Analyzing Cholesterol Dataset – Part 1

Cholesterol is a very importance substance in our body for digesting foods, producing hormones, and generating Vitamin D. This blog includes an analysis of an cholesterol dataset retrieved from MASH at The University of Sheffield. This dataset contains a mixture of Between-Subjects (type of margarine) as well as within-subjects factors (length of intervention). This leaves us room to make many comparisons but we will begin with the most straightforward comparison of whether participation in these interventions lead to a change in cholesterol.

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Analyzing Cholesterol Dataset – Part 3

So far all of our analyses have asked questions about the manipulation of a single independent variable. The t-test can compare two groups/levels while the ANOVA can ask about the differences between multiple levels. But, what do we do when there is more than one independent variable being manipulated within our experiment? What if we want to know how these factors interact with each other to produce our final result? To demonstrate how you could assess these questions we’ll again go through our Cholesterol.csv dataset.

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