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- Why are regression problems called regression problems?
I was just wondering why regression problems are called "regression" problems What is the story behind the name? One definition for regression: "Relapse to a less perfect or developed state "
- How should outliers be dealt with in linear regression analysis . . .
What statistical tests or rules of thumb can be used as a basis for excluding outliers in linear regression analysis? Are there any special considerations for multilinear regression?
- regression - Converting standardized betas back to original variables . . .
I have a problem where I need to standardize the variables run the (ridge regression) to calculate the ridge estimates of the betas I then need to convert these back to the original variables scale
- regression - When is R squared negative? - Cross Validated
Also, for OLS regression, R^2 is the squared correlation between the predicted and the observed values Hence, it must be non-negative For simple OLS regression with one predictor, this is equivalent to the squared correlation between the predictor and the dependent variable -- again, this must be non-negative
- correlation - What is the difference between linear regression on y . . .
The Pearson correlation coefficient of x and y is the same, whether you compute pearson(x, y) or pearson(y, x) This suggests that doing a linear regression of y given x or x given y should be the
- regression - How to calculate the slope of a line of best fit that . . .
This kind of regression seems to be much more difficult I've read several sources, but the calculus for general quantile regression is going over my head My question is this: How can I calculate the slope of the line of best fit that minimizes L1 error? Some constraints on the answer I am looking for:
- regression - Why do we say the outcome variable is regressed on the . . .
The word "regressed" is used instead of "dependent" because we want to emphasise that we are using a regression technique to represent this dependency between x and y So, this sentence "y is regressed on x" is the short format of: Every predicted y shall "be dependent on" a value of x through a regression technique
- regression - Difference between forecast and prediction . . . - Cross . . .
I was wondering what difference and relation are between forecast and prediction? Especially in time series and regression? For example, am I correct that: In time series, forecasting seems to mea
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