Tag Archives: variance

Regression Fantasies

Common Reasons for Doubting a Regression Model Finding a model that fits a set of data is one of the most common goals in data analysis. Least squares regression is the most commonly used tool for achieving this goal. It’s … Continue reading

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Why You Don’t Always Get the Correlation You Expect

If you’ve ever taken a statistics class on correlation, you’ve probably come to expect that a large value for a correlation coefficient, either positive or negative, means that there is a noteworthy relationship between two phenomena. This is not always … Continue reading

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Regression Fantasies: Part II

Six More Reasons for Doubting a Regression Model There are more than a few reasons for being skeptical about a regression model. Some are easy to identify, others are more subtle. Here are six more reasons you might doubt the … Continue reading

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Aphorisms for Data Analysts

An aphorism is a pithy saying that reveals some astute observation or popular notion, whether true or fictitious. “Lies, damn lies, and statistics” you’ve undoubtedly heard. If you’ve taken Stats 101, you probably know that “correlation doesn’t imply causation.” Here … 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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Limits of Confusion

A confidence interval is the numerical interval around the mean of a sample from a population that has a certain confidence of including the mean of the entire population. “Say what?” OK, let’s take it one point at a time. … Continue reading

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Secrets of Good Correlations

If you’ve ever seen a correlation coefficient, you’ve probably looked at the number and wondered, is that good? Is a correlation of -0.73 good but not a correlation of +0.58? Just what is a good correlation and what makes a … Continue reading

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Ten Fatal Flaws in Data Analysis

1. Where’s the Beef? In a way, the worst flaw a data analysis can have is no analysis at all. Instead, you get data lists, sorts and queries, and maybe some simple descriptive statistics but nothing that addresses objectives, answers … 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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