Q. 4.141 - Elementary Statistics

Question

Determine the linear correlation coefficient by formula and definition.

Step-by-Step Solution

Answer

a)The linear coefficient by the definition $=0.756$

b) The linear coefficient by the formula $=0.756$

Part (a) Step 1: Given Information

To find the linear correlation coefficient by the definition. 

Part (a) Step 2: Explanation

The linear correlation coefficient using the definition is

$r=\frac{\frac{1}{n-1}\sum \left(x_i-\overline{x}\right)\left(y_i-\overline{y}\right)}{{\sigma }_x{\sigma }_y}$

The standard deviations are

$$\begin{gathered} {\sigma }_x=\sqrt{\frac{1}{n-1}\sum (x-\overline{x}{)}^2}, \\ {\sigma }_y=\sqrt{\frac{1}{n-1}\sum (y-\overline{y}{)}^2} \end{gathered}$$

Calculation:

Make a table of values

Find the standard deviations

$$\begin{gathered} {\sigma }_x=\sqrt{\frac{1}{n-1}\sum (x-\overline{x}{)}^2} \\ =\sqrt{\frac{1}{3-1}\left(2\right)} \\ =1 \end{gathered}$$

$$\begin{gathered} {\sigma }_y=\sqrt{\frac{1}{n-1}\sum (y-\overline{y}{)}^2} \\ =\sqrt{\frac{1}{3-1}\left(14\right)} \\ =2.646 \end{gathered}$$

Find the correlation coefficient

$$\begin{gathered} r=\frac{\frac{1}{n-1}\sum \left(x_i-\overline{x}\right)\left(y_i-\overline{y}\right)}{{\sigma }_x{\sigma }_y} \\ =\frac{\frac{1}{3-1}\left(4\right)}{\left(1\right)(2.646)} \end{gathered}$$

Hence,

The linear coefficient by the definition $=0.756$

Part (b) Step 1: Given Information

To find the linear correlation coefficient by the formula. 

Part (b) Step 2: Explanation

The linear correlation coefficient using the formula

$r=\frac{\sum xy-\frac{{\sum }^x{\sum }^y}{n}}{\sqrt{\left(\sum x^2-\frac{\sum x^2}{n}\right)\left(\sum y^2-\frac{\sum y^2}{n}\right)}}$

Calculation:

Make a table of values

Find the correlation coefficient

$$\begin{gathered} r=\frac{\sum xy-\frac{\sum x\sum y}{n}}{\sqrt{\left(\sum x^2-\frac{{\left(\sum x\right)}^2}{n}\right)\left(\sum y^2-\frac{{\left(\sum y\right)}^2}{n}\right)}} \\ =\frac{34-\frac{6(1.5)}{3}}{\sqrt{(14-(36/3\left)\right)(89-(225/3\left)\right)}} \end{gathered}$$

Hence,

The linear coefficient by the formula $0.756$