Tag Archives: measurement

Hellbent on Measurement

Any variable that you record in a dataset will have some scale of measurement. Scales of measurement are, simply put, the ways that associated numbers relate to each other. Scales are properties of numbers, not the objects being measured. You … Continue reading

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Ten Tactics used in the War on Error

Scientists and other theory-driven data analysts focus on eliminating bias and maximizing accuracy so they can find trends and patterns in their data. That’s necessary for any type of data analysis. For statisticians, though, the real enemy in the battle … Continue reading

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It’s All Relative

It’s easy to quote someone out of context to impart a false impression. A movie critic might write a review saying, “This film is a delight compared to a colonoscopy” only to be quoted as saying, “This film is a … Continue reading

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The Data Dozen

Data can take a variety of forms. Some are readily amenable to statistical analysis and some are better suited to other methods of analysis. When you’re trying to solve some problem or research question, though, you need to use whatever … Continue reading

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Six Misconceptions about Statistics You May Get From Stats 101

When you learn new things, you can develop misconceptions. Maybe it’s the result of something you didn’t understand correctly. Maybe it’s the way the instructor explains something. Or maybe, it’s something unspoken, something you assume or infer from what was … Continue reading

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The Santa Claus Strategy

I’m working all out Deadline is near Model’s in doubt Dooming my career. Sta-tis-tics will chill my meltdown. I’m adding new vars Testing them twice Trying to find out which ones’ll suffice Sta-tis-tics will give the lowdown. I see the … Continue reading

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Fifty Ways to Fix your Data

Fifty Ways to Fix your Data (Sing to the tune of “Fifty Ways to Leave Your Lover” by Paul Simon) The problem is all about your scales, she said to me The R-squares will be better if you’ve matched ’em … Continue reading

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Assuming the Worst

If you’re going to be poking around data looking for patterns and anomalies, you should be aware of the fundamental requirements you need to fulfill, or at least assume you fulfill. Consider this. All models make assumptions, an evil necessity … Continue reading

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It’s All in the Technique

You can’t understand your data unless you control extraneous variance attributable to the way you select samples, the way you measure variable values, and any influences of the environment in which you are working. Using the concepts of reference, replication … Continue reading

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The Measure of a Measure

If you can measure a phenomenon, you can analyze the phenomenon. But if you don’t measure the phenomenon accurately and precisely, you won’t be able to analyze the phenomenon accurately and precisely. So in planning a statistical analysis, once you … Continue reading

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