This three-day course reviews the standard methods that are used to analyze survey data, beginning with simple methods, such as crosstabulations, and moving toward the advanced, such as logistic regression. Appropriate methods of analysis are discussed for both categorical and continuous data. Also included are discussions of qualitative data analysis and the reporting and presentation of survey results.
This intermediate course is for
- IBM SPSS Statistics users who would like a thorough introduction to the statistical analyses and reporting that can be performed on survey data.
- For users of IBM SPSS Statistics Base, although examples from some additional modules: IBM SPSS Regression Models, IBM SPSS Categories, IBM SPSS Custom Tables, IBM SPSS Data Preparation, IBM SPSS Decision Trees, IBM SPSS Missing Values, and IBM SPSS Complex Samples are presented.
You should have:
- Experience with IBM SPSS Statistics or completion of Introduction to IBM SPSS Statistics course.
Please refer to course overview for description information.
- The Logic of Survey Analysis
- Data checking and data validation
- Data transformations: create new variables
- Testing for Reliability and Validity
- Analyzing Categorical Variables
- Analyzing Interval Variables
- Analyzing Text Data
- Reporting Survey Results for Categorical and Scale Data
- Clustering Respondents
- Multivariate Analysis using Regression Techniques
- Special Issues: Missing Data
- Special Issues: Complex Samples and Sample Weights
- Measuring Change over Time with Surveys
- Decision Tree Analysis