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AP®︎/College Statistics

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Exploring categorical data

The language of variation: Variables: Exploring categorical dataRepresenting a categorical variable with graphs: Exploring categorical dataRepresenting two categorical variables: Exploring categorical data
Statistics for two categorical variables: Exploring categorical data

Exploring one-variable quantitative data: Displaying and describing

Representing a quantitative variable with dot plots: Exploring one-variable quantitative data: Displaying and describingRepresenting a quantitative variable with histograms and stem plots: Exploring one-variable quantitative data: Displaying and describingDescribing the distribution of a quantitative variable: Exploring one-variable quantitative data: Displaying and describing
Comparing distributions of a quantitative variable: Exploring one-variable quantitative data: Displaying and describing

Exploring one-variable quantitative data: Summary statistics

Measuring center in quantitative data: Exploring one-variable quantitative data: Summary statisticsMore on mean and median: Exploring one-variable quantitative data: Summary statisticsMeasuring variability in quantitative data: Exploring one-variable quantitative data: Summary statistics
Effects of linear transformations: Exploring one-variable quantitative data: Summary statisticsMore on standard deviation (optional): Exploring one-variable quantitative data: Summary statisticsGraphical representations of summary statistics: Exploring one-variable quantitative data: Summary statistics

Exploring one-variable quantitative data: Percentiles, z-scores, and the normal distribution

Percentiles: Exploring one-variable quantitative data: Percentiles, z-scores, and the normal distributionZ-scores: Exploring one-variable quantitative data: Percentiles, z-scores, and the normal distributionDensity curves: Exploring one-variable quantitative data: Percentiles, z-scores, and the normal distribution
Normal distributions and the empirical rule: Exploring one-variable quantitative data: Percentiles, z-scores, and the normal distributionNormal distribution calculations: Exploring one-variable quantitative data: Percentiles, z-scores, and the normal distribution

Exploring two-variable quantitative data

Representing the relationship between two quantitative variables: Exploring two-variable quantitative dataCorrelation: Exploring two-variable quantitative dataResiduals: Exploring two-variable quantitative data
Least-squares regression: Exploring two-variable quantitative dataAnalyzing departures from linearity: Exploring two-variable quantitative data

Collecting data

Introduction to planning a study: Collecting dataPotential problems with sampling: Collecting dataRandom sampling and data collection: Collecting data
Introduction to experimental design: Collecting dataInference and experiments: Collecting data

Probability

Estimating probabilities using simulation: ProbabilityMutually exclusive events and unions of events: ProbabilityConditional probability: Probability
Independent versus dependent events and the multiplication rule: Probability

Random variables and probability distributions

Introduction to random variables and probability distributions: Random variables and probability distributionsMean and standard deviation of random variables: Random variables and probability distributionsTransforming random variables: Random variables and probability distributions
Combining random variables: Random variables and probability distributionsIntroduction to the binomial distribution: Random variables and probability distributionsParameters for a binomial distribution: Random variables and probability distributionsThe geometric distribution: Random variables and probability distributions

Sampling distributions

The normal distribution, revisited: Sampling distributionsThe central limit theorem: Sampling distributionsBiased and unbiased point estimates: Sampling distributions
Sampling distributions for sample proportions: Sampling distributionsSampling distributions for differences in sample proportions: Sampling distributionsSampling distributions for sample means: Sampling distributionsSampling distributions for differences in sample means: Sampling distributions

Inference for categorical data: Proportions

Introduction to confidence intervals: Inference for categorical data: ProportionsConfidence intervals for proportions: Inference for categorical data: ProportionsThe idea of significance tests: Inference for categorical data: ProportionsSetting up a test for a population proportion: Inference for categorical data: Proportions
Carrying out a test for a population proportion: Inference for categorical data: ProportionsConcluding a test for a population proportion: Inference for categorical data: ProportionsPotential errors when performing tests: Inference for categorical data: ProportionsConfidence intervals for the difference of two proportions: Inference for categorical data: ProportionsTesting for the difference of two population proportions: Inference for categorical data: Proportions

Inference for quantitative data: Means

Constructing a confidence interval for a population mean: Inference for quantitative data: MeansSetting up a test for a population mean: Inference for quantitative data: MeansCarrying out a test for a population mean: Inference for quantitative data: Means
Confidence intervals for the difference of two means: Inference for quantitative data: MeansTesting for the difference of two population means: Inference for quantitative data: Means

Inference for categorical data: Chi-square

Chi-square test for goodness of fit: Inference for categorical data: Chi-squareChi square tests for relationships (homogeneity or independence): Inference for categorical data: Chi-square

Inference for quantitative data: slopes

Confidence intervals for the slope of a regression model: Inference for quantitative data: slopesTesting for the slope of a regression model: Inference for quantitative data: slopes

Prepare for the 2022 AP®︎ Statistics Exam

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Prepare for the exam: Prepare for the 2022 AP®︎ Statistics Exam

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