APPLICATION OF SUPERVISED LEARNING
LINEAR REGRESSION
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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In a statistics course, a linear regression equation was computed to predict the final-exam score from the score on the first test. The equation was y-hat= 10 + 0.9x where y-hat is the predicted final-exam score and x is the score on the first test. Bill scored a 90 on the first test and his residual was-2. What was his actual score on the final exam?
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89
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90
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91
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93
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Not enough information
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Explanation:
Detailed explanation-1: -Explain what the quantity S=2.74982 measures in the context of this problem. s is the standard deviation of the residuals. The difference between actual marriage length and predictent marriage length (for given courtship lengths) is 2.74982 yours, on average.
Detailed explanation-2: -The slope is often called the regression coefficient and the intercept the regression constant. The slope can also be expressed compactly as ß1= r × sy/sx.
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