Descriptive statistics
Bivariate Correlation and Regression
Testing hypotheses:
One group Z and t
F-test for two variances 
t-test, One-factor ANOVA
Chi square and non-parametric correlations
Students should be able to:
• Obtain means, variances, covariances, and pearson correlations conceptually, without using formulas, notes or computer programs.
• Convert deviation scores to standard Z scores without using notes/formulas.
• Obtain and interpret descriptive statistics and measures of relative standing from SPSS
• Do t-test and simple ANOVA with and without using SPSS,
• Test hypotheses and make verbal conclusions based on obtained SPSS results 

Factorial ANOVA
Pre-planned and post-hoc tests 
ANCOVA, 
Multiple regression/prediction
Regression diagnostics
A brief introduction to multivariate methods

Students should be able to:

Partition variances into indicators of effect (treatment, regression) and error (within, residual) for ANOVA and multiple regression without using notes or formulas

Test the significance of R-squared and R-squared-change

Test hypotheses based on comparing multiple regression models without using notes

Perform univariate post-hoc and pre-planned tests without using SPSS

Use SPSS to test hypotheses using ANOVA, ANCOVA, as well as follow-up tests

Do ANOVA/ANCOVA through multiple regression analysis, and interpret all results 

Obtain all information for model-testing from SPSS/SAS multiple regression procedures

coding/digitizing
a-priori-themes analysis
emerging themes analysis
pattern finding
computerized data analysis in qualitative research (QUALPro, NU-Dist, etc.)

Students should be able to:

Design qualitative data collection and analysis procedures.

Code and prepare data for content-analysis.

Content analyze qualitative information by hand and also by computer programs.

Present the results of qualitative analysis 

MANOVA
Multivariate regression
Factor Analysis
Discriminant function analysis
Canonical correlation and regression 

Students should be able to:
 

Using SPSS or SAS, test hypotheses involving multivariate group designs through MANOVA.

Using SPSS or SAS perform and interpret multivariate regression analysis and canonical correlation.

Using SPSS or SAS, perform factor analysis, modify/rotate factors, interpret, and make conclusions

Using SPSS or SAS, perform discriminant function analysis, re-classify, and make conclusions