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kondaur [170]
4 years ago
15

The following lists show the free throw percentages of 16 players for the Detroit Pistons and Miami Heat during the 2012-2013 NB

A season. Detroit Pistons: 0.69, 0.73, 0.80, 0.89, 0.78, 0.81, 0.81, 0.37, 0.77, 0.62, 0.55, 0.84, 0.75, 0.83, 0.30, 0.72 Miami Heat: 0.75, 0.72, 0.81, 0.76, 0.90, 0.75, 0.82, 0.67, 0.72, 0.72, 0.57, 1.00, 0.56, 0.50, 0.50, 1.00 Calculate the median and interquartile range for each set of data. Make sure to label your calculations. Compare the data sets using your calculations from part 1. Write your answer in complete sentences.
Mathematics
1 answer:
Alina [70]4 years ago
8 0

Answer:

the data of the detroit pistons in numerical order from least to greatest is 0.30, 0.37, 0.55, 0.62, 0.69, 0.72, 0.73, 0.75, 0.77, 0.78, 0.80, 0.81, 0.81, 0.83, 0.84, 0.89

the data of the miami heat in numerical order from least to greatest is 0.50, 0.50, 0.56, 0.57, 0.67, 0.72, 0.72, 0.72, 0.75, 0.75, 0.76, 0.81, 0.82, 0.90, 1.00, 1.00

the detroit pistons median : 1.52

the miami heat median: 1.47

the iqr of this data is 0.05

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A new shopping mall is considering setting up an information desk manned by one employee. Based upon information obtained from s
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a) P=1-\frac{\lambda}{\mu}=1-\frac{20}{30}=0.33 and that represent the 33%

b) p_x =\frac{\lambda}{\mu}=\frac{20}{30}=0.66

c) L_s =\frac{20}{30-20}=\frac{20}{10}=2 people

d) L_q =\frac{20^2}{30(30-20)}=1.333 people

e) W_s =\frac{1}{\lambda -\mu}=\frac{1}{30-20}=0.1hours

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Step-by-step explanation:

Notation

P represent the probability that the employee is idle

p_x represent the probability that the employee is busy

L_s represent the average number of people receiving and waiting to receive some information

L_q represent the average number of people waiting in line to get some information

W_s represent the average time a person seeking information spends in the system

W_q represent the expected time a person spends just waiting in line to have a question answered

This an special case of Single channel model

Single Channel Queuing Model. "That division of service channels happen in regards to number of servers that are present at each of the queues that are formed. Poisson distribution determines the number of arrivals on a per unit time basis, where mean arrival rate is denoted by λ".

Part a

Find the probability that the employee is idle

The probability on this case is given by:

In order to find the mean we can do this:

\mu = \frac{1question}{2minutes}\frac{60minutes}{1hr}=\frac{30 question}{hr}

And in order to find the probability we can do this:

P=1-\frac{\lambda}{\mu}=1-\frac{20}{30}=0.33 and that represent the 33%

Part b

Find the proportion of the time that the employee is busy

This proportion is given by:

p_x =\frac{\lambda}{\mu}=\frac{20}{30}=0.66

Part c

Find the average number of people receiving and waiting to receive some information

In order to find this average we can use this formula:

L_s= \frac{\lambda}{\lambda -\mu}

And replacing we got:

L_s =\frac{20}{30-20}=\frac{20}{10}=2 people

Part d

Find the average number of people waiting in line to get some information.

For the number of people wiating we can us ethe following formula"

L_q =\frac{\lambda^2}{\mu(\mu-\lambda)}

And replacing we got this:

L_q =\frac{20^2}{30(30-20)}=1.333 people

Part e

Find the average time a person seeking information spends in the system

For this average we can use the following formula:

W_s =\frac{1}{\lambda -\mu}=\frac{1}{30-20}=0.1hours

Part f

Find the expected time a person spends just waiting in line to have a question answered (time in the queue).

For this case the waiting time to answer a question we can use this formula:

W_q =\frac{\lambda}{\mu(\mu -\lambda)}=\frac{20}{30(30-20)}=0.0667 hours

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