Discovering the Scientist Within

Video: A Simple and Quick Way… (SPSS Tutorials)

This collection of SPSS Video Tutorials from AJ Delgado are exactly as advertised, simple and quick. Here’s just one example, this one focuses on t-tests for independent means. Click here to link to all of his videos. Videos cover all of the key statistics, as well as issues like dealign with skew, and working with […]

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Statistics’ Murky Ethical History

A look back into the historical origins of statistics reveals surprising links to Nazis and eugenics. Check out Aubrey Clayton’s article “How Eugenics Shaped Statistics“ It’s an interesting look at statistics’ historical roots and how it’s tied to modern controversies “It’s no coincidence that the method of significance testing and the reputations of the people

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Detecting Data Fraud: Miles and Miles of Fabrication

Does signing an honesty pledge at the top or bottom of a document increase honesty? That was the question researchers explored in a field study about reporting on a car’s mileage. But the data from that study may be fake. A post from DataColada.org entitled, “Evidence of Fraud in an Influential Field Experiment About Dishonesty”

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Examples: Data Visualization

The Data Visualization Catalogue is a project developed by Severino Ribecca to create a library of different information visualization types. This site features most every type of data visualization you an imagine (including some of the most common in psychology– bar chart). Each contains a description, examples, tools for creation, and a video. You can access the site

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Three Things You Can do to Make Your Data Tables More Visual

Tables that contain a lot of data can be difficult to understand. This article from PolicyViz.com shows a few ways to make that information more manageable by simplifying information, highlighting key pieces, and using the right type of chart. You can find the full article here.

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Resources: Stats of Doom

A comprehensive site created by Dr. Erin Buchanan offering lecture materials and videos for a full range of statistics concepts covered in a basic/introductory course (descriptives, graphs, z-scores, t-tests, ANOVA, correlation, regression, chi-square, etc.). Coverage also includes materials for several statistics packages (e.g., SPSS, JASP, R) Here is a link for a basic course. There

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Article: Self-Report Vs. Behavioral Logs in the Measurement of Digital Media Use

A meta-analysis looking at the correlation (or lack thereof) of self-report measures of media use and measures that track actual behavior. This would be useful to add to a discussion of types of measurement (contrasting the strengths and weaknesses of self-report and behavioral measures. Parry, D.A., Davidson, B.I., Sewall, C.J.R. et al. (2021). A systematic review and

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Article: Misunderstandings about Short Scales and Ways to Address Them

Measures that use fewer than 10 items are considered “short” and pose some challenges, including concerns about validity. This special issue addresses several misconceptions about these scales and offers ways to counteract potential problems. Ziegler, M., Kemper, C. J., & Kruyen, P. (2014). Short scales – Five misunderstandings and ways to overcome them [Editorial]. Journal of

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Example Syllabus – Research Methods (A Workshop Approach)

A sample syllabus for a 200-level research methods course taught by Dr. Jennifer Tomlinson of Colgate University. Her course is innovative and hands-on (exactly what students enjoy and benefit from). As she describes in her syllabus “PSYC 200 is more “workshop” than “class.” Each meeting is designed to engage you in the kinds of puzzle

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Article: Benefits of Mixed Methods (or Why You Should Include Qualitative Methods in Your Research)

This article “The Benefits of a Bigger Toolbox: Mixed Methods in Psychological Research“from the Psi Chi Journal of Psychological Research was written by Debi Brannan Western Oregon University and advocates for integrating quantitative methods with qualitative methods. The article describes: What Are Mixed Methods? Benefits and Challenges of Mixed Methodology, Data Collection Strategies, and the

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