The mean waiting time at the drive-through of a fast-food restaurant from the time an order is placed to the time the order is received is 83.2 seconds. A manager devises a new drive-throughsystem that she believes will decrease wait time. As a test, she initiates the new system at her restaurant and measures the wait time for 10 randomly selected orders. The wait times are provided inthe table to the right. Complete parts (a) and (b) below.106.380.566.794.858.084.273.869.864.181.8E Click the icon to view the table of correlation coefficient critical values.(a) Because the sample size is small, the manager must verify that the wait time is normally distributed and the sample does not contain any outliers. The normal probability plot is shown below and the sample correlation coefficient is known tobe r= 0.982. Are the conditions for testing the hypothesis satisfied?V the conditionsV|satisfied. The normal probability plotV linear enough, since the correlation coefficient isthan the critical value. In addition, a boxplot does not show any outliers.AExpected z-score1-0----60 75 90 105-1-Time (sec)(b) Is the new system effective? Conduct a hypothesis test using the P-value approach and a level of significance of a = 0.1.First determine the appropriate hypotheses.Ho:V83.2H,:V83.2Find the test statistic.t =0%3D(Round to two decimal places as needed.)Find the P-value.The P-value is.(Round to three decimal places as needed.)Use the a= 0.1 level of significance. What can be concluded from the hypothesis test?O A. The P-value is less than the level of significance so there is not sufficient evidence to conclude the new system is effective.O B. The P-value is less than the level of significance so there is sufficient evidence to conclude the new system is effective.OC. The P-value is greater than the level of significance so there is not sufficient evidence to conclude the new system is effective.O D. The P-value is greater than the level of significance so there is sufficient evidence to conclude the new system is effective. Critical valuesSample Size, n Critical ValueSample Size, n Critical Value0.880160.941ral0.888170.9440.898180.9460.906190.9490.912200.951100.918210.952110.923220.954120.928230.956130.932240.957140.935250.959150.939300.960PrintDonecola0 234 5

(a) Yes. the conditions are satisfied. The normal probability plot is linear enough, since the…

The mean waiting time at the drive-through of a fast-food restaurant from the time an order is placed to the time the order is received is 83.2 seconds. A manager devises a new drive-through system that she believes will decrease wait time. As a test, she initiates the new system at her restaurant and measures the wait time for 10 randomly selected orders. The wait times are provided in the table to the right. Complete parts (a) and (b) below. 106.3 66.7 58.0 73.8 64.1 80.5 94.8 84.2 69.8 81.8 E Click the icon to view the table of correlation coefficient critical values. (a) Because the sample size is small, the manager must verify that the wait time is normally distributed and the sample does not contain any outliers. The normal probability plot is shown below and the sample correlation coefficient is known ber=0.982. Are the conditions for testing the hypothesis satisfied? the conditions V satisfied. The normal probability plot linear enough, since the correlation coefficient is than the critical value. In addition, a boxplot does not show any outliers. AExpected z-score 2- 1- 0- 00 75 00 105 Time (sec)

The mean waiting time at the drive-through of a fast-food restaurant from the time an order is placed to the time the order is received is 83.2 seconds. A manager devises a new drive-through system that she believes will decrease wait time. As a test, she initiates the new system at her restaurant and measures the wait time for 10 randomly selected orders. The wait times are provided in the table to the right. Complete parts (a) and (b) below. 106.3 66.7 58.0 73.8 64.1 80.5 94.8 84.2 69.8 81.8 E Click the icon to view the table of correlation coefficient critical values. (a) Because the sample size is small, the manager must verify that the wait time is normally distributed and the sample does not contain any outliers. The normal probability plot is shown below and the sample correlation coefficient is known ber=0.982. Are the conditions for testing the hypothesis satisfied? the conditions V satisfied. The normal probability plot linear enough, since the correlation coefficient is than the critical value. In addition, a boxplot does not show any outliers. AExpected z-score 2- 1- 0- 00 75 00 105 Time (sec)

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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Concept explainers

Estimation

A new framework of data analysis where the new statistical methods are used for interpreting the results and analyzing the data is known as estimation in statistics.

Question

The mean waiting time at the drive-through of a fast-food restaurant from the time an order is placed to the time the order is received is 83.2 seconds. A manager devises a new drive-through
system that she believes will decrease wait time. As a test, she initiates the new system at her restaurant and measures the wait time for 10 randomly selected orders. The wait times are provided in
the table to the right. Complete parts (a) and (b) below.
106.3
80.5
66.7
94.8
58.0
84.2
73.8
69.8
64.1
81.8
E Click the icon to view the table of correlation coefficient critical values.
(a) Because the sample size is small, the manager must verify that the wait time is normally distributed and the sample does not contain any outliers. The normal probability plot is shown below and the sample correlation coefficient is known to
be r= 0.982. Are the conditions for testing the hypothesis satisfied?
V the conditions
V
|satisfied. The normal probability plot
V linear enough, since the correlation coefficient is
than the critical value. In addition, a boxplot does not show any outliers.
AExpected z-score
1-
0-
---
60 75 90 105
-1-
Time (sec)
(b) Is the new system effective? Conduct a hypothesis test using the P-value approach and a level of significance of a = 0.1.
First determine the appropriate hypotheses.
Ho:
V83.2
H,:
V
83.2
Find the test statistic.
t =0
%3D
(Round to two decimal places as needed.)
Find the P-value.
The P-value is.
(Round to three decimal places as needed.)
Use the a= 0.1 level of significance. What can be concluded from the hypothesis test?
O A. The P-value is less than the level of significance so there is not sufficient evidence to conclude the new system is effective.
O B. The P-value is less than the level of significance so there is sufficient evidence to conclude the new system is effective.
OC. The P-value is greater than the level of significance so there is not sufficient evidence to conclude the new system is effective.
O D. The P-value is greater than the level of significance so there is sufficient evidence to conclude the new system is effective.

Critical values
Sample Size, n Critical Value
Sample Size, n Critical Value
0.880
16
0.941
ral
0.888
17
0.944
0.898
18
0.946
0.906
19
0.949
0.912
20
0.951
10
0.918
21
0.952
11
0.923
22
0.954
12
0.928
23
0.956
13
0.932
24
0.957
14
0.935
25
0.959
15
0.939
30
0.960
Print
Done
cola0 234 5

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