# PSY 887: Statistics for Evaluators II

PSY 887

3

### Course Description

Students in this course will learn about inferential statistics and quantitative data analysis in an evaluation context. This course will build upon material from Evaluation Statistics I. The course will cover additional inferential statistics and will introduce students to other statistical tools and data analysis issues, such as handling missing data, using statistics to determine sample size and match comparison groups, and non-parametric statistics. Student will build practical skills in conducting, interpreting and reporting corresponding quantitative data analyses, in SPSS.

By the end of the semester, students will be able to:

1. Apply ethical standards to quantitative data management, analysis, and reporting
2. Understand the logic, limitations, and application of inferential and non-parametric statistics in an evaluation context
3. Identify specific evaluation contexts in which you would use t-tests, ANOVAs, and various non-parametric statistics, and conduct them in SPSS
4. Interpret and report the results of t-tests, ANOVAs, and various non-parametric statistics
5. Calculate the effect size of an intervention
6. Conduct a power analysis to determine sample size or power to detect an intervention effect
7. Address missing and non-normal data
8. Given an evaluation, choose the appropriate statistical analysis and write an analysis plan

PSY 887

3

### Course Description

Students in this course will learn about inferential statistics and quantitative data analysis in an evaluation context. This course will build upon material from Evaluation Statistics I. The course will cover additional inferential statistics and will introduce students to other statistical tools and data analysis issues, such as handling missing data, using statistics to determine sample size and match comparison groups, and non-parametric statistics. Student will build practical skills in conducting, interpreting and reporting corresponding quantitative data analyses, in SPSS.

By the end of the semester, students will be able to:

1. Apply ethical standards to quantitative data management, analysis, and reporting
2. Understand the logic, limitations, and application of inferential and non-parametric statistics in an evaluation context
3. Identify specific evaluation contexts in which you would use t-tests, ANOVAs, and various non-parametric statistics, and conduct them in SPSS
4. Interpret and report the results of t-tests, ANOVAs, and various non-parametric statistics
5. Calculate the effect size of an intervention
6. Conduct a power analysis to determine sample size or power to detect an intervention effect
7. Address missing and non-normal data
8. Given an evaluation, choose the appropriate statistical analysis and write an analysis plan