# Tag Archives: precision

## 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

## Regression Fantasies: Part I

Five 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. … Continue reading

## 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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## 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

## 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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## Grasping at Flaws

Even if you’re not a statistician, you may one day find yourself in the position of reviewing a statistical analysis that was done by someone else. It may be an associate, someone who works for you, or even a competitor. … Continue reading

## Many Paths Lead to Models

If you’ve never created a statistical model before, you might be surprised to find that the process involves a lot more than statistics. It’s like traveling. You don’t start by thinking about your transport, the plane, train, or bus you … 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

## 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