Please use minitab
Two variables within a process are thought to be correlated. Generate a Scatter Plot, determine the value of the coefficient of correlation, and estimate the variability in Y thought to be caused by X. Note: Data divided into six columns for visual display. Your analysis should have a single X column and a single Y column
X |
Y |
X |
Y |
X |
Y |
27.02 |
50.17 |
43.09 |
50.09 |
57.07 |
49.80 |
30.01 |
49.84 |
43.96 |
49.77 |
59.07 |
49.91 |
33.10 |
50.00 |
46.14 |
49.61 |
59.96 |
50.20 |
34.04 |
49.79 |
46.99 |
49.86 |
61.05 |
49.97 |
35.09 |
49.99 |
48.20 |
50.18 |
61.88 |
50.16 |
35.99 |
49.97 |
49.87 |
49.90 |
63.08 |
49.97 |
36.86 |
49.93 |
51.92 |
49.84 |
63.87 |
50.12 |
37.83 |
49.94 |
53.97 |
49.89 |
66.10 |
50.05 |
39.13 |
50.10 |
55.02 |
50.02 |
67.17 |
50.20 |
39.98 |
50.09 |
55.97 |
49.81 |
68.01 |
50.19 |
The scatter plot for the data is :
For determining the coefficient of correlation, we make use of
MS-Excel as follows :
Coefficient of correlation = CORREL(A2:A31,B2:B31) =
0.2439
where (A2:A31,B2:B31) represents the range of the data.
The variability in Y thought to be caused by X is shown by
coefficient of determination i.e. R-squared and to obtain this just
square the coefficient of correlation and thus,
R-squared = 0.24392 = 0.0595
Hope this answers your query!
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