One of the biggest mistakes made by a business or data analyst is incorrectly interpreting the results of your model; and forming faulty conclusions based on that data. In this video, Matt North shows you how to create a simple correlational matrix in RapidMiner; and gives a specific explanation for the interpretation of the coefficients, including understanding relative strength and statistical significance.
It is important to recognize whether or not there is evidence in the data to support a claim of related items, how to defend those conclusions, and understand when to take the investigation further before making a claim based on a single model's results. To get the most out of this video, you will need a basic understanding of statistics, and know how to compare variables in a data set.
- Learn how to make a simple correlational model in RapidMiner
- Understand how to interpret the meaning of correlation coefficients
- Gain confidence in your ability to explain and defend conclusions formed on the results of a correlation model
Other videos in this series:
How Can I Clean My Data for Use in a Predictive Model?
How Do I Choose the Correct Predictive Model for My Organizational Questions?
Table of contents
- Title: Does Correlation Prove Causation in Predictive Analytics?
- Release date: May 2017
- Publisher(s): Infinite Skills
- ISBN: 9781491990841
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