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Masked Relationships and Multicollinearity
In this video and R workbook I am “playing” with linear regression and I am trying to explain the concept of “controlling” for one variable (this is common in statistics, but I had hard time understanding it until I visualized the problem), masked relationships and multicollinearity.
Playing With Statistics [Part 2]
After a general rant in part 1 I will now try to be more pragmatic. Please note that with these posts I am not trying to impress lab coats, but rather provide an example for my fellow coaches who deal with testing and assessment. Nothing fancy, just down to earth analysis.
It Depends… On the Context
During the 70′ aerobic training was a hype. Everybody was doing it. It made you lean, it made you athletic. It was demanded from you to do it. Afterward, comes the static stretching. Everybody was stretching. Unstable surfaces. Strength training. We can go on and on.
Review 1 – Understanding Shortcomings in Research
When comparing groups of people in the way how they move, we first must make sure we do it in a way the acquired data can actually tell us something meaningful. Understanding and acknowledging some pitfalls when designing, conducting, and interpreting the data is crucial to NOT conclude something misleading or wrong.
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