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(Simple Linear Regression)
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===Simple Linear Regression===
 
https://www.youtube.com/watch?v=nk2CQITm_eo&t=267s
 
  
 
In general, there are 3 main stages in Linear regression:
 
 
: '''1'''. Using '''Least-squares''' to fit a line to the data
 
 
: '''2'''. Calculating <math>R^2</math>
 
 
: '''3'''. Calculating a <math>p-value</math> for <math>R^2</math>
 
 
 
<br />
 
: '''Using Least-squares to fit a line to the data'''
 
<blockquote>
 
[[File:Linear_regression1.png|400px|thumb|right|Takinf from https://www.youtube.com/watch?v=nk2CQITm_eo&t=267s]]
 
 
:* First, draw a line through the data.
 
 
:* Second, calculate the '''Residual sum of squares''': Measure the distance from the line to each data point (residual), square each distance, and then add them up.
 
::: The distance from a line to a data point is called a '''residual'''
 
 
:* Then, we rotate the line a little bit and calculate the RSS. We do this many times.
 
:* ...
 
 
:* Then, the line that represents the linear regression is the one corresponding to the rotation that has the least RSS. The regression equation:
 
 
:: <math> y = a + bx </math>
 
 
:: The equation is composed of 2 parameters:
 
 
::* Slope: <math> b </math>
 
:::  The slope is the amount of change in units of <math>y</math> for each unitchange in <math>x</math>.
 
 
::* The <math>y-axis</math> intercept: <math> a </math>
 
</blockquote>
 
 
 
<br />
 
: '''Using Least-squares to fit a line to the data'''
 
<blockquote>
 
[[File:Linear_regression2.png|600px|thumb|center|Takinf from https://www.youtube.com/watch?v=nk2CQITm_eo&t=267s]]
 
</blockquote>
 
 
 
 
<br />
 
<br />
 
 
<!-- [[File:SimpleLinearRegression.png|350px|thumb|center|]] -->
 
 
[[File:SimpleLinearRegression2.png|600px|center|]]
 
 
 
'''The regression equation:'''
 
<math> y = a + bx </math>
 
 
* Dependent variable: <math> y </math>:
 
* Independent variable: <math> x </math>:
 
* Slope: <math> b = r \frac{S_y}{S_x}</math>
 
: The slope is the amount of change in units of <math>y</math> for each unitchange in <math>x</math>.
 
* <math> y </math> intercept: <math> a = \bar{y} - b\bar{x} </math>:
 
 
 
<br />
 

Latest revision as of 22:25, 23 February 2026