Series on Easy-to-Confuse Statistical Concepts

There are many statistical concepts that are easy to confuse.

Sometimes the problem is the terminology. We have a whole series of articles on Confusing Statistical Terms.

But in these cases, it’s the concepts themselves. Similar, but distinct concepts that are easy to confuse.

Some of these are quite high-level, and others are fundamental. For each article, I’ve noted the Stage of Statistical Skill at which you’d encounter it.

So in this series of articles, I hope to disentangle some of those similar, but distinct concepts in an intuitive way.

Stage 1 Statistical Concepts

The Difference Between:

Stage 2 Statistical Concepts

The Difference Between:

Stage 3 Statistical Concepts

The Difference Between:

Are there concepts you get mixed up? Please leave it in the comments and I’ll add to my list.

Reader Interactions


  1. Sriram Ramachandran says

    There is also lot of confusion between odds ratio and hazard ratio(cox regression survival analysis), Correlation (scatterplot)and Agreement(blant-altman plot) you can add to your list

  2. William Peck says

    just what the Stats doctor ordered! Very good, excited to review.

    I mostly figured out correlation (i.e., Pearson’s correlation, both in Excel and SPSS, and a friend corroborated my work in Stata. Correlation is relatively easy to understand, even to the layman.

    But Regression always conjures up a blank cloud over my head. It’s now anything a layman can understand imo. Plus it just doesn’t click with me. Although I have done Logistic Regression in SPSS to good effect, to identify a cohort of college students coming straight from h.s. who are similar to those who go to a college prep school, then we compare how well the two groups did, in terms of GPA, Calculus, Chemistry, Physics, and English.

    but Regression in general doesn’t resonate with me … so if you have anything on that, send the link.

    Thank you!

    • Karen Grace-Martin says

      Hi William,

      We have a lot of resources on regression, though I’m not sure much on the fundamental idea of what it is. 🙂

      At it’s most basic, a linear regression is simply the equation of the line that best describes the linear relationship. It is very related to correlation, in that it’s simply the line that best describes the linear relationship in the correlation. Where it gets really complicated is if you have more than one predictor.

      As I write out this “simple explanation” I realize I’m going to need to write something longer. Keep your eye out for a new article. 🙂

Leave a Reply

Your email address will not be published. Required fields are marked *

Please note that, due to the large number of comments submitted, any questions on problems related to a personal study/project will not be answered. We suggest joining Statistically Speaking, where you have access to a private forum and more resources 24/7.