Chapter 10

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To construct an interval estimate for the difference between the means of two populations when the standard deviations of the two populations are unknown and it can be assumed the two populations have equal variances, we must use a t distribution with (let n1 be the size of sample 1 and n2 the size of sample 2) a. (n1 + n2) degrees of freedom. b. (n1 + n2 - 1) degrees of freedom. c. (n1 + n2 - 2) degrees of freedom. d. (n1 - n2 + 2) degrees of freedom.

(n1 + n2 - 2) degrees of freedom.

To compute an interval estimate for the difference between the means of two populations, the t distribution a. is restricted to small sample situations. b. is not restricted to small sample situations. c. can be applied when the populations have equal means. d. can be applied only when the populations have equal standard deviations.

is not restricted to small sample situations

If we are interested in testing whether the proportion of items in population 1 is larger than the proportion of items in population 2, the a. null hypothesis should state p1 - p2 < 0. b. null hypothesis should state p1 - p2 > 0. c. alternative hypothesis should state p1 - p2 > 0. d. alternative hypothesis should state p1 - p2 < 0.

alternative hypothesis should state p1 - p2 > 0.

If two independent large samples are taken from two populations, the sampling distribution of the difference between the two sample means a. can be approximated by any distribution. b. will have a variance of one. c. can be approximated by a normal distribution. d. will have a mean of one.

can be approximated by a normal distribution

When developing an interval estimate for the difference between two population means with sample sizes of n1 and n2, a. n1 must be equal to n2. b. n1 must be smaller than n2. c. n1 must be larger than n2. d. n1 and n2 can be of different sizes.

n1 and n2 can be of different sizes

The standard error of - is the a. pooled estimator of - . b. variance of the sampling distribution of - . c. standard deviation of the sampling distribution of - . d. margin of error of - .

standard deviation of the sampling distribution of - .


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