APPLICATION OF SUPERVISED LEARNING
LINEAR REGRESSION
|
Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
|
|
|
An X value of 0 would would increase Y by 7.
|
|
|
A 1 unit decrease in X results in a 3.2 unit decrease in Y.
|
|
|
A 1 unit increase in X results in a 3.2 unit increase in Y.
|
|
|
A 1 unit increase in X results in a 3.2 unit decrease in Y.
|
Detailed explanation-1: -The line with equation y = 0 + 1x is known as the regression line. The regression coefficient 1 is the slope of the regression line and the regression coefficient (the constant) 0 is the intercept of the line on the y-axis.
Detailed explanation-2: -The slope is interpreted as the change of y for a one unit increase in x. This is the same idea for the interpretation of the slope of the regression line. ^ 1 represents the estimated increase in Y per unit increase in X. Note that the increase may be negative which is reflected when is negative.
Detailed explanation-3: -Our model will take the form of ŷ = b 0 + b1x where b0 is the y-intercept, b1 is the slope, x is the predictor variable, and ŷ an estimate of the mean value of the response variable for any value of the predictor variable. The y-intercept is the predicted value for the response (y) when x = 0.