Does Correlation Prove Causation in Predictive Analytics?

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

Matt North is a professor of Information Systems at Utah Valley University, where he teaches courses on data analytics and database development, administration and security. He holds degrees from BYU, Utah State University and West Virginia University. He served as a Fulbright appointee at Universidad Tecnológica Nacional in Argentina, and is the recipient of the International Association for Computer Information Systems’ Ben Bauman Award for Excellence, and the Gamma Sigma Alpha Outstanding Professor Award. He is the author of numerous articles, published papers and book chapters, in addition to his two books: "Data Mining for the Masses", and "Life Lessons and Leadership".

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?