One activity in data analysis that can seem impossible is the quest to find the right analysis. I applaud the conscientiousness and integrity that 
underlies this quest.
The problem: in many data situations there isn’t one right analysis.
Stage 1
The Right Analysis or the Best Analysis? What to Do When You Can’t Run the Ideal Analysis
March 9th, 2020 by Karen Grace-Martin
Member Training: Confusing Statistical Terms
February 28th, 2020 by guest contributer
Learning statistics is difficult enough; throw in some especially confusing terminology and it can feel impossible! There are many ways that statistical language can be confusing.
Some terms mean one thing in the English language, but have another (usually more specific) meaning in statistics. (more…)
Should Confidence Intervals or Tests of Significance be Used?
December 20th, 2019 by Christos Giannoulis
What is a Confidence Interval?
Any sample-based findings used to generalize a population are subject to sampling error. In other words, sample statistics won’t exactly match the population parameters they estimate.
Confusing Statistical Term #8: Odds
December 10th, 2019 by Karen Grace-Martin
Odds is confusing in a different way than some of the other terms in this series.
First, it’s a bit of an abstract concept, which I’ll explain below.
But beyond that, it’s confusing because it is used in everyday English as a synonym for probability, but it’s actually a distinct technical term.
I found this incorrect definition recently in a (non-statistics) book: (more…)
The Wisdom of Asking Silly Statistics Questions
November 12th, 2019 by Karen Grace-Martin
I’ve written about this before–there is just something about statistics that makes people feel…well, not so smart.
This makes people v-e-r-y reluctant to ask questions.
This fact really struck me years and years ago. Hit me hard.
Eight Data Analysis Skills Every Analyst Needs
October 24th, 2019 by Karen Grace-Martin
It’s easy to think that if you just knew statistics better, data analysis wouldn’t be so hard.
It’s true that more statistical knowledge is always helpful. But I’ve found that statistical knowledge is only part of the story.
Another key part is developing data analysis skills. These skills apply to all analyses. It doesn’t matter which statistical method or software you’re using. So even if you never need any statistical analysis harder than a t-test, developing these skills will make your job easier.