DISCLAIMER
The postings on this blog are my own (except as noted) and do not necessarily represent the positions, strategies or opinions of my current, past, and future employers, cats and other family members, relatives, Facebook friends, real friends, Charlie Sheen, people who sit next to me on public transportation, or myself when I’m in my right mind.-
Recent Posts
Archives
- February 2022
- November 2020
- October 2020
- September 2020
- August 2020
- July 2020
- May 2020
- January 2019
- December 2018
- October 2018
- September 2018
- November 2017
- September 2017
- May 2017
- February 2017
- January 2017
- December 2016
- September 2016
- August 2016
- July 2016
- June 2016
- January 2016
- July 2015
- February 2015
- January 2015
- December 2014
- November 2014
- October 2014
- January 2014
- September 2013
- May 2013
- April 2013
- February 2013
- August 2012
- July 2012
- June 2012
- February 2012
- May 2011
- April 2011
- March 2011
- February 2011
- January 2011
- December 2010
- November 2010
- October 2010
- September 2010
- August 2010
- July 2010
- June 2010
- May 2010
RSS Links
Feedburner
-
Blogroll
Recent Posts from: Random TerraBytes
Meta
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, Non-linear 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, R-square, 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 R-squares will be better if you’ve matched ’em … Continue reading
Posted in Uncategorized
Tagged Box-Cox, 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 do-it-yourselfers tell me that “you need 30 samples for statistical significance.” Maybe that’s … Continue reading