Is the data discrete or continuous? Suppose the inter-arrival times for 10 people waiting for service...
Is the data discrete or continuous?
Suppose the inter-arrival times for 10 people waiting for service at the supermarket checkout is as shown. Note intervals 3.
| Sample | Inter-arrival |
|
1 |
73 |
| 2 | 18 |
| 3 | 20 |
| 4 | 60 |
| 5 | 99 |
| 6 | 81 |
| 7 | 40 |
| 8 | 33 |
| 9 | 27 |
| 10 | 22 |
Homework Answers
The data is continuous because inter arrival time can take any value within a specific interval.
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Is the data discrete or continuous?
Suppose the inter-arrival times for 10 people waiting for
service...
Question 2 Customers arrive at the checkout counter (shown in the figure below) at random from 1 to 8 minutes apart. Each possible value of inter-arrival time has the same probability of occurren...
Question 2 Customers arrive at the checkout counter (shown in the figure below) at random from 1 to 8 minutes apart. Each possible value of inter-arrival time has the same probability of occurrence, as shown in Table 2.6. The service times vary from 1 to 6 minutes with the probabilities shown in Table 2.7. Departure Arrival Checkout Counter Table 26 Distribution of TIme Between Amivals Time baweerm Arrivals Table 27 Service-Time Distribution Minutesy) Prohablity Service Tme 0.125 0.125 0.125 125...
4. The data below are waiting times (in minutes) for service at a local bank. Also...
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A critically important aspect of customer service in a supermarket is the waiting time at the...
A critically important aspect of customer service in a supermarket is the waiting time at the checkout (defined as the time the customer enters the line until he or she is served). Data were collected during time periods in which a constant number of checkout counters were open. The total number of customers in the store and the waiting time (in minutes) were recorded. . Determine the coefficient of determination, r 2 , and interpret its meaning. 6. How useful...
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RANGES FREQUENCY RELATIVE FREQUENCY CUMULATIVE REL. FREQ. 1 - 10 11 - 20 21 - 30 31 - 40...
RANGES
FREQUENCY
RELATIVE FREQUENCY
CUMULATIVE REL. FREQ.
1 - 10
11 - 20
21 - 30
31 - 40
41 - 50
51 - 60
61 - 70
71 - 80
81 - 90
91 - 100
'= 100 DATA
VALUES??
SO, WHAT DOES A FREQUENCY TABLE TELL US?
If
you wrote each of the above data values on a ping pong ball,, put
them in a jar and blindly pulled one out:
What is the probability that this ball...
Discrete vs. Continuous Random Variable: You will notice that there is most ikely no mode for...
Discrete vs. Continuous Random Variable: You will notice that there is most ikely no mode for the sample data set presented in Table 1. The reason there are not multiple instances of exactly the same value of the random variable is due to the continuous nature of the random variable. Continuous random variables are random variables whose value can take on infinitely many values- the value of which is typically governed by the precision of the device used to measure...
1. Generally speaking, which of the following is NOT a common feature of a service organization?...
1. Generally speaking, which of the following is NOT a common feature of a service organization? a. Quality is not easy to measure in service processes b. Customers are more involved in service processes c. Service processes have less variability d. Satisfaction in services is subjective 2. Which of the following is NOT an assumption made in the queueing model discussed in class? a. The arrival rate can be larger than the service rate b. There is infinite waiting room...
Ques 3 (d) Suppose that n-10, and Xi Xio represent the waiting times that the 10...
Ques 3
(d) Suppose that n-10, and Xi Xio represent the waiting times that the 10 people must wait at a bus stop for their bus to arrive. Interpret the result of (c) in the context of this scenario be iid observations from the Uniform(0,0) distribution. 3. Again, let X..., X (a) Find the joint pdf of Xu) and X() (b) Define R = X(n)-X(1) as the sample range. Find the pdf of R. (e) It turns out, if X...
Question 2 Customers arrive at the checkout counter (shown in the figure below) at random from 1 to 8 minutes apart. Each possible value of inter-arrival time has the same probability of occurrence, as shown in Table 2.6. The service times vary from 1 to 6 minutes with the probabilities shown in Table 2.7. Departure Arrival Checkout Counter Table 26 Distribution of TIme Between Amivals Time baweerm Arrivals Table 27 Service-Time Distribution Minutesy) Prohablity Service Tme 0.125 0.125 0.125 125...
4. The data below are waiting times (in minutes) for service at a local bank. Also included are son summary statistics produced by Excel. Waiting Time Waiting Time Statistics 2.7 3.6 Mean 3.82 1.5 Standard Error 0.61 4.9 Median 3.00 2.8 Mode 2.70 Standard Deviation 2.21 Sample Variance 4.89 Kurtosis 7.79 Skewness 2.55 Range 9.00 Minimum 1.50 Maximum Sum 49.60 Count 13.00 27 4.1 10.50 (Continued) Refer to the bank waiting times data on the previous page. b. Using the...
. Discrete Distributions. Suppose I flip a coin 40 times. The flips are independent. The probability the coin will come up heads is 40% at each flip. Let X be the number of heads observed in the 40 flips. 26. What is the expected value of X? 27. What is the variance of X? 28. What is P(X 18)? 29. What is P(X 2 18) 30. Using the normal approximation to the binomial with the conti 31. Is the normal...
RANGES
FREQUENCY
RELATIVE FREQUENCY
CUMULATIVE REL. FREQ.
1 - 10
11 - 20
21 - 30
31 - 40
41 - 50
51 - 60
61 - 70
71 - 80
81 - 90
91 - 100
'= 100 DATA
VALUES??
SO, WHAT DOES A FREQUENCY TABLE TELL US?
If
you wrote each of the above data values on a ping pong ball,, put
them in a jar and blindly pulled one out:
What is the probability that this ball...
Discrete vs. Continuous Random Variable: You will notice that there is most ikely no mode for the sample data set presented in Table 1. The reason there are not multiple instances of exactly the same value of the random variable is due to the continuous nature of the random variable. Continuous random variables are random variables whose value can take on infinitely many values- the value of which is typically governed by the precision of the device used to measure...
Ques 3
(d) Suppose that n-10, and Xi Xio represent the waiting times that the 10 people must wait at a bus stop for their bus to arrive. Interpret the result of (c) in the context of this scenario be iid observations from the Uniform(0,0) distribution. 3. Again, let X..., X (a) Find the joint pdf of Xu) and X() (b) Define R = X(n)-X(1) as the sample range. Find the pdf of R. (e) It turns out, if X...
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