**Step 1**: First of all, we evaluate value of ‘N’, where ‘N’ is equal to all data entries which is present in a Set and all summations values means,

∑xy, ∑x, ∑y, ∑x

^{2}and ∑y

^{2}.

**Step 2:**After evaluation of all summation values, now we use following formula to evaluate Linear Correlation coefficient –

Correlation coefficient r = N ∑xy - (∑x)(∑y) / √([N ∑x

^{2}- (∑x)

^{2}]) . ([N ∑y

^{2}- (∑y)

^{2}]),

**Step 3:**After evaluation of Linear Correlation Coefficient, we know determine the strength and direction between the given variables ‘x’ and y by r

^{2}.

Now we take an example to understand the process of linear correlation coefficient-

**Example:**Find the Linear Regression coefficient of determination for following variables -

X: 26 14 18 10 26 21 7 26 13 19 17 13 16 28 23

Y: 20 10 13 9 19 17 8 15 9 13 12 7 9 17 14?

**Solution:**We use following steps for linear correlation coefficient-

**Step 1:**First of all, we find out all values-

N = 15,

∑xy = 3882,

∑x = 277,

∑y = 192,

∑x

^{2}= 5695,

∑y

^{2}= 2698.

**Step 2:**Now we calculate linear correlation coefficient-

Correlation coefficient r = N ∑xy - (∑x)(∑y) / √([N ∑x

^{2}- (∑x)

^{2}]) . ([N ∑y

^{2}- (∑y)

^{2}]),

=> r = 15(3882) – (277)(192) / √([15 (5695) - (277)

^{2}]) . ([15 (2698) - (192)

^{2}]),

=> r = 0.901.

**Step 3:**Now we calculate r

^{2}means Square of correlation coefficient-

r

^{2}= (0.901)

^{2}= 0.81.

So, this linear correlation coefficient have 81% strong relation between ‘x’ and ‘y’ variable and 19% weak relation between ‘x’ and ‘y’ variable.