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Name: Suppose Michigan State University's Collegiate Employment Institute fo
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Description: Suppose Michigan State University's Collegiate Employment Institute found that starting salaries for recipients of bachelor's degrees in business was $50,032 in 2017. The results for a sample of 100 business majors receiving a bachelor's degree in 20

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Suppose Michigan State University's Collegiate Employment Institute found that starting salaries for recipients of bachelor's degrees in business was $50,032 in 2017. The results for a sample of 100 business majors receiving a bachelor's degree in 2018 showed a mean starting salary of $51,279 with a sample standard deviation of $5,200. Conduct a hypothesis test to determine whether the mean starting salary for business majors in 2018 is greater than the mean starting salary in 2017. Use

? = 0.01

as the level of significance.

State the null and alternative hypotheses. (Enter != for ≠ as needed.)

H₀:

H_a:

Find the value of the test statistic. (Round your answer to three decimal places.)

Find the p-value. (Round your answer to four decimal places.)

p-value =

State your conclusion.

Reject H₀. There is insufficient evidence to conclude that the mean starting salary for business majors has increased in 2018.

Reject H₀. There is sufficient evidence to conclude that the mean starting salary for business majors has increased in 2018.

Do not reject H₀. There is insufficient evidence to conclude that the mean starting salary for business majors has increased in 2018.

Do not reject H₀. There is sufficient evidence to conclude that the mean starting salary for business majors has increased in 2018.

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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