PSY 523
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Expected Prior Knowledge:

• identify level of measurement of research variables
• identify independent and dependent variables
• explain basic concepts of analysis of variance
• compute and interpret a correlation

Specific Course Objectives:

After studying each of the following sections, students should be able to:

• Multiple linear regression
  • compute (using Excel) and interpret sums of squares, sum of cross products, covariance, correlation, and regression parameters, use SPSS to run correlations and simple linear regression
  • use SPSS to compute and interpret standardized and raw regression coefficients, manipulate matrices, solve multiple regression problems with matrices, evaluate the fit of a regression model, write a journal quality results and discussion section incorporating these topics

• Assumptions & testing residuals - explain and test the assumptions underlying regression and multivariate statistics
• Partial & semipartial correlations - compute and interpret partial and semipartial correlations, derive equations from Venn diagrams, create Venn diagrams from equations, compare and contrast partial, semipartial, zero-order, and multiple correlations, write a journal quality results and discussion section incorporating partial & semipartial correlations
  • Suppression - identify and explain the three type of suppression
  • Simultaneous & stepwise regression - compare and contrast these approaches and determine the appropriate approach for different research questions
  • Sets and hierarchical regression - conduct a multiple regression (using SPSS) with sets and an hierarchical approach, determine the appropriate ordering of sets in an hierarchical regression for different research questions, write a journal quality results and discussion section for hierarchical multiple regression

• Interactions - create interaction terms, select the appropriate approach for analyzing interactions, conduct and interpret a multiple regression with interaction terms, graph interactions, compute and interpret separate regression equations for various levels of an independent variable, write a journal quality results and discussion sections for a multiple regression with interactions
• Categorical variables & coding - select appropriate coding methods, explain and interpret the meaning of regression coefficients with coded vectors, conduct a regression using coded variables, write a journal quality results and discussion section incorporating categorical and coded variables

• Canonical Correlation - determine when canonical correlation is appropriate, conduct and interpret a canonical correlation using SPSS, write a journal quality results and discussion section for a canonical correlation
• Analysis of Covariance - explain the assumptions of ANCOVA, compare ANCOVA and repeated measures designs, compare ANCOVA and multiple regression, determine when ANCOVA is appropriate, conduct and interpret an ANCOVA using SPSS, write a journal quality results and discussion section for an ANCOVA

• Multivariate Analysis of Variance - determine when MANOVA is appropriate, conduct and interpret a MANOVA using SPSS, write a journal quality results and discussion section for a MANOVA
  • Discriminant Analysis - determine when discriminant analysis is appropriate, conduct and interpret a discriminant analysis using SPSS, write a journal quality results and discussion section for a discriminant analysis
  • Logistic Regression - determine when logistic regression analysis is appropriate, conduct and interpret a logistic regression using SPSS, write a journal quality results and discussion section for a logistic regression

Course Evaluation:

• Mini-papers (5)   45%
• Tests (2)    50%
• Non-graded Work   5%

Examinations:

• First Test - Tuesday, 5-5
• Second Test - Monday, 6-8, 10:30 am
• Last Mini-paper due - Thursday, 6-4

It is also extremely helpful to read results and discussion sections from journals in your field that use the techniques covered in this class.  Please share the articles you have found with your classmate by posting references to the articles on the course web-site.

Computer Support at PSU

Getting an email account at PSU.

• PSU keeps all student email accounts on a computer called 'Odin'. To sign up for you personal Odin account go to Shattuck Hall Room 120 (see map.) Bring your PSU ID or proof of admittance such as your class list.

Free workshops:

• PSU holds free workshops on popular software such as browsing the Internet using Netscape, Word processing with Microsoft Word, and how to use your Odin email account. Contact the OIT help desk at 725-HELP for the workshop schedule.

PSU Computer Labs

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Contact Nancy Perrin. Site constructed by PSU's FIPSE Project coordinated by Nancy Perrin and John Rueter, © 1998. Last updated on June 23, 1998. For more, see the About Page.