Course Syllabus
Course Name: Analysis of Variance (ANOVA) and Computer Applications
Lecturer: Dr. Yonatan Goshen-Gottstein, Tel-Aviv University
Teaching Assistants: Eyal Rosenstreich, Lital Ruderman & Nitzan Shahar
The course will provide a comprehensive review of inferential statistical methods. In
the beginning of the course (2-3 weeks), we will review topics from the Introductionto-Statistical-Methods course, including the following topics:
Sample, Population, Sampling Distribution, Statistic, Parameter
Type I error, Type II error, Power, Significance Level, Rejection Area, 1 and 2 tailed
tests, Normal Distribution, Student’s t distribution, t-test for dependent samples, t-test
for independent samples.
The remainder of the course will be concerned with the theoretical basis, and the
application, of statistical analyses of research designs that manipulate one or more
variables, with more than two levels of manipulation per variable, and investigate
the affects of such manipulations on performance. An emphasis will be placed on
understanding the differences between research designs that manipulate variables
within subject and research designs that manipulate variables between subjects. This
analysis will include a thorough understanding of the factors that influence the
relative statistical power of such designs.
Both one-way ANOVAs and Two-way ANOVAs will be explored, and the extension
of these designs to higher-level designs will also be discussed. To this end, a deep
understanding of the term “interaction” will be undertaken, both at an intuitive level,
and at a formal level. Understanding the theoretical models that underlie each
analysis and the expected values of the Mean Squares will also be part of the course
requirements.
Nonparametric methods will also be examined, with a particular emphasis on the
Freedman test and on the Kruskal-Wallis test.
Finally, contrast-analysis will be studied, for a-priori questions as well as for post-hoc
questions. Post-hoc contrast will include some (or all) of the following: Dunn,
Dunnet, Tukey, Schefe.
Accompanying the course will be a lab, where students will learn to apply the
material that is covered in class to statistical packages. In the academic year 20032004, the package that was used was STATISTICA.