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Unit 1: Exploring One-Variable Data (40)
  • Variation in categorical and quantitative variables (0)
  • Representing data using tables or graphs (10)
  • Calculating and interpreting statistics (10)
  • Describing and comparing distributions of data (10)
  • The normal distribution (10)
Unit 2: Exploring Two-Variable Data (70)
  • Comparing representations of 2 categorical variables (10)
  • Calculating statistics for 2 categorical variables (10)
  • Representing bivariate quantitative data using scatter plots (10)
  • Describing associations in bivariate data and interpreting correlation (10)
  • Linear regression models (10)
  • Residuals and residual plots (10)
  • Departures from linearity (10)
Unit 3: Collecting Data (50)
  • Planning a study (10)
  • Sampling methods (10)
  • Sources of bias in sampling methods (10)
  • Designing an experiment (10)
  • Interpreting the results of an experiment (10)
Unit 4: Probability; Random Variables and Probability Distributions (40)
  • Using simulation to estimate probabilities (0)
  • Calculating the probability of a random event (10)
  • Random variables and probability distributions (10)
  • The binomial distribution (10)
  • The geometric distribution (10)
Unit 5: Sampling Distributions (40)
  • Variation in statistics for samples collected from the same population (0)
  • The central limit theorem (10)
  • Biased and unbiased point estimates (10)
  • Sampling distributions for sample proportions (10)
  • Sampling distributions for sample means (10)
Unit 6: Inference for Categorical Data: Proportions (50)
  • Constructing and interpreting a confidence interval for a population proportion (10)
  • Setting up and carrying out a test for a population proportion (10)
  • Interpreting a p-value and justifying a claim about a population proportion (10)
  • Type I and Type II errors in significance testing (10)
  • Confidence intervals and tests for the difference of 2 proportions (10)
Unit 7: Inference for Quantitative Data: Means (40)
  • Constructing and interpreting a confidence interval for a population mean (10)
  • Setting up and carrying out a test for a population mean (10)
  • Interpreting a p-value and justifying a claim about a population mean (10)
  • Confidence intervals and tests for the difference of 2 population means (10)
Unit 8: Inference for Categorical Data: Chi-Square (40)
  • The chi-square test for goodness of fit (10)
  • The chi-square test for homogeneity (10)
  • The chi-square test for independence (10)
  • Selecting an appropriate inference procedure for categorical data (10)
Unit 9: Inference for Quantitative Data: Slopes (30)
  • Confidence intervals for the slope of a regression model (10)
  • Setting up and carrying out a test for the slope of a regression model (10)
  • Selecting an appropriate inference procedure (10)