Module 0 prepares you to use R on your own computer. You will learn the difference between R and RStudio, install both programs in the correct order, verify that they are working, install essential packages, import a STATLAB dataset, and run your first commands. If you cannot install software on your device, you will also learn how to use RStudio through Posit Cloud.

Learn how statistical thinking turns questions, data, uncertainty, ethics, and communication into better business decisions.

Plan credible data collection by defining variables, measurement levels, populations, samples, survey designs, data sources, and bias risks.

Choose, build, interpret, and critique visual displays for business and economic data, from dot plots and histograms to dashboards and deceptive graph repair.

Describe center, variability, position, relationships, and distribution shape with numerical evidence.

Quantify uncertainty, calculate event probabilities, revise beliefs when new evidence arrives, and evaluate risk in business decisions.

Model counts, arrivals, successes, finite-population samples, waiting times, and business risk using discrete probability distributions.

Use area, bounded models, normal and inverse-normal reasoning, continuity-corrected approximations, exponential reliability, and transparent triangular scenarios for business decisions.

Connect sample statistics, standard errors, confidence intervals, and estimation.

Test claims about a single population mean, proportion, or process target.

Compare two groups while accounting for variability and study design.

Compare three or more group means using ANOVA logic.

Model the relationship between one predictor and one outcome.

Use several predictors to explain and forecast outcomes responsibly.

Explore trend, seasonality, forecasting, and time-ordered business data.

Analyze categorical counts, independence, and goodness of fit.

Use rank-based and distribution-light methods when assumptions are limited.

Apply statistical tools to defects, processes, control, and improvement.

Use repeated trials to understand uncertainty, risk, and complex decisions.

Learn R from first expressions and data preparation through visualization, forecasting, volatility, financial risk, option pricing, and multivariate time-series analysis using reproducible examples and Canadian data.