Search Results
| Search type | Search syntax |
|---|---|
| Tags | [tag] |
| Exact | "words here" |
| Author |
user:1234 user:me (yours) |
| Score |
score:3 (3+) score:0 (none) |
| Answers |
answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
| Views | views:250 |
| Code | code:"if (foo != bar)" |
| Sections |
title:apples body:"apples oranges" |
| URL | url:"*.example.com" |
| Saves | in:saves |
| Status |
closed:yes duplicate:no migrated:no wiki:no |
| Types |
is:question is:answer |
| Exclude |
-[tag] -apples |
| For more details on advanced search visit our help page | |
Results tagged with correlation
Search options not deleted
user 35584
A measure of the degree of association among a pair of variables.
-1
votes
Can you calculate $R^2$ from correlation coefficents in multiple linear regression?
If you have both the absolute errors from the regression and the dependent variable values, you can calculate $R^2$ as:
$$1 - ({\rm absolute\ error\ variance} / {\rm dependent\ variable\ variance})$$ …
- 1,216
1
vote
Accepted
Keep eliminating data points until good correlation coefficient is obtained-using Python
This should be similar to what you are looking for:
import numpy, scipy, matplotlib
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
import scipy.stats
import copy
xyDataPairs = …
- 1,216
1
vote
Can a relationship between x and y be modeled, if all the data points fill the area under a ...
I extracted the data points from the visible edge of the scatterplot, and divided the "x" values by 1000 to scale the large values (ignoring what looks like a outlier in the center of the scatterplot) …
- 1,216