https://github.com/denissimon/linear-regression

Linear regression implementation in R.
https://github.com/denissimon/linear-regression

correlation linear-regression plot prediction r regression

Last synced: about 2 months ago
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Linear regression implementation in R.

• Host: GitHub
• URL: https://github.com/denissimon/linear-regression
• Owner: denissimon
• License: mit
• Created: 2015-04-20T22:52:04.000Z (about 10 years ago)
• Default Branch: master
• Last Pushed: 2016-04-11T12:24:50.000Z (about 9 years ago)
• Last Synced: 2025-01-18T21:18:23.442Z (3 months ago)
• Topics: correlation, linear-regression, plot, prediction, r, regression
• Language: R
• Homepage:
• Size: 44.9 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
Linear Regression

=================

Linear regression implementation in R (for university course).

##### The initial data

|X (key)|Y (value)|

|-------|-------|

|1|2

|2|2

|3|5

|4|4

|5|5

|6|6

|7|6|

We'll first enter the given data in R and create a scatter plot for it. Then we'll craft for our plot the "line of best fit", or the "least squares regression line".

![plot](./img/plot.png)

After that, we'll define the "Pearson's correlation coefficient", commonly called "the correlation coefficient".

![correlation](./img/correlation.png)

The correlation coefficient 0.9053 satisfies the condition -1 <= Rxy <= 1, and indicates a quite strong degree of linear dependence between the given variables.

Finally, we'll predict the value for key = 8.

![plot1](./img/plot1.png)