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University of Ottawa · Ottawa · probability and inference
University of Ottawa MAT1372 / MAT1772 — Elements of Probability and Statistical Inference
Practise distributions, sampling, normal/t inference, chi-square counts and supplied regression lines from the public statistical-inference descriptions.
56 original question families · 168 parameter instances
Practise this course →Course alignment and coverage
Current public English/French course descriptions checked on 25 October 2026. Language-coded counterparts share one independent practice pathway; this is not a transfer-credit or section-equivalence determination. Current weekly section plans remain unverified.
Across this collection: 140 distinct original families and 420 parameter instances. Courses share topic banks; translations and shared mappings are not extra questions.
Supported learning objectives
Descriptive statistics
Calculate means, medians and weighted summaries.
Variance and standard deviation
Distinguish sample and population denominators and scale changes.
Probability
Use complements, independence and conditional probability.
Distributions
Use binomial and normal models under stated assumptions.
Sampling and standard error
Calculate standard errors and sample-size effects.
Confidence intervals for a mean
Calculate known-sigma z intervals; critical values are supplied.
Hypothesis tests for a mean
Calculate a known-sigma z statistic, p-value decision or critical boundary.
Two independent means
Compare independent means with known population standard deviations.
Proportions
Estimate a proportion and calculate a standard error or z interval.
Correlation and regression
Use a supplied least-squares line and interpret residuals and r².
One-sample and paired t
Use sample SD for a one-sample or paired t statistic, degrees of freedom and a margin with supplied t critical value.
Chi-square counts
Compute a simple goodness-of-fit statistic, an expected cell, table degrees of freedom and a decision from a supplied p-value.
Normal areas and quantiles
Use supplied rounded normal tables for complements, central areas, standardization and a percentile.
Independent two-sample Welch inference
Calculate unpooled SE, a Welch t statistic, fractional degrees of freedom and a CI endpoint using a supplied critical value.
What is not covered
Numerical foundations only. No statistical software labs, study-design assessment, graphs, bootstrapping/permutation simulation, ANOVA, multiple regression or regression inference. Critical values/table probabilities are supplied; normal-area exercises use rounded supplied tables. Welch examples are independent normal samples; paired t is a separate objective. Proofs of the LLN/CLT are not included. Do not infer prerequisite eligibility from this map.
An original worked example
Find the mean of 2, 4, 6, 8.
Worked solution
Answer: 5
- The total is 20.
- Mean=20/4=5.
Official course sources
Independent, original, free self-study practice. Not affiliated with or endorsed by this university; these are not official exam questions. Topic alignment does not establish transfer credit, a current section’s weekly syllabus, full course coverage or a grade prediction. Follow your instructor’s rules and use official course materials for assessed work. No live AI chat or paid access is required.