I have answered the questions but need to have them checked to see how good or bad i did on them. Thanks

The quick rule would say that in a bivariate scatter plot with 25 observations, a correlation of 0.45 is significantly different than zero (but just barely).

A) True

B) False

MY ANSWER A

2.

The bivariate correlation coefficient always has the same sign as b1 in Y = b0 + b1X.

A) True

B) False

MY ANSWER A

3.

The least squares regression line is obtained when the sum of the squared residuals is minimized.

A) True

B) False

MY ANSWER B

4.

When using the least squares method, the column of residuals always sums to zero.

A) True

B) False

MY ANSWER A

5.

In linear regression between two variables, a significant correlation exists when the p-value of the F statistic is greater than the stated level of alpha.

A) True

B) False

MY ANSWER B

6.

The sample coefficient of correlation

A) can range from -1.00 up to 1.00.

B) is also called Pearson's r.

C) is tested for significance using a t-test.

D) has all of the above properties

MY ANSWER. B

7.

Which is not true of the coefficient of determination?

A) It is the square of the coefficient of correlation.

B) It is negative when there is an inverse relationship between X and Y.

C) It reports the percent of the variation in Y explained by X.

D) It is based on sum of squares (SSR, SSE, and SS total).

MY ANSWER B

8.

If the sample size is 25 and the fitted regression is Y = 3.5 + 2.1X, then it is incorrect to say that

A) Y increases 2.1 percent for a 1 percent increase in X.

B) the equation crosses the Y axis at 3.5.

C) the correlation coefficient is positive.

D) the correlation is probably significant if it exceeds 0.40.

MY ANSWER A

9.

Which of the following is not a characteristic of the F distribution?

A) It is a continuous distribution.

B) It can never be negative.

C) It is a family based on two sets of degrees of freedom.

D) It describes the ratio of two sample means.

MY ANSWER A

Use the following scenario to answer questions 10 and 11.

William used a sample of 68 U.S. cities to estimate the relationship between Crime (annual property crimes per 100,000 persons) and Income (median income per capita). His estimated regression equation was Crime = 428 + .050 Income.

10.

From this information, we can conclude that

A) the slope is not significantly different from zero.

B) crime creates additional income in a city.

C) wealthy individuals tend to commit more crimes.

D) none of the above are correct.

MY ANSWER D

11.

Assuming b1 is significant, if Income decreases by 1000 we would predict that Crime will

A) increase by 428.

B) increase by 50.

C) increase by 500.

D) none of the above are correct.

MY ANSWER C

12.

Which outcomes would be likely in a bivariate regression on 45 randomly chosen U.S. cities in 2005 with

Y = number of robberies in each city (thousands of robberies) and

X = size of police force in each city (thousands of police)?

A) Autocorrelation.

B) High R2 (due to city size).

C) Positive slope (due to city size).

D) Both b and c

MY ANSWER B