Master ANOVA, multiple regression, logistic models, forecasting, and simulation — the advanced toolkit for data-driven business decisions.
Work through each chapter in order. Each one builds on the last.
Review two-sample tests, understand their limitations, and discover why ANOVA is needed for comparing three or more groups.
🕑 ~50 min readBuild the ANOVA table from scratch, compute F-statistics, and make decisions using the F-distribution.
🕑 ~55 min readIdentify which groups differ with Tukey HSD and Bonferroni, and measure practical significance with eta-squared.
🕑 ~45 min readExtend simple regression to multiple predictors, interpret coefficients, and evaluate model fit with adjusted R-squared.
🕑 ~60 min readEvaluate regression assumptions, detect influential points, and choose the best model using information criteria.
🕑 ~50 min readModel binary outcomes, interpret odds ratios, and apply logistic regression to business classification problems.
🕑 ~45 min readDecompose time series, apply moving averages and exponential smoothing, and build forecasts for business planning.
🕑 ~55 min readUse random sampling to model uncertainty, estimate probabilities, and support risk-aware decision-making.
🕑 ~50 min readBy the end of this course, you will be able to:
Conduct one-way ANOVA to compare three or more group means and follow up with post-hoc tests to identify which groups differ.
Build and interpret multiple regression models with several predictors, and evaluate fit using adjusted R-squared.
Apply logistic regression to binary business outcomes and interpret odds ratios for decision-making.
Decompose time series data, apply smoothing techniques, and generate business forecasts with confidence intervals.
Design and run Monte Carlo simulations to model uncertainty and support risk-aware strategic decisions.
What you need before starting this course.
This course assumes familiarity with hypothesis testing, confidence intervals, simple linear regression, and the basics of probability distributions covered in STATS200. You should be comfortable with t-tests, p-values, and interpreting regression output.
Practice what you learn with these interactive stats games.
Test whether group means differ using ANOVA. Build the F-statistic and make the call under time pressure.
Play Now →Analyze residual plots, detect multicollinearity, and pick the best regression model from the clues.
Play Now →Run simulations to estimate probabilities and expected values. See how sample size drives accuracy.
Play Now →Compete to produce the most accurate forecasts using moving averages, smoothing, and trend decomposition.
Play Now →