Mindtap Business Analytics, 1 Term (6 Months) Printed Access Card For Camm/cochran/fry/ohlmann/anderson/sweeney/williams' Essentials Of Business Analytics, 2nd
2nd Edition
ISBN: 9781305861794
Author: Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann, David R. Anderson
Publisher: Cengage Learning
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Chapter 2, Problem 21P
Return to the waiting times given for the physician’s office in Problem 19.
- a. Considering only offices without a wait-tracking system, what is the z-score for the 10th patient in the sample (wait time 5 37 minutes)?
- b. Considering only offices with a wait-tracking system, what is the z-score for the 6th patient in the sample (wait time 5 37 minutes)? How does this z-score compare with the z-score you calculated for part a?
- 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 without a wait-tracking system contain any outliers?
19. Suppose that the average waiting time for a patient at a physician’s office is just over 29 minutes. 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 (in 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 such systems.
- a. What are the
mean andmedian patient wait times for offices with a wait-tracking system? What are the mean and median patient wait times for offices without a wait-tracking system? - b. What are the variance and standard deviation of patient wait times for offices with a wait-tracking system? What are the variance and standard deviation of patient wait times for visits to offices without a wait tracking system?
- c. Create a box plot for patient wait times for offices without a wait-tracking system.
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Theorem 2.6 (The Minkowski inequality)
Let p≥1. Suppose that X and Y are random variables, such that E|X|P <∞ and
E|Y P <00. Then
X+YpX+Yp
Theorem 1.2 (1) Suppose that P(|X|≤b) = 1 for some b > 0, that EX = 0, and
set Var X = 0². Then, for 0 0,
P(X > x) ≤e-x+1²²
P(|X|>x) ≤2e-1x+1²²
(ii) Let X1, X2...., Xn be independent random variables with mean 0, suppose
that P(X ≤b) = 1 for all k, and set oσ = Var X. Then, for
x > 0.
and
0x) ≤2 exp
Σ
k=1
(iii) If, in addition, X1, X2, X, are identically distributed, then
P(S|x) ≤2 expl-tx+nt²o).
Theorem 5.1 (Jensen's inequality)
state without proof the Jensen's Ineg.
Let X be a random variable, g a convex function, and suppose that X and g(X) are
integrable. Then
g(EX) < Eg(X).
Chapter 2 Solutions
Mindtap Business Analytics, 1 Term (6 Months) Printed Access Card For Camm/cochran/fry/ohlmann/anderson/sweeney/williams' Essentials Of Business Analytics, 2nd
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