Statistics for the Rest of Us: Mastering the Art of Understanding Data Without Math Skills (Advanced Thinking Skills Book 4)

you know that two phenomena are correlated, but you incorrectly label one as the cause of the other.

Question 4: How is the data presented, and is the presentation misleading in any way? This question gets a whole chapter to itself (Chapter 9) because misleading statistical presentations are, unfortunately, very common in the media.

Think of the display as a puzzle that you are trying to figure out, and ask yourself the following questions: ● What is the title of the graph? ● If there are axes, what does each axis represent, and what is the scale of each axis? ● Can I pick one data point and figure out what it represents? ● What is the shape of the data? Does it show a certain

Pitfall #1: Ignoring scale

Once again, the median might have given you a better sense of how you did in comparison to others, and you might have felt even better about your grade.

1) Strength of association (how strong is the association between the data?) 2) Consistency (will the same results be found if different people replicate the study at different times?) 3) Specificity (how specific is the association?) 4) Temporality (did the effect occur after the cause?) 5) Biological gradient (is there a correlation between the a

Pitfall #2: Looking at the wrong measure of center

This chapter will look at five common pitfalls in statistics and how you, the average consumer, can recognize them.

Pitfall #5: Getting causation backwards