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Concordia University · Montréal · selected course foundations
Concordia University STAT250 — Statistics
Practise a small computational starting point for interval estimation and testing before Concordia’s theoretical statistics. Likelihood, optimal tests and mathematical arguments remain outside these forms.
24 original question families · 72 parameter instances
Practise this course →Course alignment and coverage
Current catalogue and public Fall 2026 outline checked 25 October 2026. These original exercises cover selected stated topics, not the section’s assignments, examination or weekly order.
Across this collection: 156 distinct original families and 468 parameter instances. Courses share topic banks; translations and shared mappings are not extra questions.
Supported learning objectives
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.
Proportions
Estimate a proportion and calculate a standard error or z interval.
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.
Normal areas and quantiles
Use supplied rounded normal tables for complements, central areas, standardization and a percentile.
What is not covered
Numerical estimation/test exercises only, with supplied critical values. No likelihood estimation, Neyman–Pearson lemma, likelihood-ratio tests, estimator theory, proofs or full theoretical-statistics coverage. STAT249 is a prerequisite; MAST219 is a co-/prerequisite.
An original worked example
An independent random sample has n=16 from a population with SD 12. Find SE of the sample mean.
Worked solution
Answer: 3
- SE=12/sqrt(16).
- The standard error is 3, not the population SD.
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.