# Which of the following statements about the correlation coefficient

QUESTION 1

Which of the following statements about the correlation coefficient between variable X1 (Number of advertisements placed the previous week) and variable X2 (Number of calls received the previous week) is correct:

-The correlation coefficient is not statistically significant at 5% level

-The correlation coefficient is not statistically significant at 10% level

-Number of ads placed the previous week is not independent from the number of calls received previous week

-An increase in the number of ads placed the previous week would cause the number of calls to increase by 61 percent

-A decrease in the number of ads placed the previous week would cause the number of calls to decrease by 0.61 percent

1 points

QUESTION 2

Which of the following statements about the estimated model is correct:

-The proportion of variance in Y explained is 59.11%

-The difference between R squared and adjusted R squared indicated that the overall model is insignificant

-The sample size of 12 is too small for regression to be performed

-The intercept of -270 means that next week should be expected 270 fewer calls than the previous week

-The F-value of 3.85 is greater than 2.0; therefore, the model is significant

1 points

QUESTION 3

The unexplained variance in Y (Number of Calls Received) is

=0.9208

=0.5882

=0.4969

=0.4118

0

1 points

QUESTION 4

Which of the following statements is correct:

-None of the independent variable are statistically significant at 5% level

-The effect of X2 (Calls Received Previous Week) variable is statistically significant at 5% level

-The effect of X3 (Airline Bookings) variable is statistically significant at 5% level

-All of the independent variables are statistically significant at 5% level

The dependent variable is statistically significant at 5% level

1 points

QUESTION 5

Which of the following statements is correct:

-The regression model produces an unbiased estimate of the dependent variable

-The regression model produces good estimates because the average residual is less than 5%

-The average error produced by the regression model is 13 calls

-The average error produced by the regression model is about 74 calls

-The average error produced by the regression model is insignificant at 5% level

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