Quiz——Multiple Choice
Name2011上海中考英语 Student Number Scores
1. An estimator is
然而英语(A) an estimate.
(B) a formula that gives an efficient guess of the true population value.
(C) a random variable.
(D) a nonrandom number.
2. An estimate is
(A) efficient if it has the smallest variance possible.
(B) a nonrandom number.
(C) unbiad if its expected value equals the population value.
(D) another word for estimator.
3.An estimator of the population value is unbiad if
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(A) . (B) has the smallest variance of all estimators.
(C) . (D) .
4. The standard error of is given by the following formula:
(A) . (B) .
(C) . (D) .
5. A type I error is
(A) always the same as (1-type II) error.
(B) the error you make when rejecting the null hypothesis when it is true.
(C) the error you make when rejecting the alternative hypothesis when it is true.
(D) always 5%.
6. A type II error
(A) is typically smaller than the type I error.
(B) is the error you make when choosing type II or type I.
(C) is the error you make when not rejecting the null hypothesis when it is fal.
(D) cannot be calculated when the alternative hypothesis contains an “=”.
7. When you are testing a hypothesis against a two-sided alternative, then the alternative is written as
(A) . (B) . (C) . (D) .
8. If the null hypothesis states , then a two-sided alternative hypothesis is
(A) . (B) .
(C) hometown. (D)
9. A scatterplot
(A) shows how Y and X are related when their relationship is scattered all over the place.
(B) relates the covariance of X and Y to the correlation coefficient.
(C) is a plot of n obrvations on and , where each obrvation is reprented by the point ().
(D) shows n obrvations of Y over time.
10. A large p-value implies
(A) rejection of the null hypothesis.
(B) a large t-statistic.
(C) a large .
(D) that the obrved value is consistent with the null hypothesis.
11. The standard error for the difference in means if two random variables M and W , when the two population variances are different, is
(A) . (B) . (C) . (D) .
12. The following statement about the sample correlation coefficient is true. 睡帽
(A) –11. (B) .
(C) . (D) .
13. The correlation coefficient
(A) lies between zero and one.
(B) is a measure of linear association.
(C) is clo to one if X caus Y.
(D) takes on a high value if you have a strong nonlinear relationship.
14.When the estimated slope coefficient in the simple regression model, , is zero, then
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(A) R2 = . (B) 0 < R2 < 1. (C) R2 = 0. (D) R2 > (SSR/TSS).
15. The regression is defined as follows:
(A) (B) (C) (D)
16. The standard error of the regression (SER) is defined as follows
(A) (B) forgetyouSSR26个英文字母的音标 (C) 1- (D)
插花培训班17. Binary variables
(A) are generally ud to control for outliers in your sample.
(B) can take on more than two values.
(C) exclude certain individuals from your sample.
(D) can take on only two values.
18. The following are all least squares assumptions with the exception of:
(A) The conditional distribution of given has a mean of zero.
(B) The explanatory variable in regression model is normally distributed.
(C) are independently and identically distributed.
(D) Large outliers are unlikely.
19. The OLS estimator is derived by
(A) connecting the Yi corresponding to the lowest Xi obrvation with the Yi corresponding to the highest Xi obrvation.
(B) making sure that the standard error of the regression equals the standard error of the slope estimator.
(C) minimizing the sum of absolute residuals.
(D) minimizing the sum of squared residuals.
20. The OLS estimator is derived by
(A) connecting the Yi corresponding to the lowest Xi obrvation with the Yi corresponding to the highest Xi obrvation.
(B) making sure that the standard error of the regression equals the standard error of the slope estimator.
(C) minimizing the sum of absolute residuals.
(D) minimizing the sum of squared residuals.
21. The OLS residuals, , are defined as follows:
(A) (B) (C) (D)
22. The OLS residuals
