OK, so you might have a perfectly clean dataset, your favourite stats program is happy to run analyses on it, but are your data sensible and fit-for-purpose? This course will teach you how to make these checks, including running preliminary analyses on your dataset so you get a good understanding of the story that it’s trying to tell you, even before your ‘real’ analyses have begun. You’ll also learn how to remove outliers from your numerical data with a single step.
At the end of this course you will receive a certificate of completion. Post it to Facebook, your LinkedIn page or print it out and stick it on your wall. Just don’t throw darts at it, ok…
- Over 1 hour of video content!
- Learn how to remove unwanted text data from your dataset
- Learn how to check that your data are sensible and fit-for-purpose
- Learn how to remove outliers with one ninja move
- Excel is used as a learning tool, but the lessons learned are transferable to other media
- Data files are provided for the student to practice with
- Practical learning experience with real data
Section 1 - Introduction to Data Integrity
Section 2 - How to Remove Unwanted Text Entries
Section 3 - How to Check that Your Numerical Data are Sensible
Section 4 - How to Remove Statistical Outliers
Section 5 - Data Integrity Recap