Jones_Quinel_waittime2
pdf
keyboard_arrow_up
School
Ohio University, Main Campus *
*We aren’t endorsed by this school
Course
1500
Subject
Industrial Engineering
Date
Dec 6, 2023
Type
Pages
3
Uploaded by CommodoreNeutronRat8
Name:
Wait time lab 2
Instructions: Follow the steps below carefully. Submit a pdf version of your work using the
convention:
Lastname_Firstname_waittime2.pdf
Elias is a branch manager at a local bank. Recently, he has been receiving customer feedback
saying that the wait times are too long. Management has set a goal that wait times should not
average more than 35 seconds. Elias decides to observe and write down the time spent by
customers waiting in line. The file
wait_time2
contains his observations of wait times (in
seconds) on three different days (N=21 for each day): the Friday before Labor Day, the
following Wednesday, and the next Monday.
Elias would like to analyze the data by making a histogram and calculating some measures of
center and spread.
a)
In Tableau, open the file and create a box plot for each day. Remember to the Analysis tab at the
top of the pane and unse
lect the ‘Aggregate Measures’ option.
Label the 1
st
Quartile, 2
nd
Quartile (i.e., the median), and the 3
rd
Quartile by right clicking on the y-
axis and selecting ‘Add
reference line.’ Select ‘distribution’
and ‘per cell’ for scope. Under ‘Value’ choose ‘Quantile’ and
leave the number at 4. Under formatting, choose ‘None’ for both line and fill.
(This process will
inlay another distribution on top of the boxplot. To remove it, click on the shaded area and a
formatting pane will appear to the left. Select ‘no
fill’ under ‘fill’ for the Reference Distribution.
Also label the min and max (you must do each separately) by right clicking on the y-axis, adding
a reference line, choosing ‘per cell’ and
selecting the appropriate measure in the drop-down
menu. Paste a snap shot of your box plots below.
b)
Are there any outliers on any days? Explain.
Yes, there are outliers on all of them because for each day the wait time will be different
depending on what time of day it is. For example, the outlier on Monday is 26.02, whereas on
Wednesday, the outlier is 12.52.
c)
In excel, manually (i.e., do not use the canned formula) calculate the total sample average and
the sample average for each day and include here.
Total sample average- 30.6643
Monday- 32.7
Wednesday- 17.4
Friday- 41.8857
d)
Also in excel, manually calculate the overall sample standard deviation and the standard
deviation for each day and include here.
Sample- 11.2906
Monday- 3.68864
Wednesday- 1.77169
Friday- 7.48059
e)
Calculate the coefficient of variation = (sample standard deviation)/(sample mean) (overall and
for each day) and comment on the relative variability. What explains the differences between
days?
Does Elias need to make major changes to meet management’s expectations?
What do
we learn about the importance of variability and sample size?
Sample- 0.36820015
Monday- 0.11280245
Wednesday- 0.1182126
Friday- 0.17859532
I would say that Elias needs to make major changes to meet managements expectations so that way the
overall wait time wouldn
’
t be large, and so the coefficient variations can be adjusted accordingly. With
this experiment, we learn the importance of variability and sample size by seeing how it can be related
to reality and how this can be applied in the real world.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help