Data Quality and Validation in IBM SPSS Statistics

Data can pose significant challenges that must be addressed before conducting any analysis. Issues such as missing data, out-of-bounds values, duplicate records, and empty cases must be thoroughly examined and resolved prior to analysis. Verifying data quality is a crucial first step, as good data quality can lead to accurate results. This two-day course will cover:
• Why does data quality and validation matter?
• How to assess data quality
• What are the steps in data validation?
• How to use the Overview tab
• Codebook
• Descriptives
• Graphing options
• Explore
• Data Validation
• Identify duplicate Cases
• Identify unusual cases
• Missing value analysis
Best for: Analysts and researchers who are new to IBM SPSS Statistics or have used the tool before and need to validate data to ensure its quality. On completing this course, you should be confident in leveraging the power of IBM SPSS Statistics to examine and validate your data.

Event Venue

Online