The Analysis Factor
Statistical Consulting, Resources, and Statistics Workshops for Researchers
Interpreting the results of logistic regression can be tricky, even for people who are familiar with performing different kinds of statistical analyses. How do we then share these results with non-researchers in a way that makes sense?
[Read more…] about August Member Training: Explaining Logistic Regression Results to Non-Researchers
The scatterplot is a simple display of the relationship between two, or sometimes three, variables. You have a wide range of options for displaying a scatterplot. In particular, you can control the location, size, shape, and color of the points in your scatterplot.
[Read more…] about Member Training: Practical Suggestions for Improving Your Scatterplots
Good graphs are extremely powerful tools for communicating quantitative information clearly and accurately.
Unfortunately, many of the graphs we see today confuse, mislead, or deceive the reader.
[Read more…] about Member Training: How to Avoid Common Graphical Mistakes
by David Lillis, Ph.D.
Today we see how to set up multiple graphs on the same page. We use the syntax par(mfrow=(A,B)) [Read more…] about R Graphics: Multiple Graphs and par(mfrow=(A,B))
Graphing predicted values from a regression model or means from an ANOVA makes interpretation of results much easier.
Every statistical software will graph predicted values for you. But the more complicated your model, the harder it can be to get the graph you want in the format you want.
Excel isn’t all that useful for estimating the statistics, but it has some very nice features that are useful for doing data analysis, one of which is graphing.
In this webinar, I will demonstrate how to calculate predicted means from a linear and a logistic regression model, then graph them. It will be particularly useful to you if you don’t have a very clear sense of where those predicted values come from.
Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.
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.
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