16. 1423376.qxszay Jump to level 1 A auto maker is interested in information about how long transmissions last. A sample of transmissions are run constantly and the number of miles before the transmission fails is recorded. The auto maker claims that the transmissions can run constantly for over 150,000 miles before failure. The results of the sample are given belov Miles (1000s of mies) Mean 151.2 Variance 17.22 Observations 44 Hypothesized Mean 150 df 43 t Stat P(T<=t) one-tail t Critical one-tail P(T
16. 1423376.qxszay Jump to level 1 A auto maker is interested in information about how long transmissions last. A sample of transmissions are run constantly and the number of miles before the transmission fails is recorded. The auto maker claims that the transmissions can run constantly for over 150,000 miles before failure. The results of the sample are given belov Miles (1000s of mies) Mean 151.2 Variance 17.22 Observations 44 Hypothesized Mean 150 df 43 t Stat P(T<=t) one-tail t Critical one-tail P(T
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:**Hypothesis Test for a Population Mean**
*A car manufacturer wants to know how long transmissions last. A sample of transmissions is run constantly, and the number of miles before failure is recorded. The auto maker claims that transmissions can run constantly for over 150,000 miles before failure. Below are the sample results:*
- **Mean (in 1000s of miles):** 151.2
- **Variance:** 17.22
- **Observations (n):** 44
- **Hypothesized Mean:** 150
- **Degrees of Freedom (df):** 43
- **t Stat:** 1.889
- **P(T<=t) one-tail:** 0.033
- **t Critical one-tail:** 1.681
- **P(T<=t) two-tail:** 0.066
- **t Critical two-tail:** 2.017
- **Confidence Level (95.0%):** 1.129
**Visual Explanation:**
The image contains a bell-shaped normal distribution curve, illustrating the t-distribution. The horizontal axis denotes the t values, marked from -3 to 3, aligning with typical ranges used in standard t-distributions.
The region under the curve, highlighted to the right, illustrates the p-value for a one-tailed test. This visual representation helps determine where the test statistic (t) lies in comparison to the critical value.
**Interactive Content:**
- **What condition is met for the use of a t-distribution?**
- The user is prompted to make a selection from dropdown options, which may include conditions like "Sample size relatively small" or "Population variance unknown."
- **Calculations:**
- \( t = \) (user input)
- \( s = \) (user input)
These inputs allow users to engage with the data and compute necessary statistics themselves.
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