Math: High school & college Ages 14-18 ● Media ready

AP®︎/College Statistics

Learn a powerful collection of methods for working with data! AP® Statistics is all about formulating questions, collecting and analyzing data, and interpreting results from data.

19 units 118 lessons 181 videos 5 on CDN

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Unit 2 Exploring one-variable data and collecting data

1 Introducing statistics: what can we learn from data? Free 2 video(s) ● 2 Variables Free 2 video(s) ● 4 Tabular representation and summary statistics for one categorical variable 🔒 Pro 1 video(s) ● 5 Graphical representations for one categorical variable 🔒 Pro 1 video(s) 7 Graphical representations for one quantitative variable 🔒 Pro 2 video(s) 9 Descriptions for one quantitative variable distributions 🔒 Pro 1 video(s) 11 Summary statistics for one quantitative variable distributions 🔒 Pro 2 video(s) 13 Graphical representations of summary statistics for one quantitative variable 🔒 Pro 15 Comparisons of the distributions for one quantitative variable 🔒 Pro 3 video(s) 17 The investigative question revisited and data collection 🔒 Pro 5 video(s) 19 Random sampling 🔒 Pro 4 video(s) 20 Potential problems with sampling 🔒 Pro 2 video(s) 22 Experimental design 🔒 Pro 2 video(s) 10 Regression analysis: Unit test 🔒 Pro

Unit 3 Probability, random variables, and probability distributions

1 Tabular and graphical representations for the distributions 🔒 Pro 2 video(s) 3 Summary statistics for two categorical variables 🔒 Pro 1 video(s) 5 Estimating probabilities using simulation 🔒 Pro 1 video(s) 6 Introduction to probability 🔒 Pro 1 video(s) 8 Mutually exclusive events 🔒 Pro 9 Conditional probability 🔒 Pro 2 video(s) 10 Independent events and unions of events 🔒 Pro 3 video(s) 12 Introduction to random variables and probability distributions 🔒 Pro 5 video(s) 14 Parameters of random variables 🔒 Pro 3 video(s) 16 The binomial distribution 🔒 Pro 6 video(s) 18 The normal distribution 🔒 Pro 6 video(s) 20 Sampling distributions and the central limit theorem 🔒 Pro 4 video(s)

Unit 4 Inference for categorical data: proportions

1 Estimators 🔒 Pro 2 video(s) 3 Sampling distributions for sample proportions 🔒 Pro 4 video(s) 5 Constructing a confidence interval for a population proportion 🔒 Pro 5 video(s) 7 Setting up a test for a population proportion 🔒 Pro 4 video(s) 9 P-values 🔒 Pro 3 video(s) 10 Carrying out a test for a population proportion 🔒 Pro 2 video(s) 11 Potential errors when performing tests 🔒 Pro 4 video(s) 13 Sampling distributions for the difference between sample proportions 🔒 Pro 2 video(s) 15 Constructing a confidence interval for the difference between two population proportions 🔒 Pro 3 video(s) 17 Setting up a test for the difference between two population proportions 🔒 Pro 2 video(s) 18 Carrying out a test for the difference between two population proportions 🔒 Pro 2 video(s) 20 Setting up a chi-square test for homogeneity or independence 🔒 Pro 2 video(s) 21 Carrying out a chi-square test for homogeneity or independence 🔒 Pro

Unit 5 Inference for quantitative data: means

1 Sampling distributions for sample means 🔒 Pro 2 video(s) 3 Constructing a confidence interval for a population mean or population mean difference 🔒 Pro 6 video(s) 5 Setting up a test for a population mean or population mean difference 🔒 Pro 2 video(s) 7 Carrying out a test for a population mean or population mean difference 🔒 Pro 6 video(s) 8 Sampling distributions for the difference between two sample means 🔒 Pro 2 video(s) 10 Constructing a confidence interval for the difference between two population means 🔒 Pro 3 video(s) 12 Setting up a test for the difference between two populations means 🔒 Pro 2 video(s) 13 Carrying out a test for the difference between two population means 🔒 Pro 2 video(s)

Unit 6 Regression analysis

1 Graphical representations between two quantitative variables 🔒 Pro 3 Correlation 🔒 Pro 4 Linear regression models 🔒 Pro 6 Residuals 🔒 Pro 8 Least-squares regression 🔒 Pro 2 video(s)

Unit 7 Exploring categorical data

1 The language of variation: Variables 🔒 Pro 2 Representing a categorical variable with graphs 🔒 Pro 3 Representing two categorical variables 🔒 Pro 4 Statistics for two categorical variables 🔒 Pro

Unit 8 Exploring one-variable quantitative data: Displaying and describing

1 Representing a quantitative variable with dot plots 🔒 Pro 2 Representing a quantitative variable with histograms and stem plots 🔒 Pro 3 Describing the distribution of a quantitative variable 🔒 Pro 4 Comparing distributions of a quantitative variable 🔒 Pro

Unit 9 Exploring one-variable quantitative data: Summary statistics

1 Measuring center in quantitative data 🔒 Pro 2 More on mean and median 🔒 Pro 3 Measuring variability in quantitative data 🔒 Pro 4 Effects of linear transformations 🔒 Pro 5 More on standard deviation (optional) 🔒 Pro 4 video(s) 6 Graphical representations of summary statistics 🔒 Pro

Unit 10 Exploring one-variable quantitative data: Percentiles, z-scores, and the normal distribution

1 Percentiles 🔒 Pro 2 video(s) 2 Z-scores 🔒 Pro 3 Density curves 🔒 Pro 2 video(s) 4 Normal distributions and the empirical rule 🔒 Pro 5 Normal distribution calculations 🔒 Pro 1 video(s)

Unit 11 Exploring two-variable quantitative data

1 Representing the relationship between two quantitative variables 🔒 Pro 2 Correlation 🔒 Pro 3 Residuals 🔒 Pro 4 Least-squares regression 🔒 Pro 5 Analyzing departures from linearity 🔒 Pro 7 video(s)

Unit 12 Collecting data

1 Introduction to planning a study 🔒 Pro 1 video(s) 2 Potential problems with sampling 🔒 Pro 3 Random sampling and data collection 🔒 Pro 4 Introduction to experimental design 🔒 Pro 1 video(s) 5 Inference and experiments 🔒 Pro 1 video(s)

Unit 13 Probability

1 Estimating probabilities using simulation 🔒 Pro 2 Mutually exclusive events and unions of events 🔒 Pro 3 Conditional probability 🔒 Pro 1 video(s) 4 Independent versus dependent events and the multiplication rule 🔒 Pro 1 video(s)

Unit 14 Random variables and probability distributions

1 Introduction to random variables and probability distributions 🔒 Pro 2 Mean and standard deviation of random variables 🔒 Pro 3 Transforming random variables 🔒 Pro 2 video(s) 4 Combining random variables 🔒 Pro 6 video(s) 5 Introduction to the binomial distribution 🔒 Pro 5 video(s) 6 Parameters for a binomial distribution 🔒 Pro 7 The geometric distribution 🔒 Pro 7 video(s)

Unit 15 Sampling distributions

1 The normal distribution, revisited 🔒 Pro 1 video(s) 2 The central limit theorem 🔒 Pro 3 Biased and unbiased point estimates 🔒 Pro 4 Sampling distributions for sample proportions 🔒 Pro 5 Sampling distributions for differences in sample proportions 🔒 Pro 6 Sampling distributions for sample means 🔒 Pro 7 Sampling distributions for differences in sample means 🔒 Pro

Unit 16 Inference for categorical data: Proportions

1 Introduction to confidence intervals 🔒 Pro 3 video(s) 2 Confidence intervals for proportions 🔒 Pro 3 The idea of significance tests 🔒 Pro 4 Setting up a test for a population proportion 🔒 Pro 5 Carrying out a test for a population proportion 🔒 Pro 6 Concluding a test for a population proportion 🔒 Pro 3 video(s) 7 Potential errors when performing tests 🔒 Pro 8 Confidence intervals for the difference of two proportions 🔒 Pro 9 Testing for the difference of two population proportions 🔒 Pro 1 video(s)

Unit 17 Inference for quantitative data: Means

1 Constructing a confidence interval for a population mean 🔒 Pro 2 Setting up a test for a population mean 🔒 Pro 3 Carrying out a test for a population mean 🔒 Pro 4 Confidence intervals for the difference of two means 🔒 Pro 5 Testing for the difference of two population means 🔒 Pro 1 video(s)

Unit 18 Inference for categorical data: Chi-square

1 Chi-square test for goodness of fit 🔒 Pro 2 video(s) 2 Chi square tests for relationships (homogeneity or independence) 🔒 Pro

Unit 19 Inference for quantitative data: slopes

1 Confidence intervals for the slope of a regression model 🔒 Pro 3 video(s) 2 Testing for the slope of a regression model 🔒 Pro 3 video(s)

Unit 20 Prepare for the AP®︎ Statistics Exam

1 Prepare for the exam 🔒 Pro