PSYC 2021. Statistical methods IDepartment of Psychology
Summer term S1 2018
Tuesday and Thursday, 2:30 - 5:30
General description: This course covers the fundamental concepts and application of descriptive statistics. It provides an introduction to probability and inferential statistics, including hypothesis testing with the normal and t distributions.
Announcements July 17. Here are the final marks for the course, including the final exam. Use the last five digits of your student number to look up your mark in this list.
June 29. Here's an example of how to calculate the sample Pearson correlation.
June 13. The final exam will be on Thursday, July 5, 9:00 am - 12:00 pm, in ACW 005 and ACW 006.
June 11. In Urdan's chapter 8 (t tests), you can skip the box called "Time out for technicality", and you can also skip the discussion of effect sizes in the section on the independent samples t test (e.g., Table 8.2).
May 23. Here is the companion website for Urdan's textbook, with chapter summaries and solutions to the end-of-chapter problems. Urdan also has a separate website with additional problems and solutions.
May 23. Here are some suggestions on how to study.
May 23. Use the missed class form if you miss a test. Provide us with a printed copy of the form with all information filled in.
May 23. For the tests and final exam, you will need a simple calculator with only basic functions (e.g., arithmetic and square roots). Bring a simple calculator, like this, not a scientific calculator, like this.
May 23. If you are interested in following along with the optional R code that I will post from time to time, you can download the R programming language for free from the R website. R is also available on Computing Commons terminals. The R code is completely optional, and will not be covered on tests or the final exam.
| Lecture 1a Introduction||problems||code||slides|
| Lecture 1b Mean and variance||problems||code|
| Lecture 2a Normal distributions; z scores||problems||code|
| Lecture 2b Standard error; statistical significance||problems||code|
| Lecture 3a Effect size; confidence intervals||problems|
| Lecture 4a t tests||problems|
| Lecture 4b Correlation||problems||correction|
| Lecture 5a Regression||problems|
| Lecture 6a The chi-square test||problems||worked example|
Tests Test 1 answers
Test 2 answers