Γλωσσολογικές Αναζητήσεις
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On being misquoted
Although I am not a statistician, through some quirk of Google’s search algorithm, it appears that I have become promoted to the status of a go-to internet expert on Likert scales. This is sometimes awkward, especially when a less-than-perfect blog post is cited in a peer-reviewed publication, but I can live with that. On the other…
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How to summarise Likert scale data using SPSS
If you want to convert multiple Likert item scores in a combined scale, here’s one way to do it using SPSS.
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On Likert scales, levels of measurement and nuanced understandings
I have found it moderately bemusing that my post on Likert scales has received so much attention, considering that I had only intended to mention statistics in passing, in order to make what I perceived to be a more broadly relevant remark. Because my authorial intention was not to educate readers in statistics, the views I expressed in that…
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How to interpret ordinal data
Let’s assume that you have prepared a questionnaire, where respondents had to select among responses ranging from “strongly agree” to “strongly disagree”. For convenience, you have probably followed the established practice of replacing these responses with numbers: “1” for “strongly disagree”, “2” for “agree” and so on. How do you go about analysing these data?
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How to use Likert scales effectively
Many questionnaires use Likert items & scales to elicit information about language teaching and learning. In this post, I discuss how to use these instruments effectively, by looking into the difference between items and scales, and explaining how to analyse the data that they produce.
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Mid-points, central tendencies and statistical significance in Likert scales
When your questionnaire uncovers differences in the ways people have responded, how do you know of these mean something, or if they are due to chance?
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Likert scales: Four things you may not know
If you use quantitative methods in your research project, you may want to read this first.
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On Likert scales, ordinal data and mean values
Some thoughts about how to deal with a common statistical mistake.