(i. The interval estimate states the range within which a population parameter probably lies.
(ii) A 95 percent confidence interval implies that about 95 out of 100 similarly constructed intervals will include the parameter being estimated.
(iii) For a sampling distribution of the means, 95% percent of the means would be between $\pm$ 1.96 standard deviations.
A) (i), (ii), and (iii) are all correct statements.
B) (i) and (ii) are correct statements but not (iii).
C) (i) and (iii) are correct statements but not (ii).
D) (ii) and (iii) are correct statements but not (i).
E) (i), (ii), and (iii) are all false statements.

Question

(i. The interval estimate states the range within which a population parameter probably lies. 
(ii) A 95 percent confidence interval implies that about 95 out of 100 similarly constructed intervals will include the parameter being estimated.
(iii) For a sampling distribution of the means, 95% percent of the means would be between $\pm$ 1.96 standard deviations.
A) (i), (ii), and (iii) are all correct statements.
B) (i) and (ii) are correct statements but not (iii).
C) (i) and (iii) are correct statements but not (ii).
D) (ii) and (iii) are correct statements but not (i).
E) (i), (ii), and (iii) are all false statements.

Quizplus · Accepted Answer

(i) correctly defines an interval estimate. (ii) accurately describes the meaning of a 95 percent confidence interval. (iii), despite its unclear notation, seems to intend to describe the rule that for a normally distributed sampling distribution of the mean, approximately 95% of the sample means will fall within ±1.96 standard deviations of the population mean.

(I the Interval Estimate States the Range Within Which a Population