Ah, logarithms. They were frustrating enough back in high school. (If you even got that far in high school math.)
And they haven’t improved with age, now that you can barely remember what you learned in high school.
And yet… they show up so often in data analysis.
If you don’t quite remember what they are and how they work, they can make the statistical methods that use them seem that much more obtuse.
So we’re going to take away that fog of confusion about exponents and logs and how they work.
We’ll explain the logic and algebra of logs in plain English. By the end of this webinar, you’ll intuitively understand:
- What they are, really
- How they work
- Why they are so useful in certain statistical applications
We’ll also review a couple of those applications — log transformations and log and logistic link functions, log-likelihoods — and see how the nature of logs affects interpretations of those statistics.
Note: This webinar is only accessible to members of the Statistically Speaking Membership Program.
Date and Time
Wednesday, January 24, 2018
3 pm – 4:30 pm (US EST) (In a different time zone?)
About the Instructor
Karen Grace-Martin helps statistics practitioners gain an intuitive understanding of how statistics is applied to real data in research studies.
She has guided and trained researchers through their statistical analysis for over 15 years as a statistical consultant at Cornell University and through The Analysis Factor. She has master’s degrees in both applied statistics and social psychology and is an expert in SPSS and SAS.
Not a Member Yet?
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Just head over to our enrollment page to sign up for Statistically Speaking.
You’ll get exclusive access to this month’s webinar, plus live Q&A sessions, a private stats forum, 50+ video recordings of past webinars, and more.
- December 2017 Member Webinar: Model Fit Statistics in Structural Equation Modeling
- November 2017 Member Webinar: A Data Analyst’s Guide to Methods and Tools for Reproducible Research
- October 2017 Member Webinar: A Quick Introduction to Weighting in Complex Samples
- September 2017 Member Webinar: Quantile Regression: Going Beyond the Mean