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Simon Fraser University · Burnaby · life sciences

Simon Fraser University STAT201 — Statistics for the Life Sciences

Use the published life-sciences outline to practise summaries, normal areas, estimation, one-/two-sample calculations and contingency counts.

56 original question families · 168 parameter instances

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Course alignment and coverage

SFU Fall 2026 calendar and the public D100 section outline checked on 25 October 2026. The shared practice does not reproduce that section’s assignments or weekly order.

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.

An original worked example

Find the mean of 2, 4, 6, 8.

Worked solution

Answer: 5

  1. The total is 20.
  2. Mean=20/4=5.
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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.