You are a process engineer for a company that manufactures widgets. A particular machine at your company has some downtime during the day on 32.5% of days. You decided to make some changes to how the machine is calibrated in an attempt to reduce downtime. After monitoring the machine for 400 days after your changes were implemented, you find that the machine had some downtime during the day on 28.1% of days. Conduct a hypothesis test to determine if the proportion of days that the machine has downtime has decreased from before, with a= 0.05. Using this information, what is the conclusion in your analysis? Round intermediate calculations to four decimal places. We reject the null hypothesis, since the test statistic of approximately -1.88 is more extreme than the critical value of -1.64. We fail to reject the null hypothesis, since the test statistic of approximately -1.89 is more extreme than the critical value of -1.64. We reject the null hypothesis, since the test statistic of approximately -2.03 is more extreme than the critical value of -1.96. None of the statements are the correct conclusion for the analysis. We fail to reject the null hypothesis, since the test statistic of approximately -1.64 is less extreme than the critical value of -2.14.
You are a process engineer for a company that manufactures widgets. A particular machine at your company has some downtime during the day on 32.5% of days. You decided to make some changes to how the machine is calibrated in an attempt to reduce downtime. After monitoring the machine for 400 days after your changes were implemented, you find that the machine had some downtime during the day on 28.1% of days. Conduct a hypothesis test to determine if the proportion of days that the machine has downtime has decreased from before, with a= 0.05. Using this information, what is the conclusion in your analysis? Round intermediate calculations to four decimal places. We reject the null hypothesis, since the test statistic of approximately -1.88 is more extreme than the critical value of -1.64. We fail to reject the null hypothesis, since the test statistic of approximately -1.89 is more extreme than the critical value of -1.64. We reject the null hypothesis, since the test statistic of approximately -2.03 is more extreme than the critical value of -1.96. None of the statements are the correct conclusion for the analysis. We fail to reject the null hypothesis, since the test statistic of approximately -1.64 is less extreme than the critical value of -2.14.
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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Transcribed Image Text:You are a process engineer for a company that manufactures widgets. A particular
machine at your company has some downtime during the day on 32.5% of days. You
decided to make some changes to how the machine is calibrated in an attempt to
reduce downtime. After monitoring the machine for 400 days after your changes
were implemented, you find that the machine had some downtime during the day on
28.1% of days. Conduct a hypothesis test to determine if the proportion of days that
the machine has downtime has decreased from before, with a= 0.05. Using this
information, what is the conclusion in your analysis? Round intermediate calculations
to four decimal places.
We reject the null hypothesis, since the test statistic of approximately -1.88 is
more extreme than the critical value of -1.64.
We fail to reject the null hypothesis, since the test statistic of approximately
-1.89 is more extreme than the critical value of -1.64.
We reject the null hypothesis, since the test statistic of approximately -2.03 is
more extreme than the critical value of -1.96.
None of the statements are the correct conclusion for the analysis.
We fail to reject the null hypothesis, since the test statistic of approximately
-1.64 is less extreme than the critical value of -2.14.
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