Statistics II is inferential statistics. Inferential statistics allows one to make assumptions about a population based on the results of a sample (subset of the population). Students will first be exposed to probability theory, probability and the normal and binomial distribution. Next, the basic principles underlying the logic of hypothesis testing will be covered. The majority of the course will be spent exposing students to a variety of parametric and nonparametric test; t-test, chi-square, Mann-Whitney U, Wilcoxon T and Spearman rank correlation. Emphasis will be placed on one-way and two-way analysis of variance (independent and repeated measure design) and simple and multiple regression. If time permits, students will get a brief introduction to the Bayesian approach to statistics.
The second major objective is to teach students how to compute statistical problem, interpret the results and to choose the appropriate statistical procedures.
The third objective is to teach students how to use statistics to critically analyze the research of others and to incorporate appropriate techniques when designing their own research projects.
The fourth major objective is to interface statistical analysis and the computer.
The fifth major objective is to strengthen students’ ability to see patterns
emerging from the data and to work smart and efficiently in teams.