Simple linear regression is an improvement on correlation analysis of the relati

Question

Simple linear regression is an improvement on correlation analysis of the relationship between two variables in that it

Select one:
a. Can never have a regression coefficient of zero
b. Can be calculated even when there is no relationship between the X and the Y variables
c. Always gives an equation with an intercept of zero
d. Specifies the amount by which the Y variable changes in response to a change in the X variable

Regression works in determining the equation of a line that represents a scatter plot by

Select one:
a. Yielding the line that has the smallest intercept
b. Yielding the line that best describes the relationship for points beyond the data set
c. Yielding the line with the smallest squared distances from the data points to the line
d. Yielding the line that explains all of the variation in Y

In regression, the p-value of a regression coefficient results from

Select one:
a. The t-value of a hypothesis test that the coefficient's value is zero
b. The calculation of Pearson’s r
c. Calculation of the R2
d. The use of an F-test

Explanation / Answer

Answer to the questions:

1. d. is the right option. The SLR need not have a 0 intercept. IT can even give a reg-coefficient of 0. B is also not poosible, there has to be a linear relatonship between variables to make sense of SLR.

The right answer is D. SLR says if u change x by 1 unit, y changes by these many units.

2. SLR line minimizes the squared distances ( or the sum of squared errors), So,
c. is the right choice

3. a. is the right option. The fate of hypothesis test of this coefficient. is decided by the t value. A is right

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