Cumulative Frequency Homework Help

Computing Cumulative Relative Frequency

Due to rounding, the answer you compute may not exactly match any of the options listed. Choose the option which comes closest to what you have computed.

Use the following data for number of widgets sold over a period of 50 days.

0	6	3	4	5
3	6	4	2	1
2	3	1	6	2
3	6	4	2	5
4	2	6	2	2
4	4	1	6	2
4	4	3	1	1
4	6	3	4	2
3	5	5	4	1
5	5	5	2	1

1) What is the cumulative relative frequency when 4 widgets are sold?

A. 0.16

B. 0.22

C. 0.5

D. 0.72

Use the following data for the next question:

12.1	18.7	4.4	5.5	16.5
5.5	13.2	3.3	8.8	9.9
6.6	6.6	13.2	20.9	3.3
16.5	13.2	16.5	0	7.7
16.5	3.3	11	8.8	11
11	8.8	17.6	19.8	14.3
13.2	7.7	3.3	20.9	20.9
12.1	13.2	12.1	17.6	9.9
7.7	15.4	17.6	16.5	7.7
1.1	0	9.9	9.9	1.1

2) What is the best class width according to the formulas in the text book:

A. 3

B. 4

C. 5

D. 6

3) What is the cumulative relative frequency of less than 12 minutes?

A. 0.20

B. 0.54

C. 0.74

D. 0.94

Z Values

4) In general, Z values will have which of the following attributes? (Best answer)

1 Positive for values above the mean.

2 Negative for values below the mean

3 Zero for values equal to the mean.

4 identifies the number of standard deviations of a particular value from the mean.

5 converts the value of x to a different set of units

6 z score has no units

A. Only 1, 2 5, 6 are true

B. Only 1, 2, 3 are true

C. All are true

D. Only 1, 2, 3, 4, 5

5) A data set of unknown distribution has a mean of 60 and a standard deviation of 7. At least how much of the data lies between 46 and 74? Hint: (Chebyshev)

A. 95%

B. 99.7%

C. 68%

D. 75%

Use this data for Questions 6-8:

	GM	Ford	Toyota	Total
car	5	14	7	26
Truck	6	1	3	10
Total	11	15	10	36

Random Probability Test

6) What is the probability that a randomly selected vehicle is either a Ford or a car?

A. 0.75

B. 0.269

C. 0.067

D. 0.690

7) What is the probability that a randomly selected vehicle is a Toyota, given it is a car?

A. 0.75

B. 0.269

C. 0.067

D. 0.690

8) What is the probability that a randomly selected vehicle is a Toyota, given it is a car?

A. 0.75

B. B.0.269

C. 0.067

D. 0.69

Binomial Probability Distribution

9) Consider a binomial probability distribution with p=0.35 and n=8. What is the probability of fewer than three successes?

A. 0.137

B. 0.258

C. .4278

D. .0318

10) Consider a binomial probability distribution with n=8, p=.35 calculate the probability of P(x>1)?

A. 0.0476

B. 0.8308

C. 0.3571

D. 0.4770

11) What is the expected mean of the amount of time spent on social media, assuming a uniform distribution of between 85 and 110 minutes?

A. 97.5

B. 99.8

C. 88.5

D. 100.1

12) An exponential probability has a  equal to 24 customers per hour. What is the probability a customer will arrive within the next 30 seconds?

A. 0.2389

B. 0.1813

C. 0.1940

D. 0.1834

Use the data below to develop a p-chart to answer questions 13 and 14

The data is from a local pizza parlor. Each day the management sampled 25 pizzas to see if they met the quality requirements of the business, making sure that the order had been fulfilled properly. The table below shows the number of pizzas that did not pass the quality check.

Day	Sample Size	Pizza's with Quality Issues
1	25	2
2	25	1
3	25	3
4	25	2
5	25	1

13. What is the value of ?

A. 28

B. 7

C. 07

D. 4

14. What are the values of the UCL and the LCL

A. 194 and -0.082

B. 46 and 0 (LCL does not exist)

C. 056 and 0.006

D. 227 and 0 (LCL does not exist)

Use the following data to construct a c-chart to answer questions 15 and 16.

The data below represents the number of complaints recorded the customer service desk at a local call center. The data shows the number of complaints logged each day over a seven day period.

Day	Complaints Received
1	8
2	2
3	3
4	3
5	2
6	1
7	2

15) What is the upper control limit of the c-chart?

A. 10.856

B. 8.196

C. 2.714

D. 1.647

16) Which of the following are true about the process?

A. Special causes of variation are indicated

B. There are only common causes of variation

C. The process is not in control

D. Process is in control.

Use the following data to answer questions 17-19.

An assembly line pouring cereal into boxes pulls samples once an hour. In the chart below is the summary of ten boxes that are sampled each hour, including the mean weight of each sample and the range between the heaviest and lightest box of the sample. The table shows the results for a 6 hour period. All weights are recorded in ounces.

Hour	Mean weight	Range
1	15.1	0.13
2	14.8	0.09
3	15.0	0.15
4	14.9	0.06
5	15.0	0.21
6	14.9	0.08

17.What is the UCL and LCL of the control chart?

986 and 14.913
792 and 13.008
892 and 12.108
751 and 11.149

18. What is the UCL of the range control chart?

1405
2132
1746
3600

19. What did we learn about the process from the control charts?

The range is in control so the entire process is in control
The mean is in control
Special causes of variation are present for the process range.
Special causes of variation are present for the process mean

Use this following information to answer questions 20-21:

The following sample data taken from the “Back of the Bike” ice cream company, and. contains the temperature (Temp.) and the number of boxes of ice cream sold (#boxes):

Temp.	# boxes
67	12
73	17
88	28
102	33

20) Compute the regression line to estimate number of ice cream boxes sold.

A. Y = 67 + 27.23X

B. Y = 33.52 + 21.2X

C. Y=-27.60+ 0.61X

D. Y = -43.52 + 4.5X

21) The correlation coefficient is

A. 0.58

B. 0.33

C. 0.76

D. 0.99

Use this information for Questions 22 – 26.

Sample data (as shown below) was collected on the weight of 5 vehicles (in lbs.) and associated fuel efficiency in Miles Per Gallon (MPG). The following is a partial Excel output that was reported.

partial Excel output

22) What is the correlation coefficient for these variables?

A. 0.983

B. -0.984

C. 0.911

D. -0.911

E. 0.898

23) What is the regression equation?

A. Y = 7 + 1X

B. Y = 1 + 7X

C. Y = -1.38 + 99.3X

D. Y= 43.28 - 0.0063X

24) What can you say about the relationship between the weight of the vehicle and MPG?

A. 96.9% of variability in the MPG can be explained by the weight of the vehicle

B. 96.6% of variability in the weight of the vehicle can be explained by the MPG

C. 95.4% of variability in the MPG can be explained by the weight of the car

D. 95.4% of variability in the weight of the car can be explained by the MPG

25) What is the Standard Error?

A. 1.42

B. 2.32

C. 6.74

D. Cannot be computed

26) What is the SST?

A. 400.7

B. 170.7

C. 503.4

D. 521.2

Use the following data for problems 27 - 30

Month	Sales
Jan	45
Feb	48
Mar	46
Apr	47
May	49
June

27) Using a two month moving average, what is the forecast for June?

A. 47.0

B. 30.5

C. 49.5

D. 48.0

28) Using a three month weighted moving average, compute a forecast for June with weights of 0.1, 0.4, and 0.5 (oldest data to newest data, respectively).

A. 32.3

B. 47.9

C. 48.9

D. 47.2

Exponential Smoothing

29) Using exponential smoothing, with an alpha value of 0.3 and assuming the forecast for April is 44.0, what is the forecast for June?

A. 44.2

B. 48.2

C. 47.0

D. 46.9

30) What is the MAD value for the two month moving average?

A. 1.8

B. 1.0

C. 2.5

D. 3.0

31) You are examining four different forecasts and have calculated the following MAD levels:

• 2 Month moving average = 2.5

• 3 Month moving average = 1.5

• Exponential smoothing = 1.7 and

• Exponential Smoothing with Trend = 1.9

Which forecast is best?

A. 2 Month Moving Average

B. 3 Month Moving Average

C. Exponential Smoothing

D. Exponential Smoothing with Trend

Use the following data for problems 32 and 33

The table below shows sales (in thousands) for each quarter of the last three years

	QTR1	QTR2	QTR3	QTR4
Year 1	11.5	7.2	5.1	14.2
Year 2	12.5	8.1	5.7	16.2
Year 3	13.8	9.0	6.2	17.8

32) What is the seasonal index for QTR4?

A. 0.25

B. 0.38

C. 0.17

D. 0.15

33) Using time series analysis, what is the forecast for QTR2 of the fifth year of sales?

A. 10.6

B. 55.6

C. 21.1

D. 8.1

Use the following information to answer Questions 34-37. Use space below for the network.

The table shown, below, reports a project’s activity times (in days) and precedence relationships.

activity	Time (days)	Predecessors
A	5	NONE
B	6	NONE
C	4	A, B
D	15	A, B
E	16	A, B
F	8	C, D
G	11	C, D
H	9	E
I	7	F, G, H
J	4	F, G, H

34) What is your estimate of completion time for this project?

A. 26 days

B. 44 days

C. 39 days

D. 36 days

35) What is the critical path?

A. B, D, G, I

B. B, D, G, J

C. A, C, E, F, H, J

D. A, E, H

36) What is the Earliest Start (ES) time for activity G?

A. 10

B. 11

C. 21

D. 25

37) What is the slack for activity D?

A. 0 days

B. 1 day

C. 2 days

D. 3 days

Use the following information about a PERT project to answer question 38-39.

Times are in days. Assume only one critical path exists which is: A, E, F

Activity	optimistic	Most likely	pessimistic
A	4	5	12
B	9	12	15
C	2	5	7
D	15	17	25
E	7	10	13
F	3	5	8

38) What is the expected project completion time? Round off to the nearest integer.

A. 21 days

B. 19 days

C. 23 days

D. 53 days

39) What is the standard deviation of activity F?

A. 1.86 days

B. 0.83 days

C. 0.69 days

D. 3.47 days

Use the two POM crashing windows which appear on the next page to answer Question 40. Times are in days.

40) You are given a bonus of $1,750/day the project is complete early. What day will you complete the project to maximize your total bonus?

A. 59 Days

B. 56 Days

C. 53 Days

D. 50 Days

Use with Questions 39 and 40
Activity	Normal time	Crash time	Normal Cost	Crash Cost	Crash cost/pd	Crash by	Crashing cost
Project	59	46
A	15	12	15000	20000	1666.67	3	5000
B	9	6	18000	26000	2666.67	0	0
C	13	10	29000	40000	3666.67	3	11000
D	10	8	10000	12000	1000	0	0
E	8	5	20000	30000	3333.33	0	0
F	9	6	12000	15000	1000	3	3000
G	4	1	20000	24000	1333.33	0	0
H	12	10	36000	40000	2000	2	4000
I	10	7	5000	8000	1000	0	0
J	6	5	4000	8000	4000	1	4000
K	4	3	16000	20000	4000	1	4000
TOTALS			185000				31000

Use with Questions 39 and 40
Project time	Period cost	Cumulative cost	A	B	C	D	E	F	G	H	I	J	K
59	0	0
58	1000	1000						1
57	1000	2000						2
56	1000	3000						3
55	1666.67	4666.67	1					3
54	1666.67	6333.33	2					3
53	1666.67	8000	3					3
52	2000	10000	3					3		1
51	2000	12000	3					3		2
50	3666.67	15666.67	3		1			3		2
49	3666.67	19333.33	3		2			3		2
48	3666.67	23000	3		3			3		2
47	4000	27000	3		3			3		2		1
46	4000	31000	3		3			3		2		1	1

Cumulative Relative Frequency Homework Help Online

Computing Cumulative Relative Frequency

Random Probability Test

Binomial Probability Distribution

Use the data below to develop a p-chart to answer questions 13 and 14

Use the following data to construct a c-chart to answer questions 15 and 16.

Use this following information to answer questions 20-21:

Use this information for Questions 22 – 26.

Use the following data for problems 27 - 30

Exponential Smoothing