Use the given statistics to complete parts (a) and (b). Assume that the populations are normally distributed.(a) Test whetherμ1>μ2at theα=0.10level of significance for the given sample data.(b) Construct a90%confidence interval aboutμ1−μ2. Population 1Population 2 n2815x45.543.9s5.912.3(a) Identify the null and alternative hypotheses for this test. A.H0:μ1=μ2H1:μ1≠μ2 B.H0:μ1=μ2H1:μ1>μ2Your answer is correct. C.H0:μ1≠μ2H1:μ1=μ2 D.H0:μ1>μ2H1:μ1=μ2 E.H0:μ1<μ2H1:μ1=μ2 F.H0:μ1=μ2H1:μ1<μ2 Find the test statistic for this hypothesis test. (need this answer) (Round to two decimal places as needed.)

Given: n1=28x¯1=45.5s1=5.9n2=15x¯2=43.9s2=12.3α=0.10

Answered: Use the given statistics to complete…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

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Use the given statistics to complete parts (a) and (b). Assume that the populations are normally distributed.

(a) Test whether

μ1>μ2

at the

α=0.10

level of significance for the given sample data.

(b) Construct a

90%

confidence interval about

μ1−μ2.

			Population 1	Population 2
n	28	15
x	45.5	43.9
s	5.9	12.3

(a) Identify the null and alternative hypotheses for this test.

H0:

μ1=μ2

H1:

μ1≠μ2

H0:

μ1=μ2

H1:

μ1>μ2

Your answer is correct.

H0:

μ1≠μ2

H1:

μ1=μ2

H0:

μ1>μ2

H1:

μ1=μ2

H0:

μ1<μ2

H1:

μ1=μ2

H0:

μ1=μ2

H1:

μ1<μ2

Find the test statistic for this hypothesis test. (need this answer)

(Round to two decimal places as needed.)

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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