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Modules
Browse the statistics sequence. Completed modules will unlock lessons, quizzes, datasets, and R labs.
Available now
9 of 20 modules are live for the MVP. The remaining modules show the planned course sequence.
ماژول ۰ شما را برای استفاده از R روی رایانه خود آماده میکند. تفاوت R و RStudio را میآموزید، هر دو برنامه را به ترتیب درست نصب و آزمایش میکنید، بستههای ضروری را نصب میکنید، یک مجموعهداده STATLAB را وارد میکنید و نخستین دستورها را اجرا میکنید. اگر نصب نرمافزار ممکن نباشد، استفاده از RStudio در Posit Cloud را نیز میآموزید.
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.
Track module completion and quiz trends as learner progress is connected.
The public course map shows learning modules only. The hidden admin route is intentionally excluded from navigation.