### Psych 341: Statistics II

Instructor: Gary C. Ramseyer
Office: 451 Degarmo Hall
Phone: 309-438-7939
Email: gcramsey@ilstu.edu
Web Site: http://www.ilstu.edu/~gcramsey

TEXT:
Howell, D.C. (1997). Statistical Methods for Psychology (4th ed). Belmont, CA: Duxbury.

OBJECTIVES:
This course is designed to enhance the student's basic knowledge and understanding of the statistical method as it pertains to hypothesis testing. Several fundamental reoccurring themes are emphasized. At the end of the semester a student should be able to read and intelligently assess the majority of the research literature in his or her own particular field. Also, at the end of the semester a student should be able to apply the statistical techniques presented in the course to his or her own research projects.

METHOD OF INSTRUCTION:
A combination of lecture and discussion is employed. Class notes are presented in detail on the blackboard and through dittoed and mimeographed handouts. Actually, a student is encouraged to write his or her own textbook from the presented materials. Practice exercises are assigned at the end of each unit and typically some class time is devoted to the solutions of each set (these are not handed in or graded). Following discussion of the practice exercises, one or two additional exercises are assigned and these are handed in and graded. Students are encouraged at all times during the course to participate in discussion, to ask questions, or to simply release their pent up aggression against statistics (please frown, smile or show other emotions). The instructor endeavors to promote a relaxed, free-wheeling atmosphere in the classroom.

REQUIREMENT:
A ten-digit scientific calculator.

EVALUATION:

TOPICS:

1. Sampling error theory and its applications.
2. Simple hypothesis testing and the power of the test.
3. Interval estimation.
4. The t-statistic and some of its applications.
5. The continuous and frequency chi-square statistics and their applications.
6. The F-statistic.
7. Analysis of variance (ANOVA): the simple one-way design and multiple comparisons.
8. Selected non-parametric statistics.
9. Two-way analysis of variance.
10. Regression analysis with two predictor variables.