Suppose that the average waiting time for a patient at a physician's office is just over 29 minutes. In order to address the issue of long patient wait times, some physicians' offices are using wait-tracking systems to notify patients of expected wait times. Patients can adjust their arrival times based on this information and spend less time in waiting rooms. The following data show wait times (minutes) for a sample of patients at offices that do not have a wait-tracking system and wait times for a sample of patients at offices with a wait-tracking system. Without Wait- Tracking System With Wait-Tracking System 20 8 56 12 12 11 35 16 26 32 48 36 16 8 10 9 27 15 36 5 (a) Considering only offices without a wait-tracking system, what is the z-score for the 10th patient in the sample (wait time = 36 minutes)? If required, round your intermediate calculations and final answer to two decimal places. z-score = (b) Considering only offices with a wait-tracking system, what is the z-score for the 6th patient in the sample (wait time = 36 minutes)? If required, round your intermediate calculations and final answer to two decimal places. z-score = How does this z-score compare with the z-score you calculated for part (a)? The input in the box below will not be graded, but may be reviewed and considered by your instructor. (c) Based on z-scores, do the data for offices without a wait-tracking system contain any outliers? Based on z-scores, do the data for offices with a wait-tracking system contain any outliers?
Contingency Table
A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.
Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
Suppose that the average waiting time for a patient at a physician's office is just over 29 minutes. In order to address the issue of long patient wait times, some physicians' offices are using wait-tracking systems to notify patients of expected wait times. Patients can adjust their arrival times based on this information and spend less time in waiting rooms. The following data show wait times (minutes) for a sample of patients at offices that do not have a wait-tracking system and wait times for a sample of patients at offices with a wait-tracking system.
Without Wait- Tracking System |
With Wait-Tracking System |
20 | 8 |
56 | 12 |
12 | 11 |
35 | 16 |
26 | 32 |
48 | 36 |
16 | 8 |
10 | 9 |
27 | 15 |
36 | 5 |
(a) | Considering only offices without a wait-tracking system, what is the z-score for the 10th patient in the sample (wait time = 36 minutes)? |
If required, round your intermediate calculations and final answer to two decimal places. | |
z-score = | |
(b) | Considering only offices with a wait-tracking system, what is the z-score for the 6th patient in the sample (wait time = 36 minutes)? |
If required, round your intermediate calculations and final answer to two decimal places. | |
z-score = | |
How does this z-score compare with the z-score you calculated for part (a)? | |
The input in the box below will not be graded, but may be reviewed and considered by your instructor. | |
|
|
(c) | Based on z-scores, do the data for offices without a wait-tracking system contain any outliers? |
Based on z-scores, do the data for offices with a wait-tracking system contain any outliers? | |
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