Antony Lewis

 Early Universe

Statistics for Engineers (from course in 2012)

This course was an introduction to probability and statistics. It covers common discrete and continuous 1-dimensional distributions, and does not require knowledge of fourier transforms or matrix algebra. I did not design the course syllabus, so the choice of topics is not what I would have chosen; however the first sets of notes make up the core part of most basic classical (i.e. mainly frequentist) statistics courses.

Notes cover essentially the same material as the slides, plus additional examples and derivations:

  1. Probability theory
  2. Discreet random variables
  3. Continuous random variables
  4. Statistics and inference
  5. Regression and correlation
  6. Acceptance sampling
  7. Reliability and failure

These use PowerPoint 2010 (which can be viewed with PowerPoint Viewer). Due to animations some of these will not print out very well, but PDFs are also provided in case you can't view PowerPoint. Odd numbered lectures are one hour, even numbered two hours. They include TurningPoint clicker questions.

  1. Lecture 1: Probability theory (PDF)
  2. Lecture 2: Inference and Random Variables (PDF)
  3. Lecture 3: Variances and Binomial distribution (PDF)
  4. Lecture 4: Poisson, PDFs and uniform distribution (PDF)
  5. Lecture 5: Exponential distribution (PDF)
  6. Lecture 6: Normal distribution, central limit theorem (PDF)
  7. Lecture 7 and 8: Estimators, Confidence intervals, t-distribution (PDF)
  8. Lecture 9: Linear regression (PDF)
  9. Lecture 10: Regression, correlation and acceptance sampling (PDF)
  10. Lecture 11: Reliability (PDF)

Statistical tables and formulae

  1. Normal distribution
  2. t-distribution
  3. Acceptance Sampling
  4. Formula sheet