growthmgmt - COURSE SYLLABUS IP&T 650 Quantitative...

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COURSE SYLLABUS Winter Semester 2006 INSTRUCTOR: Dr. Richard R Sudweeks (150-M McKay Bldg, 422-7078) Office Hours: 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 (5 th ed.). Pacific Grove, CA: Duxbury. Course Packet COURSE OBJECTIVES: This course is designed to help students— 1. Understand the reasoning process used in testing research hypotheses and estimating parameters, and use this process to analyze and interpret research findings. 2. Explain what a sampling distribution is and how knowledge of the characteristics of sampling distributions is used in statistical inference. 3. 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. 4. 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. 5. 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. 6. Plan, conduct, and interpret the results of follow-up analyses of statistically significant main effects and interactions. 7. 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. 8. Understand the similarities and differences between multiple regression analysis (MRA), analysis of variance (ANOVA), analysis of covariance (ANCOVA), and the general linear model (GLM). 9. 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 and understanding. 10. Acquire a working knowledge of the vocabulary of modern statistics including conventional
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growthmgmt - COURSE SYLLABUS IP&T 650 Quantitative...

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