Linear Regression Formula Class 12 ISC Mathematics

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                              Linear Regression 

Formula

Regression Coefficients

The Regression Coefficient of y on x is denoted by \mathbf{{\color{Purple} b_{yx}}}  

b_{yx}=\frac{\sum xy-\frac{1}{n}\sum x\sum y}{\sum x^{2}-\frac{1}{n}(\sum x)^{2}}           (we use this formula when x, y are small numbers)

b_{yx}=\frac{\sum (x-x\bar{})(y-y\bar{})}{\sum (x-x\bar{})^{2}}            (when  x - x\bar{}, y-y\bar{} are small fraction less numbers)

b_{yx}=\frac{\sum uv-\frac{1}{n}\sum u\sum v}{\sum u^{2}-\frac{1}{n}(\sum u)^{2}}          (when  u=x-A,\, v=y-B,\, A \, and\, B are assumed means)

b_{yx}= r.\, \frac{\sigma _{y}}{\sigma _{x}\, }   (where  \sigma _{x} is the standard deviation of x-variate,  \sigma _{y} is the standard deviation of y-variate and r is the coefficient of correlation)

The Regression Coefficient of x on y is denoted by  \mathbf{{\color{Purple} b_{xy}}}

b_{xy}=\frac{\sum xy-\frac{1}{n}\sum x\sum y}{\sum y^{2}-\frac{1}{n}(\sum y)^{2}}    (we use this formula when x, y are small numbers)

b_{xy}=\frac{\sum (x-x\bar{})(y-y\bar{})}{\sum (y-y\bar{})^{2}}  (when  x-x\bar{}, \, y-y\bar{} are small fraction less numbers)

b_{xy}=\frac{\sum uv-\frac{1}{n}\sum u\sum v}{\sum v^{2}-\frac{1}{n}(\sum v)^{2}}   (when u=x-A,\, v=y-BA\, \, and\, \, B  are assumed means)

b_{xy}= r.\, \frac{\sigma _{x}}{\sigma _{y}}  (where \sigma _{x} is the standard deviation of x-variate, \sigma _{y} is the standard deviation of y-variate and r is the coefficient of correlation)

Coefficient of correlation:  \mathbf{{\color{Purple} r(x,y)\, or\, \rho (x,y)}}

r^{2}=b_{yx}.b_{xy}\, \, \, \, and\, \, \, 0\leq r^{2}\leq 1

r=\sqrt{b_{yx}.b_{xy}}\, \, \, and\, \, \, -1\leq r\leq 1

b_{xy},\, b_{yx}\, \, and\, \, \rho (x,y)  are of the same sign.

Equations of two lines of regression

The regression equation of  y  on  x  is      y-y\bar{}=b_{yx}(x-x\bar{})

The regression equation of  x  on  y  is      x-x\bar{}=b_{xy}(y-y\bar{})

The two regression lines intersect at    (x\bar{},y\bar{})

The acute angle θ between two regression lines is given by

tan\, \theta =\left | \frac{1-r^{2}}{b_{xy}+b_{yx}} \right |

If two lines coincide then θ = 0 . \mathrm{So}\, \, \, 1-r^{2}=0\, \, \, and\, \, \, r=\pm 1

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ISC   –   Class 12  –  Mathematics  –  Sem 2  –  2022  – Sample Paper

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