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Tag Archives: correlation coefficient
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
Posted in Uncategorized
Tagged accuracy, autocorrelation, correlation coefficient, dependent variable, heteroscedasticity, intercept, misspecification, model, multicollinearity, Nonlinear relationships, number of samples, outliers, overfitting, precision, regression, sample size, samples, software, standardization, statistical analysis, statistical tests, statistics, stats with cats, stepwise regression, trend, variability, variance
13 Comments
How to Tell if Correlation Implies Causation
You’ve probably heard the admonition: Correlation Does Not Imply Causation. Everyone agrees that correlation is not the same as causation. However, those two words — correlation and causation — have generated quite a bit of discussion. Why Causality Matters No … Continue reading
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
Posted in Uncategorized
Tagged cats, causation, correlation, correlation coefficient, relationships, spurious correlations, statistics, stats with cats, variables, variance
8 Comments
O.U..T…L….I……E……..R………………..S
Datasets may contain values that is far greater (or less) than, or doesn’t display the same characteristics as the other values. If the influential observation is not representative of the population being sampled, it is called an outlier. Deciding what to do with outliers can be a challenge for data analysts. Continue reading
Posted in Uncategorized
Tagged anomaly, bias, cats, correlation coefficient, diagrams, influential observations, outlier
8 Comments
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
Posted in Uncategorized
Tagged accuracy, cats, client, correlation coefficient, data scrubbing, information, objectives, precision, samples, statistical analysis, statistics, stats with cats, variability, variance
1 Comment
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
Posted in Uncategorized
Tagged cats, correlation coefficient, criticism, dependent variable, jargon, math, mean, Normal distribution, number of samples, objectives, population, precision, probability, rule of thumb, sample size, samples, software, statistical analysis, statistical tests, statistics, stats with cats, uncertainty, variability
8 Comments
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
Posted in Uncategorized
Tagged cats, coefficient of determination, correlation coefficient, measurement scales, multiple correlation, number of samples, objectives, outliers, partial correlation, Rsquare, sample size, shrunken correlation, software, statistical analysis, statistical tests, statistics, stats with cats, trend, variance
36 Comments
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 Rsquares will be better if you’ve matched ’em … Continue reading
Posted in Uncategorized
Tagged BoxCox, cats, correlation coefficient, differencing, information, lags, math, measurement, measurement scales, model, Normal distribution, recoding, rescaling, smoothing, software, standardization, statistical analysis, statistics, stats with cats, transformations, trend
31 Comments
30 Samples. Standard, Suggestion, or Superstition?
If you’ve ever taken any applied statistics courses in college, you may have been exposed to the mystique of 30 samples. Too many times I’ve heard statistician doityourselfers tell me that “you need 30 samples for statistical significance.” Maybe that’s … Continue reading