K-A)

Representing a quantitative variable with dot plots (K-A)

Representing a quantitative variable with histograms and stem plots (K-A)

Exploring one-variable quantitative data: Summary statistics (K-A)

Effects of linear transformations (K-A)

Graphical representations of summary statistics (K-A)

Measuring center in quantitative data (K-A)

Measuring variability in quantitative data (K-A)

More on mean and median (K-A)

More on standard deviation (optional) (K-A)

Exploring one-variable quantitative data: Percentiles, z-scores, and the normal distribution (K-A)

Density curves (K-A)

Normal distribution calculations (K-A)

Normal distributions and the empirical rule (K-A)

Percentiles (K-A)

Z-scores (K-A)

Exploring two-variable quantitative data (K-A)

Analyzing departures from linearity (K-A)

Correlation (K-A)

Least-squares regression (K-A)

Representing the relationship between two quantitative variables (K-A)

Residuals (K-A)

Collecting data (K-A)

Inference and experiments (K-A)

Introduction to experimental design (K-A)

Introduction to planning a study (K-A)

Potential problems with sampling (K-A)

Random sampling and data collection (K-A)

Probability (K-A)

Conditional probability (K-A)

Estimating probabilities using simulation (K-A)

Independent versus dependent events and the multiplication rule (K-A)

Mutually exclusive events and unions of events (K-A)

Random variables and probability distributions (K-A)

Combining random variables (K-A)

Introduction to random variables and probability distributions (K-A)

Introduction to the binomial distribution (K-A)

Mean and standard deviation of random variables (K-A)

Parameters for a binomial distribution (K-A)

The geometric distribution (K-A)

Transforming random variables (K-A)

Sampling distributions (K-A)

Biased and unbiased point estimates (K-A)

Sampling distributions for differences in sample means (K-A)

Sampling distributions for differences in sample proportions (K-A)

Sampling distributions for sample means (K-A)

Sampling distributions for sample proportions (K-A)

The central limit theorem (K-A)

The normal distribution, revisited (K-A)

Inference for categorical data: Proportions (K-A)

Carrying out a test for a population proportion (K-A)

Concluding a test for a population proportion (K-A)

Confidence intervals for proportions (K-A)

Confidence intervals for the difference of two proportions (K-A)

Introduction to confidence intervals (K-A)

Potential errors when performing tests (K-A)

Setting up a test for a population proportion (K-A)

Testing for the difference of two population proportions (K-A)

The idea of significance tests (K-A)

Inference for quantitative data: Means (K-A)

Carrying out a test for a population mean (K-A)

Confidence intervals for the difference of two means (K-A)

Constructing a confidence interval for a population mean (K-A)

Setting up a test for a population mean (K-A)

Testing for the difference of two population means (K-A)

Inference for categorical data: Chi-square (K-A)

Chi square tests for relationships (homogeneity or independence) (K-A)

Chi-square test for goodness of fit (K-A)

Inference for quantitative data: slopes (K-A)

Confidence intervals for the slope of a regression model (K-A)

Testing for the slope of a regression model (K-A)

Prepare for the 2022 AP®︎ Statistics Exam (K-A)

Prepare for the exam (K-A)