Question 9

[1.8 Diagnostics]In the simple linear regression,the normality assumption states that response variable is normaly distrubuted.

True

False

Question 10

[1.2 Estimation method] In simple linear regression,the sampling distribution for the variance estimator is (chi-squared) regardless of whether assumptions of the model hold or not.

True

False

Question 11

[2.8 Data Example] In ANOVA if the constant variance assumptions does not hold the statistical inference on the equality of the means will not be reliable.

True

False

Question 12

[1.2 Estimation Method] In simple linear regression,a negative value of B1 is consistent with an inverse relationship between the predicting variable and the response variable.

True

False

Question 13

[2.8 Data Example] In ANOVA if the pear wise comparison interval between groups does not include zero, we conclude that the two means are plausibly equal.

True

False

Question14

[2.2 Estimation Method] An ANOVA model with a qualitative predicting variable containing k groups will have k+1 parameters to estimate.

True

False

Question 15

[1.10 Diagnostics model Evaluation Example] In simple linear regression, we asses the constant variance assumption by plotting the response variable against fitted values.

True

False

Question 16

[1.8 Diagnostics] With the Box-Cox transformation, we do not transform the response variable when (lambda)=0.

True

false

Question 17

[See 1.5 statistical inference Data Example] the p-value is a measure of the probability of rejecting the null hypothesis.

True

false

Question 18

[Model fit Assessment] In ANOVA, we can only use the quantile-quantile normal plot of the residuals for assessing normality assumption.

True

False

Question 19

[1.4 statistical inference] In sampling linear regression, the distribution of0-hat is a

Chi squared distribution

t- squared distribution

normal distribution

None of the Above

Question 20

[1.9 Outliers and Model Evaluation] A data point far from the meaning of both the x's and y's is always:

An influential point and an outlier

A leverage point and an influential point

an outlier and leverage point

None of the above

Question 21

[2.4 Test for equal means] In ANOVA, when testing for equal means across groups, the alternative hypothesiscan be started as,

The means of all pairs of groups are different

The means of all groups are equal

The means of at least one pair of groups is different

None of the Above

Question 22

[1.4 statistical inference] To test if a regression coefficient is less than a critical value, C, we conduct a one-sided test on the______ tail of a________ distribution.

Left, t

Left, normal

Right, t

None of the above

Question 23

[2.4 Test for equal means] The F-test is a_______ tailed test with ________ and________ degrees of freedom

One, k-1, N-k

One, k,N-k

Two, k-1, N-k

Two k, N-1

None of the Above

For 24 & 25

The following output of a simple linear regression model that relates the duration of an eruption with the waiting time since the previous eruption

Coefficients :

Estimates Std. Error t value Pr(>|t|)

(Intercept) -1.374016 A -1.70 0.045141

waiting 0.043714 0.011098 B 0.000052

Residual Standard error: 0.4965 on 270 degrees of freedom

Multiple R-squared: 0.8115, Adjusted R-squared: 0.8108

F-statistic: 1162 on 1 and 270 DF, p-value: <2.2e-16

Question 24

[1.4 Statistical inference] Using the table above, what is the standard error of the intercept, labeled A, and rounded to three decimal places?

2.336

0.808

0.806

-0.806

None of the Above

Question 25

[1.4 Statistical inference] Using the table, above what is the t-value of the coefficient for waiting, labeled B, and rounded to three decimal places?

3.939

3.931

3.935

None of the Above