How to Interpret the Intercept in 6 Linear Regression Examples

by Karen Grace-Martin

In all linear regression models, the intercept has the same definition: the mean of the response, Y, when all predictors, all X = 0.

But “when all X=0” has different implications, depending on the scale on which each X is measured and on which terms are included in the model.

So let’s specifically discuss the meaning of the intercept in some common models [click to continue…]

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R Is Not So Hard! A Tutorial, Part 4

We will use a data set of counts (atomic disintegration events that take place within a radiation source), taken with a Geiger counter at a nuclear plant. The counts were registered over a 30 second period for a short-lived, man-made radioactive compound.

We read in the data and subtract the background count of 623.4 counts per second in order to obtain the counts that pertain to the radio-active source. Cut and paste the following data into your R workspace.

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How to Get a Code Book from SPSS

And having them all in the variable view window makes things incredibly easy while you’re doing your analysis. But sometimes you need to just print them all out–to create a code book for another analyst or to include in the output you’re sending to a collaborator. Or even just to print them out for yourself for easy reference.

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The Most Difficult Step in Calculating Sample Size Estimates

One of the most difficult steps in calculating sample size estimates is determining the smallest scientifically meaningful effect size.

Here’s the logic:

The power of every significance test is based on four things: the alpha level, the size of the effect, the amount of variation in the data, and the sample size.

The effect size in question will be measured differently, depending on which statistical test you’re performing.

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Strategies for Choosing the Reference Category in Dummy Coding

So it’s best to choose a category that makes interpretation of results easier. Here are a few common options for choosing a category.

Remember, the regression coefficients will give you the difference in means ( and/or slopes if you’ve included an interaction term) between each other category and the reference category.

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Factor Analysis: A Short Introduction, Part 6–Common Problems

In the previous blogs I wrote about the basics of running a factor analysis. While the step-by-step introduction sounds relatively straightforward, real-life factor analysis can become complicated. Here are some of the more common problems researchers encounter and some possible solutions:

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Inter Rater Reliability is one of those statistics I seem to need just seldom enough that I forget all the details and have to look it up every time. Luckily, there are a few really great web sites by experts that explain it (and related concepts) really well, in language that is accessible to non-statisticians. [...]

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Steps to Running Any Statistical Model Questions, Part 1

I would start by putting the literature review before Step 1. You’ll use that to decide on a theoretical research question, as well as ways to operationalize it..

But it will help you other places as well. For example, it helps the sample size calculations to have

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Factor Analysis: A Short Introduction, Part 5–Dropping unimportant variables from your analysis

After you perform your factor analysis, you may wind up with a good solution that has variables that do not load highly on any of your factors. How will you decide which variables you should exclude from your analysis?

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Ten Data Analysis Tips in R answers to webinar questions

David Lillis, guest presenter for Craft of Statistical Analysis Webinar Ten Data Analysis Tips in R, answers your questions.

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