Respuesta :
Answer:
See Explanation and attachments
Step-by-step explanation:
Given
See question for data
Solving (a):
The scale used is an ordinal scale.
Ordinals scale uses hierarchy arrangement and the data can be arranged as:
[tex]EARLY ->> ON-TIME ->> LATE ->> LOST[/tex]
The variable of the delivery performance is qualitative because it is non-numerical
Solving (b): Frequency table
From the table, we have:
[tex]On - Time = 57[/tex] [tex]Early = 19[/tex] [tex]Late = 9[/tex] [tex]Lost = 2[/tex]
So, the frequency distribution table is:
[tex]\begin{array}{cc}{Performance}&{Frequency}&{On-Time}&{57}&{Early}&{19}&{Late}&{9} & {Loss} & {2} & {Total} & {87}\end{array}[/tex]
Solving (c): Frequency table.
To do this, we add another column (Relative Frequency) to the above table.
The relative frequency is calculated as:
[tex]Relative\ Frequency = \frac{Frequency}{Total}[/tex]
So, we have:
[tex]On - Time = \frac{57}{87} = 0.656[/tex] [tex]Early = \frac{19}{87} = 0.218[/tex]
[tex]Late = \frac{9}{87} = 0.103[/tex] [tex]Lost = \frac{2}{87} = 0.023[/tex]
So, the frequency distribution table is:
[tex]\begin{array}{ccc}{Performance}&{Frequency}&{Relative\ Frequency} & {On-Time}&{57}&{0.656}&{Early}&{19}&{0.218} & {Late}&{9} & {0.103} & {Loss} & {2} & {0.023} & {Total} & {87}&{1}\end{array}[/tex]
Solving (d & e): See attachment 1 for bar chart & attachment 2 for pie chart
Solving (f):
From the question, we understand that the object is to return 99% early or on time and never to lose a package.
The analysis is as follows:
Early and On-Time (ET) packages
[tex]ET = \frac{Early + On-Time}{Total} * 100\%[/tex]
[tex]ET = \frac{57 + 19}{87} * 100\%[/tex]
[tex]ET = \frac{76}{87} * 100\%[/tex]
[tex]ET = \frac{7600}{87} \%[/tex]
[tex]ET = 87.4 \%[/tex]
Lost packages
[tex]Lost = \frac{Lost}{Total} * 100\%[/tex]
[tex]Lost = \frac{2}{87} * 100\%[/tex]
[tex]Lost = \frac{200}{87} \%[/tex]
[tex]Lost = 2.30\%[/tex]
From the above analysis, we can see that 87.4% of the packages were delivered early enough and 2.30% were lost.
The fraction of packages delivered early can be improved and the fraction of lost packages can be reduced by exploring the chances of taking alternative routes when possible.

