Just follow the below steps to calculate the linear regression:
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The Linear regression calculator calculates the linear regression between two data sets, say X & Y. It also calculates the mean and covariance of both sets. It gives a step-by-step solution to the problems.
In statistics, linear regression is a linear approach for modeling the relationship between a scalar response and one or more dependent and independent variables. The case of one variable is called simple linear regression for more than one, the process is called multiple linear regression.
The general formula of linear regression is as follows:
In the above formula:
The equation of a line “y = mx + c” is also used to calculate the linear regression.
In the following example, the method to calculate the linear regression is explained briefly.
Example 1:
Calculate the linear regression of the following data sets
X = 5, 3, 8, 4, 2, 7
Y = 43, 6, 4, 55, 1, 9
Solution:
Step 1: Calculate the mean of the data sets.
Mean of X = (5 + 3 + 8 + 4 + 2 + 7) / 6
Mean of X = (29) / 6
Mean of X = 4.833
Mean of Y = (43 + 6 + 4 + 55 + 1 + 9) / 6
Mean of Y = (118) / 6
Mean of Y = 19.667
X | Y | X.Y | X2 | Y2 |
5 | 43 | 215 | 25 | 1849 |
3 | 6 | 18 | 9 | 36 |
8 | 4 | 32 | 64 | 16 |
4 | 55 | 220 | 16 | 3025 |
2 | 1 | 22 | 4 | 1 |
7 | 9 | 63 | 49 | 81 |
∑X = 29 | ∑Y = 118 | ∑XY = 550 | ∑X2 = 167 | ∑Y2 = 5008 |
Step 2: Calculate slope m
Slope = m = {(6 × 550) − (29 × 118)} / {6 × 167 − 841}
Slope = m = −122 / 161
Slope = m = -0.7578
Step 3: Calculate y-intercept “c”
y-intercept = c = {(118) − (−0.7578 × 29)} / 6
y-intercept = c = 23.3294
Step 4: Put the values in the straight-line equation to find out the regression equation
y = mx + b
y = −0.7578x + 23.3294
Linear regression | Wikipedia.
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