In: Statistics and Probability
The data shown in the table were collected by surveying 100 employees with five years’ experience. Find the correlation relationship for the data. Use Microsoft Excel. Create a scatter plot. Identify and discuss the type of correlation, and whether is negative or positive, strong or weak. Create a regression line and analyze the coefficients for significance. Predict the estimates salary with 20 years of schooling.
Years of schooling |
Total annual salary |
10 |
$32 K |
12 |
$33 K |
13 |
$44.3 K |
15 |
$55.7 K |
18 |
$60 K |
The scatter plot shows a positive correlation
The following data are passed:
Years of schooling X | Total annual salary ($'k)Y |
10 | 32 |
12 | 33 |
13 | 44.3 |
15 | 55.7 |
18 | 60 |
The independent variable is X, and the dependent variable is Y. In order to compute the regression coefficients, the following table needs to be used:
X | Y | X*Y | X2 | Y2 | |
10 | 32 | 320 | 100 | 1024 | |
12 | 33 | 396 | 144 | 1089 | |
13 | 44.3 | 575.9 | 169 | 1962.49 | |
15 | 55.7 | 835.5 | 225 | 3102.49 | |
18 | 60 | 1080 | 324 | 3600 | |
Sum = | 68 | 225 | 3207.4 | 962 | 10777.98 |
Based on the above table, the following is calculated:
Therefore, based on the above calculations, the regression coefficients (the slope m, and the y-intercept n) are obtained as follows:
Therefore, we find that the regression equation is:
Y = -8.8882 + 3.9624 X
At X = 20
Y = -8.8882 + 3.9624 *20
Y = -8.8882 + 79.248
Y = $70.3598 k
Graphically: