We covered Ch. 15 Ethics in Statistics including the abuse of statistics, ethics in data collection (prisoner studies, the Milgram Experiment, cherry picking data, non-respondent bias, interview bias, volunteer bias), ethics in analysis (falsified data, inappropriate methods, sampling bias), ethics and reporting (conflicts of interest, ghost writing, financial support, reporting non-significant results), and enforcing ethics.

We covered Ch. 13-6 Rank Correlation (Rank correlation test, rank correlation coefficient, causation, correlation), 13-7 Run Test for Randomness (Run, randomness), 14-1 Statistical Process Control (Monitoring process parameters over time to detect changing patterns), 14-2 Control Charts for Variation and Mean (Run chart, statistically stable, variations R Chart, means x-bar chart), 14-3 Control Chart Attributes (p-charts for proportions). We watched a video on the practical applications of data and statistics to the comparison of historical warriors, in this case the apache to the gladiator.

We covered Ch. 11-3 Contingency Tables (Frequency counts of categorical data, test of independence, expected frequency, observed frequency, test of homogeneity), 12-1 Analysis of Variance (ANOVA, F-distribution, not symmetric, values greater than or equal to zero, shape depends on degrees of freedom), 12-2 One-Way ANOVA (Test the equality of three or more population means by analyzing sample variances, F-distribution, avoids Type I Errors), 12-3 Two-Way ANOVA (Interaction between two variables, one changes the other), 13-1 Non-Parametric Statistics (Parametric tests, e.g. parameters, normal distribution not required, can be based on a parameter, less rigid requirements, more data types, qualitative, not as efficient, rank criterion, sign test, e.g. positive and negative signs assigned), 13-2 Sign Test, 13-3 Wilcoxson Signed-Ranks Test for Matched Pairs (Non-parametric test using ranks), 13-4 Wilcoxson Rank-Sum Test for Two Independent Samples.

We covered Ch. 10-4 Prediction Intervals and Variation (Prediction intervals, total deviation, explained deviation, unexplained deviation, coefficient of determination, and the Turing Test for Artificial Intelligence.), 10-5 Multiple Regression (Multiple variation, multiple regression, multiple coefficient of determination, adjusted coefficient of determination.), 11-1 Introduction, and 11-2 Goodness of Fit (Hypothesis test, expected frequency). We also discussed the real-world application of statistics and algorithms to electronic game design.

We covered Ch. 10-1 Review and Preview (Correlation and Regression); 10-2 Correlation including linear correlation, non-linear correlation, the correlation coefficient, r, common correlation errors, 1. Doesn't assume causality, 2. Error arises based on averages, 3. Linearity; and 10-3 Regression including regression lines, marginal change, outliers, residuals, least-squares property, and residual plots.

We covered Ch. 9-1 Review and Preview, 9-2 Two Proportions (Testing two populations and comparing them, hypothesis testing, critical value method, and confidence intervals), 9-3 Two Means: Independent Samples (Cases where the standard deviation is unknown and known), 9-4 Two Dependent Samples (Matched pairs, t-test), and 9-5 Two variances or standard deviations, F-Test). We previewed Ch. 10 Correlation and Regression.

We covered Ch. 8 including Ch. 8-2 Basics of Hypothesis (Hypothesis, tests, one-tailed and two-tailed tests, p-value, t-value, critical value method, wording of the final conclusion, Type I and Type II errors), 8-3 Testing a Claim About a Proportion (z-value), 8-4 Testing a Claim About a Mean (t-value), and 8-5 Testing a Claim About Standard Deviation or Variance (Chi-square).

We covered Ch. 7-1 Estimates and Sample Sizes Basics, 7-2 Estimating Population Proportion, 7-3 Estimating Population Mean, 7-4 Estimating Population Mean Using Confidence Intervals, 8-1 Hypothesis Testing Preview, and 8-2 Basics of Hypothesis Testing (Rare Event Rule, significance level, test statistic, two-tailed test, left-tailed test, right-tailed test, p-value or critical value).

We discussed among other things the following articles and the statistics and statistical thinking the authors employed: Analysis: FBI Director James Comey's 'October Surprise' Doomed Hilary Clinton's Candidacy; Right-Wing Billionaires Have a Project Going to Rewrite Our Constitution, and They Are Shockingly Close to Pulling It Off; Comparing Homegrown Right Wing Extremism To Islamic Extremism.

We discussed the Scientific American article When the Big Lie Meets Big Data. This article describes new technologies using data and analytics (statistics) to manipulate the thinking and behavior of people and how it will be possible in the near future to use artificial intelligence to manage this control.