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Recent Posts from: Random TerraBytes
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.About pictures
I decided to start using other peoples' pictures of cats for my blogs for a variety of reasons. It's hard enough for me to get a good picture of my cats let alone one that might go with what I'm writing. I also thought it would improve my blogs by having a much greater variety of images to choose from. I understand enough about creativity and art and photography to know they are both a talent and a skill that should be recognized. I want to give proper attribution to the creators of the images I use in my blogs, but there is a problem. Virtually every image I want to use appears in more than one place on the Internet. I thought using tineye.com, a search site for finding URLs of uploaded images, would help. In fact, I found the opposite. Some of the images I've searched for are found on a hundred different sites, making it impossible to identify the original. So, if I can't identify the original, I'll cite the site I got the image from or if it's an image I don't have a URL for, I'll cite the site that tineye.com indicates has the image that most closely matches the image I use. If I use an image that you created and I didn’t give you credit, I'm sorry. Let me know and I’ll fix the citation or remove the image.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, 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
4 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
7 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