(i. The interval estimate states the range within which a population parameter probably lies.
(ii) The confidence interval is the interval within which a population parameter is expected to lie.
(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) The confidence interval is the interval within which a population parameter is expected to lie.
(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) and (ii) essentially describe the same concept using slightly different wording, both correctly defining aspects of interval estimation and confidence intervals. (iii) correctly describes the 95% confidence interval in the context of a sampling distribution of means, where approximately 95% of sample means would fall within 1.96 standard deviations of the population mean.

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