Construct and interpret graphical displays of univariate data distributions

Summarize and compare distributions of univariate data

Explore bivariate and categorical data

Identify center, spread, cluster, gaps, outliers, and shape of data

Measure median, mean, range, interquartile range, standard deviation, quartiles, percentiles, and z-scores

Use box plots

Compare center and spread, clusters and gaps, outliers and other unusual features, and shapes

Analyze patterns in scatter plots

Identify correlation and linearity

Identify least-squares regression line

Identify residual plots, outliers, and influential points

Apply transformations to achieve linearity

Identify frequency tables and bar charts

Identify marginal and joint frequencies for two-way tables

Identify conditional relative frequencies and association

Compare distributions using bar charts

Identify census and sample survey

Identify experiment

Identify observational study

Identify characteristics of surveys

Identify populations

Identify samples

Identify random selections

Identify sources of bias in sampling and surveys

Identify sampling methods

Identify characteristics of experiments

Identify treatments, control groups, experimental units, random assignments, and replication

Identify sources of bias and confounding

Identify randomized design

Identify randomized block design

Interpret probability

Interpret long-run relative frequency

Apply law of large numbers

Apply addition rule

Apply multiplication rule

Apply conditional probability

Apply independence

Identify discrete random variables

Identify probability distributions

Simulate random behavior

Simulate probability distributions

Calculate mean

Calculate standard deviation

Apply linear transformation of a random variable

Identify the notion of independence versus dependence

Apply mean and standard deviation for sums and differences of independent random variables

Apply properties of normal distribution

Use tables of normal distribution

Use the normal distribution as a model for measurement

Identify sampling distributions of a sample proportion

Identify sampling distributions of a sample mean

Apply central limit theorem

Identify sampling distributions of a difference between two independent sample proportions

Identify sampling distributions of a difference between two independent sample means

Apply simulations of sampling distributions

Estimating population parameters

Estimating margins of error

Apply properties of point estimators

Apply logic of confidence intervals, meaning of confidence level and confidence intervals

Apply properties of confidence intervals

Identify large sample confidence interval for a proportion

Identify large sample confidence interval for a difference between two proportions

Identify confidence interval for a mean

Identify confidence interval for a difference between two means

Identify confidence interval for the slope of a least-squares regression line

Apply logic of significance testing, null and alternative hypotheses; p-values; one- and two-sided tests; concepts of Type I and Type II errors; concept of power

Apply large sample test for a proportion

Apply large sample test for a difference between two proportions

Test for a mean

Test for a difference between two means

Apply Chi-square test for goodness of fit, homogeneity of proportions, and independence

Test for the slope of a least-square regression line

Null hypotheses

Alternative hypotheses

P-values

Type I errors

Type II errors

Goodness of fit

Homogeneity of proportions

Slope of a least-squares regression line