For all practical purposes. Statistics Program 8 focuses on exploratory data analysis, emphasizing that the human eye and brain are the best known devices to see and recognize patterns. Introduces histograms, medians, quartiles, scatterplots and boxplots. Program 9 analyzes how we can predict long-term patterns of chance events by looking at the operation of a gambling casino. Introduces elementary probability concepts along with an analysis of normal curves, standard deviation and expected value.

Inference for one mean Covers inference about the mean of a single distribution, with emphasis on paired samples. Also covers the "t" confidence interval and test.

Describing distributions Deals with numerical measures of specific aspects of distribution, such as center (mean, median), spread (percentiles, boxplots, standard deviation), and resistance.

Comparing two means Deals with two-sample t confidence intervals and tests for comparing means.

Binomial distributions Deals with the law of large numbers and presents additional rules for means and variances of random variables. Also covers binomial distributions for sample counts.

The Question of causation Deals with the association between categorical variables displayed in a two-way table. Illustrates Simpson's paradox, the numerous relations among variables that underlie an observed association, and how evidence of causation is obtained. Examples siting the relationship between smoking and lung cancer are used.

Inference for two-way tables Covers the chi-square test for independence/equal distributions in two-way tables.

Inference for proportions Covers confidence intervals and tests for a single proportion and for comparing proportions based on paired and independent samples. Examples are chosen from government estimates on unemployment.

Significance tests Deals with the reasoning behind significance tests, null and alternative hypotheses and P-values, and cautions on the limited information provided by tests. A hiring discrimination case is used as an example.

The Sample mean and control charts Covers the sampling distribution of x̄, the central limit theorem, x̄ control charts, and statistical process control. Examples are chosen from the game of Roulette and business applications.