CSE602 Statistics for Science and Engineering: study guides

Lectures 1–5 rebuilt as concept-ordered pages, with the assignments, the instructor's practice sheets and the midterm review as practice. This was the midterm scope (5 October 2026); the final exam is on 7 December 2026 and covers everything. One A4 formula sheet is allowed, so the skill tested is choosing the right formula and showing every step.

Read in this order. Each page builds on the one before it.

  1. Describing data (Lectures 1–2): data types, mean, median, mode; quartiles, IQR, boxplots and outliers, variance and SD; shape; which chart; frequency tables.
  2. Design, probability and Bayes (Lecture 3, Lecture 4 s18–47): population and sample, study design, correlation; sample spaces, the complement, addition and multiplication rules, counting; conditional probability, total probability, Bayes' rule.
  3. Discrete random variables (Lecture 4 s1–17, Lecture 5 s5–40): pmf and cdf, expected value and variance, skewness; Bernoulli, binomial, multinomial, geometric, Poisson; choosing the model.
  4. The normal curve and the CLT (Lecture 5 s41–130): the normal density, the empirical rule, z-scores and the z-table, critical values; Poisson planning; sampling distributions, the central limit theorem, dependent variables and covariance.

Practice covered: Assignment 1 and 2, the quizzes inside the slides, the Lecture 2 practice-quiz answer key, the midterm practice problems (two sheets, with the instructor's solutions), the midterm review's "try it" blocks, the Lecture 5 practice set, the 30-minute conceptual practice exam and the "at least / at most" notes. Two quartile recipes are in use in this course (interpolation on the slides, medians of the halves in the answer keys); page 1 shows both. Slide errors found are flagged in amber boxes.