Winter Semester 2006
Dr. Richard R Sudweeks (150-M McKay Bldg, 422-7078)
1:00-4:00 p.m. M & W; 9:00—11:00 a.m. T & Th; and other times by appointment
CLASS MEETING SCHEDULE:
10:30—11:50 a.m., Mondays and Wednesdays, 202 MSRB
Howell, D.C. (2002).
Statistical methods for psychology
ed.). Pacific Grove, CA: Duxbury.
This course is designed to help students—
Understand the reasoning process used in testing research hypotheses and estimating parameters, and
use this process to analyze and interpret research findings.
Explain what a sampling distribution is and how knowledge of the characteristics of sampling
distributions is used in statistical inference.
Distinguish between the roles of research design and statistical analysis in educational research, and
understand the limitations of statistical analysis in compensating for design flaws.
Make defensible choices regarding which statistical procedures should be used to analyze the data in
a given research study consistent with the researcher’s purpose, the design of the study, the nature of
the variables to be analyzed, and other relevant considerations.
Understand the similarities and differences between various types of analysis of variance including
univariate versus multivariate studies; single-factor versus multi-factor designs; completely
randomized, randomized block, and split plot designs; and fixed, random, and mixed models, etc.
Plan, conduct, and interpret the results of follow-up analyses of statistically significant main effects
Understand the difference between statistical significance and practical significance. Use descriptive
statistics, effect size estimates, and measures of the strength of association in addition to the results
of significance tests when interpreting research findings.
Understand the similarities and differences between multiple regression analysis (MRA), analysis of
variance (ANOVA), analysis of covariance (ANCOVA), and the general linear model (GLM).
Use computer software to explore data sets, compute descriptive statistics, estimate parameters, and
test hypotheses to analyze research data.
Read and interpret the resulting printouts with confidence
10. Acquire a working knowledge of the vocabulary of modern statistics including conventional