The basics of statistics -- How statistics are used -- Key points of statistical analytics -- Mixing up the test -- Knowing the quality of your data -- Modeling risk, measuring samples, and predicting -- Frequency distributions -- Dot plots, bar charts, histograms, frequency polygons -- More ways to see numbers-based data -- The mean, the median, and the mode -- The range and interquartile range -- Mean deviations and variations -- The law of large numbers -- Empirical probability and subjective probability -- Yes or no -- Basics of probability distributions -- Analyzing probability distributions -- The roll of the dice -- Normal distribution -- The central limit theorem -- Outliers on the bell curve -- Limited and unlimited data -- Variance as a measure of risk -- Size matters -- Measuring distribution -- What are confidence intervals? -- Measuring confidence intervals -- The basics of hypothesis testing -- Taking it to the next level -- Measuring large sample population propertions -- The hypothesis test -- Patterns in data -- Predicting the future -- The T-distribution -- Groups of data -- Tests for two populations -- Statistics in academic research -- Getting good data -- A regression example -- What regression data tables tell us -- Determining the causes -- Chi-square distribution -- Anova basics -- Anova at work -- Quantitative research design -- Quality of the data -- Quantity and courcing of the data -- Appropriate survey design -- The ethics of statistics -- Big data, supercomputers, and artificial intelligence.