Public Professional Training Courses | 2 Day Course

Data Quality and Validation in IBM SPSS Statistics

Discover the power of IBM SPSS Statistics. Our Version 1 SPSS experts offer comprehensive Statistics training with express and longer courses. This training is more than just a course; it’s a key to unlocking your potential. It’s a tool that can be tailored to your individual or group needs, enhancing your skills and expanding your knowledge of statistical analysis and machine learning methods. By investing in this training, you are maximising your usage of this powerful tool.

Data may pose significant challenges that need to 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 poor data quality can lead to misleading results.

This two-day course will cover the following topics:

  • 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

On completing this course, you will be equipped with the skills and knowledge to confidently check data quality and run data validation tools in IBM SPSS Statistics. Your investment in this course will yield tangible results in your data analysis capabilities.

Course attendees will receive a course manual and sample data files after completing the course.

Best for: Analysts and researchers who are familiar with SPSS and want to expand their knowledge by learning the most widely used advanced statistical analysis techniques.

Course Duration

2 Days

Experience Level

Entry Level to Mid

Upcoming Dates

6th January 2025 (2 Days)

Online

4th March 2025 (2 Days)

Online

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Version 1’s SPSS Team offers a wide range of training courses for statistical analysis, survey research and data mining/predictive analytics.

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