• Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar
The Analysis Factor

The Analysis Factor

Statistical Consulting, Resources, and Statistics Workshops for Researchers

  • Home
  • Our Programs
    • Membership
    • Online Workshops
    • Free Webinars
    • Consulting Services
  • About
    • Our Team
    • Our Core Values
    • Our Privacy Policy
    • Employment
    • Collaborate with Us
  • Statistical Resources
  • Contact
  • Blog
  • Login

Have you Wondered how using SPSS Burns Calories?

by Karen Grace-Martin Leave a Comment

Maybe I’ve noticed it more because I’m getting ready for next week’s SPSS in GLM workshop. Just this week, I’ve had a number of experiences with people’s struggle with SPSS, and GLM in particular.

Number 1: I read this in a technical report by Patrick Burns comparing SPSS to R:

“SPSS is notorious for its attitude of ‘You want to do one of these things. If you don’t understand what the output means, click help and we’ll pop up five lines of mumbo-jumbo that you’re not going to understand either.’ “

And while I still prefer SPSS, I had to laugh because the anonymous person Burns quotes is right on the nose about its documentation.

Number 2: Yesterday, I had a consultation with a PhD student who hired out the entire data analysis for her dissertation. We were going over her output and she said that she started out doing it herself, and was doing okay implementing the analysis, but was completely overwhelmed trying to understand what the output told her, and it made her doubt her intelligence. She was, of course, using GLM.

(An aside rant: It makes me mad that statistics, the field, does this to people. Would you feel bad if you had trouble sailing a boat across an ocean or performing heart surgery after taking a couple classes? No! Doing data analysis on real, messy data isn’t like solving a few text book examples! End of rant).

Number 3: Just this afternoon I had a consultation with another student who was confused about how to enter which variables into which parts of GLM. She’d been stuck for a while, because the directions she’d been following to do a path analysis were all in the context of a regression. And it just isn’t obvious that SPSS means “any continuous predictor” when it says “Covariate.”

Number 4: This morning, I received an email listing some interesting facts, among them: “Banging your head against a wall burns 150 calories an hour.” I’m pretty sure that one is not specifically about SPSS, but it could be.

All of this is exactly why I created the workshop, which starts next Tuesday. Once you decode SPSS’s unique terminology and learn how ANOVA and regression fit into the GLM framework (which isn’t unique to SPSS), it’s actually logical. If you find yourself in the situation of any of these people, join us in the workshop.

Just think, once you’re not struggling with SPSS, you’ll have time for a healthier way to burn 150 calories. 🙂


Bookmark and Share

Getting Started with SPSS
Karen will introduce you to how SPSS is set up, some hidden features to make it easier to use, and some practical tips.

Tagged With: SPSS GLM

Related Posts

  • Centering a Covariate to Improve Interpretability
  • SPSS GLM or Regression? When to use each
  • Dummy Coding in SPSS GLM–More on Fixed Factors, Covariates, and Reference Groups, Part 2
  • Dummy Coding in SPSS GLM–More on Fixed Factors, Covariates, and Reference Groups, Part 1

Reader Interactions

Leave a Reply Cancel 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.

Primary Sidebar

This Month’s Statistically Speaking Live Training

  • Member Training: Analyzing Pre-Post Data

Upcoming Free Webinars

Poisson and Negative Binomial Regression Models for Count Data

Upcoming Workshops

  • Analyzing Count Data: Poisson, Negative Binomial, and Other Essential Models (Jul 2022)
  • Introduction to Generalized Linear Mixed Models (Jul 2022)

Copyright © 2008–2022 The Analysis Factor, LLC. All rights reserved.
877-272-8096   Contact Us

The Analysis Factor uses cookies to ensure that we give you the best experience of our website. If you continue we assume that you consent to receive cookies on all websites from The Analysis Factor.
Continue Privacy Policy
Privacy & Cookies Policy

Privacy Overview

This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may affect your browsing experience.
Necessary
Always Enabled
Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.
Non-necessary
Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.
SAVE & ACCEPT