(a) State the null hypothesis Ho and the alternative hypothesis H₁. H:0 H₁:0 b) Determine the type of test statistic to use,
(a) State the null hypothesis Ho and the alternative hypothesis H₁. H:0 H₁:0 b) Determine the type of test statistic to use,
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
![**Hypothesis Test for the Difference of Population Means: Paired**
(a) **State the Null and Alternative Hypothesis:**
- \( H_0 \): [ ]
- \( H_1 \): [ ]
(b) **Determine the Type of Test Statistic to Use:**
- Type of test statistic: (Choose one) [Dropdown menu]
(c) **Find the Value of the Test Statistic:**
- [Input box] (Round to three or more decimal places.)
(d) **Find the Critical Value at the 0.05 Level of Significance:**
- [Input box] (Round to three or more decimal places.)
(e) **Conclusion at the 0.05 Level:**
- Can the company conclude that the mean assembly time for Process 1 exceeds that of Process 2?
- [ ] Yes
- [ ] No](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fab310076-c445-4f02-aa72-05faca788dac%2F6925c09a-515e-45cf-88a6-c52fa180d49a%2Fbdc90no_processed.jpeg&w=3840&q=75)
Transcribed Image Text:**Hypothesis Test for the Difference of Population Means: Paired**
(a) **State the Null and Alternative Hypothesis:**
- \( H_0 \): [ ]
- \( H_1 \): [ ]
(b) **Determine the Type of Test Statistic to Use:**
- Type of test statistic: (Choose one) [Dropdown menu]
(c) **Find the Value of the Test Statistic:**
- [Input box] (Round to three or more decimal places.)
(d) **Find the Critical Value at the 0.05 Level of Significance:**
- [Input box] (Round to three or more decimal places.)
(e) **Conclusion at the 0.05 Level:**
- Can the company conclude that the mean assembly time for Process 1 exceeds that of Process 2?
- [ ] Yes
- [ ] No
![A computer manufacturer is interested in comparing assembly times for two keyboard assembly processes. Process 1 is the standard process used for several years, and Process 2 is an updated process hoped to bring a decrease in assembly time. Assembly times can vary considerably from worker to worker, and the company decides to eliminate this effect by selecting 8 workers at random and timing each worker on each assembly process. Half of the workers are chosen at random to use Process 1 first, and the rest use Process 2 first. For each worker and each process, the assembly time (in minutes) is recorded, as shown in the table below:
| Worker (k) | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
|------------|----|----|----|----|----|----|----|----|
| Process 1 | 79 | 39 | 56 | 72 | 49 | 90 | 75 | 67 |
| Process 2 | 74 | 19 | 60 | 77 | 38 | 75 | 44 | 44 |
| Difference (Process 1 - Process 2) | 5 | 20 | -4 | -5 | 11 | 15 | 31 | 23 |
Based on these data, can the company conclude, at the 0.05 level of significance, that the mean assembly time for Process 1 exceeds that of Process 2? Answer this question by performing a hypothesis test regarding \(\mu_d\) (which is \(\mu\) with a letter "d" subscript), the population mean difference in assembly times for the two processes. Assume that this population of differences (Process 1 minus Process 2) is normally distributed.
Perform a one-tailed test. Then complete the parts below. Carry your intermediate computations to three or more decimal places and round your answers as specified. (If necessary, consult a list of formulas.)
(a) State the null hypothesis \(H_0\) and the alternative hypothesis \(H_1\).
- \(H_0\):
- \(H_1\):
Carry out the hypothesis test using these hypotheses to determine if Process 1's mean assembly time significantly exceeds that of Process 2.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fab310076-c445-4f02-aa72-05faca788dac%2F6925c09a-515e-45cf-88a6-c52fa180d49a%2F9equu3n_processed.jpeg&w=3840&q=75)
Transcribed Image Text:A computer manufacturer is interested in comparing assembly times for two keyboard assembly processes. Process 1 is the standard process used for several years, and Process 2 is an updated process hoped to bring a decrease in assembly time. Assembly times can vary considerably from worker to worker, and the company decides to eliminate this effect by selecting 8 workers at random and timing each worker on each assembly process. Half of the workers are chosen at random to use Process 1 first, and the rest use Process 2 first. For each worker and each process, the assembly time (in minutes) is recorded, as shown in the table below:
| Worker (k) | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
|------------|----|----|----|----|----|----|----|----|
| Process 1 | 79 | 39 | 56 | 72 | 49 | 90 | 75 | 67 |
| Process 2 | 74 | 19 | 60 | 77 | 38 | 75 | 44 | 44 |
| Difference (Process 1 - Process 2) | 5 | 20 | -4 | -5 | 11 | 15 | 31 | 23 |
Based on these data, can the company conclude, at the 0.05 level of significance, that the mean assembly time for Process 1 exceeds that of Process 2? Answer this question by performing a hypothesis test regarding \(\mu_d\) (which is \(\mu\) with a letter "d" subscript), the population mean difference in assembly times for the two processes. Assume that this population of differences (Process 1 minus Process 2) is normally distributed.
Perform a one-tailed test. Then complete the parts below. Carry your intermediate computations to three or more decimal places and round your answers as specified. (If necessary, consult a list of formulas.)
(a) State the null hypothesis \(H_0\) and the alternative hypothesis \(H_1\).
- \(H_0\):
- \(H_1\):
Carry out the hypothesis test using these hypotheses to determine if Process 1's mean assembly time significantly exceeds that of Process 2.
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