Please check this website periodically for announcements regarding PSYCH 710.
"Without replication, all results should be taken as preliminary." -- Gary Marcus, Cleaning Up Science, The New Yorker News Desk, December 24, 2012
- The course outline can be obtained here.
- Lectures will be held onn Tuesday afternoon, 3:30-5:30 PM, in room ABB-270. The first lecture is on September 4th.
- You will be assigned to one of two statistics labs that will be held on Thursdays, 10:30AM-12:30PM or 12:30PM-2:30PM, in PC-154. The first labs will be on September 13th.
- The textbook for this course, Designing Experiments and Analyzing Data: A model comparison perspective (3rd ed., Maxwell & Delaney), can be obtained in the McMaster bookstore.
- The statistical softwared used in this course is R, which can be downloaded here.
- Office Hour:
- TAs will hold weekly office hours at a time that will be announced shortly.
- You can arrange to meet with me by sending me an email (with PSYCH 710 in the subject line).
- UPDATES:
- [05-Dec 10:05 AM] The final review session will be held on Tuesday December 11, 3:30-5:30 PM, in PC-154 (computer cluster).
- [30-Nov 8:30 AM] The answers to the within-subjects ANOVA practice questions are here.
- [04-Dec 10:30 AM] Please take a few minutes to evaluate your TAs. You can fill out and submit your evaluations here.
- [30-Nov 8:30 AM] Some practice questions for within-subjects ANOVAs can be found here. We will review the answers in class next Tuesday.
- [19-Nov 11:20 AM] You can pick up your 2nd tests in the Psychology main office.
- [06-Nov 10:00 AM] The answer key for the practice questions on factorial ANOVA is here.
- [04-Nov 7:15 PM] A small set of practice questions for factorial ANOVA can be found here. We will go over the answers in class on Tuesday.
- [19-Oct 2:25 PM] Updated my slides for linear contrasts.
- [03-Oct 10:35 AM] In class yesterday we discussed the relation between two-sided and one-sided confidence intervals. In your lab, it was pointed out that a the t values that were used to construct two- and one-sided confidence intervals had to be adjusted to have the same coverage. For example, simply dropping one side of a two-sided 95% confidence interval yields a 97.5% one-sided confidence interval, so we have to adjust the t get a 95% one-sided CI. Note that R's t.test command does this adjustment for you automatically. You can see this for yourself by comparing the two-sided and one-sided intervals in the t tests performed in the first set of practice questions. All of the intervals have 95% coverage, but the "edges" of the two- and one-sided intervals differ.
- [03-Oct 10:30 AM] I updated my notes for chapter 3 to include the reference to the pwr.anova.test function (page 15) that I used in my slides.
- [02-Oct 11:05 AM] The answers for the first set of practice questions are here.
- [29-Sep 7:55 AM] The first set of practice questions (t tests and 1-way anova) are posted here.
- [28-Sep 11:55 AM] I posted the answer key for lab 3. I will upload practice exam questions later this afternoon.
- [18-Sep 2:50 PM] The answer key for lab 1 is posted here.
- [18-Sep 2:48 PM] An R script illustrating t tests and equivalence tests is here.
- [06-Sep 9:46 AM] There is NO stats lab today. The labs will start next week. Sorry for the confusion.
- [05-Sep 8:15 AM] I uploaded the course outline.
- [30-Aug 11:55 AM] Periodic announcements and updates will appear here throughout the term.
- Review of basic aspects of descriptive and inferential statistics: PSYCH 710 assumes that students have taken an undergraduate course in inferential statistics. Some of the important concepts taught in such a course are reviewed in the following documents.
- Maxwell & Delaney's basic statistics tutorial. This file also can be found on the CD that came with the textbook.
- PJB's notes on z and t-tests [updated 10:55AM, September 9, 2014]
- Instructions for getting the data sets that accompany A Beginner's Guide to R can be found here.
- A brief handout describing how to extract subsets of data from R variables can be found here.
- Here is a very useful discussion about using colourmaps to visualize data.
- The following items review important issues regarding significance testing:
- The ASA's Statement on p-Values
- Goodman, S (2008). A Dirty Dozen: Twelve P-Value Misconceptions, Seminars in Hematology, 45(3), 135-40.
- Cohen, J (1994). The earth is round (p<.05). American Psychologist, 49(12), pp. 997-1003.
- Lykken, D.T. (1968). Statistical significance in psychological research. Psychological Bulletin, 70(3), pp. 151-159.
- Gelman, A (2013). P values and statistical practice. Epidemiology, 24(1), 69-72.
- Loftus, G. (1996). Psychology will be a much better science when we change the way we analyze data. Current Directions in Psychological Science, 5, 161-71.
- Krantz, D (1999). The null hypothesis testing controversy in Psychology. J. American Statistical Association, 44(448), 1372-81.
- Significant
- Please don't ever try to boost your results.
- Interesting websites that deal with statistical issues
- Course notes on chapters from the textbook: (N.B. These notes may be modified during the term.)
- If you need a review of basic statistics, please read my notes on testing differences between means. [updated 11-Sep 5:30 PM]
- I created two R scripts that illustrate the central limit theorem. The scripts show the distribution of sample means when the scores are drawn from a uniform distribution and a log-normal distribution. To use the scripts you must download them to your computer and then execute them using R's source command. More detailed instructions, as well as a description of what you will see when the script executes, are provided in the script files (which can be read with any text editor or word processor). If you do open/edit the files with a word processor, make sure to save them as ascii text files.
- R tutorial for conducting t tests for paired and independent samples.
- Chapter 3 (One-way Between-Subjects ANOVA) [updated 03-Oct-2018 10:30 AM]
- A script that contains the R commands that I used in class can be obtained here here.
- A handout that provides an example of how to do a one-way ANOVA in R can be found here.
- Several 1-way ANOVA practice questions can be found here.
- Chapter 4 (Individual Comparisons Among Means)
- Chapter 5 (Multiple Comparisons of Means)
- Illustrations of potential problems associated with doing multiple comparisons can be found here, here, and here.
- Chapter 6 (Trend Analyses) [updated on 28-Sept-2015, 4:00 PM]
- Chapter 7 (Between-Subjects Factorial Designs)
- Here is a paper describing common erroneous analyses of interactions.
- Chapter 9 (Designs with Covariates)
- Chapter 10 (Designs With Random or Nested Factors) [updated on 2-Dec-2014, 7:45 PM]
- Chapter 11 (One-way Within-Subjects Designs: Univariate Approach)
- Chapter 12 (Higher-Order Designs with Within-Subjects Factors)