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There is an opportunity for 4 Extra Credit Points on Problem 2. 1. When constructing confidence intervals and conducting hypothesis tests for the comparison of two population means Hi and µ2, we analyze the difference (u1 – #2). In doing so, we turn to the sampling distribution of (T – F1). a) The mean, HT-), of the sampling distribution of (7ī – 2) is equal to (i) Hi42 (ii) uỉ – u3 (iii) (iv) µ1- 42 b) Suppose the two populations have standard deviations o, and o2, and the sample sizes are, respectively, ni and n2 (and that the samples are independent). Then the standard deviation, o-), of the sampling distribution of (T - 1) is equal to (i) ni+n2 (ii) of - ož (iii) (iv) đ102 c) Due to the Central Limit Theorem, for large sample sizes (n 2 30 and ną 2 30), the sampling distribution of (T – 11) is (approximately) (i) normal (ii) uniform (iii) exponential (iv) log-normal

There is an opportunity for 4 Extra Credit Points on Problem 2. 1. When constructing confidence intervals and conducting hypothesis tests for the comparison of two population means Hi and µ2, we analyze the difference (u1 – #2). In doing so, we turn to the sampling distribution of (T – F1). a) The mean, HT-), of the sampling distribution of (7ī – 2) is equal to (i) Hi42 (ii) uỉ – u3 (iii) (iv) µ1- 42 b) Suppose the two populations have standard deviations o, and o2, and the sample sizes are, respectively, ni and n2 (and that the samples are independent). Then the standard deviation, o-), of the sampling distribution of (T - 1) is equal to (i) ni+n2 (ii) of - ož (iii) (iv) đ102 c) Due to the Central Limit Theorem, for large sample sizes (n 2 30 and ną 2 30), the sampling distribution of (T – 11) is (approximately) (i) normal (ii) uniform (iii) exponential (iv) log-normal

Calculus For The Life Sciences
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter13: Probability And Calculus
Section13.2: Expected Value And Variance Of Continuous Random Variables
Problem 10E
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There is an opportunity for 4 Extra Credit Points on Problem 2. 1. When constructing confidence intervals and conducting hypothesis tests for the comparison of two population means µi and 42, we analyze the difference (41 - 42). In doing so, we turn to the sampling distribution of (rī – F2). a) The mean, HT-3), of the sampling distribution of (Fī – 12) is equal to (i) H142 (ii) uỉ – u3 (iii) (iv) H1 - 42 b) Suppose the two populations have standard deviations o1 and o2, and the sample sizes are, respectively, nị and n2 (and that the samples are independent). Then the standard deviation, o(7-7), of the sampling distribution of (T- F2) is equal to (i) ta (ii) of – o (ii) (iv) đ102 c) Due to the Central Limit Theorem, for large sample sizes (n 2 30 and ng 2 30), the sampling distribution of (FT – F2) is (approximately) (i) normal (ii) uniform (iii) exponential (iv) log-normal d) Also, for large sample sizes, s? and sž will provide good approximations to of and of. Therefore, for large sample sizes, we can approximate o(- using (i) (i) -品 (iii) (iv) $182
Transcribed Image Text:There is an opportunity for 4 Extra Credit Points on Problem 2. 1. When constructing confidence intervals and conducting hypothesis tests for the comparison of two population means µi and 42, we analyze the difference (41 - 42). In doing so, we turn to the sampling distribution of (rī – F2). a) The mean, HT-3), of the sampling distribution of (Fī – 12) is equal to (i) H142 (ii) uỉ – u3 (iii) (iv) H1 - 42 b) Suppose the two populations have standard deviations o1 and o2, and the sample sizes are, respectively, nị and n2 (and that the samples are independent). Then the standard deviation, o(7-7), of the sampling distribution of (T- F2) is equal to (i) ta (ii) of – o (ii) (iv) đ102 c) Due to the Central Limit Theorem, for large sample sizes (n 2 30 and ng 2 30), the sampling distribution of (FT – F2) is (approximately) (i) normal (ii) uniform (iii) exponential (iv) log-normal d) Also, for large sample sizes, s? and sž will provide good approximations to of and of. Therefore, for large sample sizes, we can approximate o(- using (i) (i) -品 (iii) (iv) $182
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