A linear regression model takes the pressure level from a production process and uses this to predict product quality in advance of production. This model has already been fitted to the data, and the table below displays predicted values from the model along with the actual values.
Predicted Quality Y^ | 57 | 45 | 64 | 41 |
Actual Quality Y | 56 | 64 | 67 | 58 |
Based on the above information, the coefficient of determination is given by:
Solution :
from given information:
S.No | X | (X-x̄) | (X-x̄)2 | |
1 | 57 | 5.25 | 27.5625 | |
2 | 45 | -6.75 | 45.5625 | |
3 | 64 | 12.25 | 150.0625 | |
4 | 41 | -10.75 | 115.5625 | |
average xbar =Σx/n | 51.75 | Σ(X-x̄)2= | 338.75 |
SST =338.75
Y | (y-ybar) | (y-y^)^2 |
56 | -5.25 | 27.5625 |
64 | 2.75 | 7.5625 |
67 | 5.75 | 33.0625 |
58 | -3.25 | 10.5625 |
61.25 | total | 78.75 |
SSE =78.75
coefficient of determination =1-SSE/SST =1-78.75/338.75 = 0.7675
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