*** 請注意，實習課使用R軟體，時間為週三、五中午任選一時段。***

The goal of this (one-year) course is to teach students the basic concepts of probability and statistics, and its applications in psychology. Topics include random variables and distributions, expectations and variances, sampling distributions, law of large numbers, central limit theorem, hypothesis testing, covariance and correlation, simple and multiple regressions, and analysis of variance. We will also touch issues of power, confidence interval, multiple comparison, and goodness of fit. Some commonly-used tests, such as the chi-square test, t test, F test, and some non-parametric tests, will be introduced. We will use R for simulation and statistical analysis.

The (mandatory) weekly 實習課 is mainly for R and also for problem solving. The 實習課 and homework assignments will count 30% of the final grade. There will be two midterms and one final (total 70% of the final grade).

There are many resources/books on probability and statistics and R, including some on youtube and some pdf files that can be downloaded from the internet. In this course I will cover some of the chapters from the book “Statistical Methods for Psychology” by David Howell.

The tentative schedule is as follows:

Week 1 (Review)
Week 2 – Week 3 Covariance and correlation
Week 4 – Week 8 Least square, simple & multiple regressions (1st midterm in week 6)
Week 9 – Week 12 (Factorial) Analysis of variance (2nd midterm in week 12)
Week 13 – Week 15 Multiple comparison, non-parametric tests
Week 16 – Week 17 Bootstrapping (and others)
Week 18 (Final exam)