The least squares method is used to determine an estimated regression line that minimizes the squared deviations of the data values from the line.

1.   ?    True
2.   ?    False

The least squares method is applicable only in situations where the estimated regression line has a positive slope.

1.   ?    True
2.   ?    False

If the slope of the estimated regression line is positive, the correlation coefficient must be negative.

1.   ?    True
2.   ?    False

The slope of the estimated regression line (b1) is a sample statistic, since, like other sample statistics, it is computed from the sample observations.

1.   ?    True
2.   ?    False

The sampling distribution of b1 is normal if the usual regression assumptions are satisfied.

1.   ?    True
2.   ?    False

If two variables are perfectly linearly related, the sample correlation coefficient must equal -1 or 1.

1.   ?    True
2.   ?    False

The residual is the difference between the actual value of a dependent variable and the value predicted by the estimated regression line.

1.   ?    True
2.   ?    False

For the estimated regression line = 3 - 10x, the correlation coefficient r_xy

1.   ?    equals 0
2.   ?    is less than 0
3.   ?    is greater than 0

If the correlation coefficient for two variables is -.9, the coefficient of determination is

1.   ?    .9
2.   ?    -.81
3.   ?    .81
4.   ?    Cannot be determined
5.   ?    None of the above

If all else is held constant, compared to the prediction interval for a particular value of y, the confidence interval for a mean value of y will be

1.   ?    narrower
2.   ?    wider
3.   ?    not enough information is given

Below you are given a summary of the output from a simple linear regression analysis from a sample of size 15:
SS (total) = 152
SS(regression) =100
The coefficient of determination is

1.   ?    0.5200
2.   ?    0.6579
3.   ?    0.8111
4.   ?    1.52
5.   ?    Cannot be determined given this information

Below you are given a summary of the output from a simple linear regression analysis from a sample of size 15:
SS (total) = 152
SS(regression) =100
The correlation coefficient is

1.   ?    0.5200
2.   ?    0.6579
3.   ?    0.8111
4.   ?    1.52
5.   ?    Cannot be determined given this information

Below you are given a summary of the output from a simple linear regression analysis from a sample of size 15:
SS (total) = 152
SS(regression) =100
An F test for a significant relationship is to be done, the test statistic value is

1.   ?    4
2.   ?    5
3.   ?    25
4.   ?    100
5.   ?    Cannot be determined given this information

Below you are given a summary of the output from a simple linear regression analysis from a sample of size 15:
SS (total) = 152
SS(regression) =100
An F test for a significant relationship is to be done with  = .05, the critical value for this test is

1.   ?    1.771
2.   ?    2.160
3.   ?    4.67
4.   ?    9.07

Below you are given a summary of the output from a simple linear regression analysis from a sample of size 15:
SS (total) = 152
SS(regression) =100
An F test for a significant relationship is to be done with a = .05, the decision for this test is

1.   ?    do not reject the null hypothesis
2.   ?    reject the null hypothesis