Sigma Finance Assingment Help With Solution

Posted on March 16, 2017

Sigma Finance Assingment Help With Solution

 

ACCOUNTS PAYABLE SCENARIO 1

 
The following sample of 40 data points was generated from the accounts payable department during the past month.

 
It is the number of days to pay an invoice after it was received into the department. There is an internal requirement

 
(specification) that an invoice be paid between 35 and 45 days

 
40 45 40 42 42 45 44
44 43 42 40 47 38 42
41 44 42 46 38 37 42
43 47 40 41 43 39 40
44 40 46 43 42 41 42
44 46 41 45 44

 
1. Based on this data, what distribution best describes the accounts payable process?
a. Uniform
b. Gamma
c. Exponential
d. Normal
e. None of the above

 
2. Build a 95% confidence interval for a population mean
a. 41.31 <=mean <=43.44
b. 35.01 <=mean <=49374
c. 37.40 <=mean <=49.84
d. 41.58 <=mean <=43.17
e. None of the above

 
3. Historical data from the last 2 years prior to this month has established that the average time to process

 
an invoice has been 40 days. What can you say about this month's process performance with respect to the previous
two-year average?
a) This month's average is not significantly different than the historical average
b) This month's average is significantly larger than the historical average
c) This month's average is significantly less than the historical average
d) It is not possible to compare the two
e) None of the above

 
4. What is the ppk of this month's process?
a) .67
b) 1.06
c) .99
d) .35
e. None of the above
 

 

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ACCOUNTS PAYABLE SCENARIO 2

 
The accounts payable made what they think is an inprovement to the processs to reduce the time to pay an invoice.

 
The following data was collected under the "new" process

 
41 39 43 44 44
41 37 41 44 39
41 38 37 40 40
41 38 41 42 41

 
1. Perform the appropriate hypothesis test to check if the means of this new process and the old process (data from scenario#1) are significantly different

 
a) This new process average is not significantly different from the prior month's average
b) This new process average is significantly larger than the prior month's average
c) This new process average is significantly less than the prior month's average
d) It is not possible to compare the two
e) None of the above

 
2. The team also wanted to reduce the process variation. Perform the appropriate hypothesis test to check if the standard deviations are significantly different

 
a) This new process standard deviation is not significantly different from prior month's standard deviation
b) This new process standard deviation is significantly larger from prior month's standard deviation
c) This new process standard deviation is not significantly less than prior month's standard deviation
d) It is not possible to compare the two
e) None of the above

 

SOFTWARE DEVELOPMENT PROJECT SCENARIO 3

 
The total number of person-years required for a software development project needs to be estimated for the purpose of bidding on a contract.
The following date gives the total number of person-years (y) required for each of the 20 previous software development projects by this company
The independent variable (x) is the number of the application subgroups developed in that project

 
Project# x y
1 135 52
2 128 58
3 221 207
4 82 95
5 401 346
6 360 244
7 241 215
8 130 112
9 252 195
10 220 54
11 112 48
12 29 39
13 57 31
14 28 57
15 41 20
16 27 33
17 33 19
18 7 6
19 17 7
20 94 56

 
A. What is the linear regression equation between the y and the x, that is y=?
a) y = .7509 -3.4774x
b) y = .7509 +3.4774x
c) y = .7509 -3.4774
d) y = .7509 +3.4774
e) None of the above

 
B. What is the R-Squared? (Not the adjusted R-Squared)
a) .836
b) .845
c) .914
d) .919
e) None of the above

 

C. The best line estimate of the standard deviation of the predicted y-value (response) is:-
a) 89.5
b) 8007.5
c) 38.4
d) 1472.9
e) None of the above

 
D. Based on your answers to the three questions above, which statement best describes the model
a) It is a strong prediction model accounting for more than 80% of the variability in y
b) It is an extremely strong model for prediction accounting for more than 90% of the variation in y
c) It is a poor model for prediction for less than 20% of the variability in y
d) It is an extremely poor model for prediction accounting for less than 10% of the variability in y
e) Regression isnt supposed to have predictive capabilities

 

DESIGN OF EXPERIMENTS (DOE) : ENGINEERING SCENARIO 4

 
An engineer needs to improve turbine blade quality by reducing the thickness variability around a target
value of 3mm. A brainstorming sesssion identified three variables that are likely to affect the thickness.
The engineer decides to do a full factorial experiment on three factors, each at two levels
Those variables and their high and low values in the experiment are as follows:-

 
Low (-1) High (+1)
Mold Temperature 300° C 350° C
Pour Time 1 second 3 seconds
Set Time 1 minute 2 minutes

 
Due to constraints, the engineer could only run 2 replications and these are shown below with the experimental design

 
Combination Mold Temp Pour Time Set Time Y1 Y2
1 300 1 1 2.49 2.31
2 300 1 2 2.39 2.3
3 300 3 1 2.41 2.32
4 300 3 2 2.27 2.23
5 350 1 1 4.11 4.2
6 350 1 2 4.33 4.26
7 350 3 1 4.15 4.22
8 350 3 2 4.33 4.19

 
A. Which effects are significant for shifting the average or the mean value?
a) Mold Temp and Mold Temp * Pour Time interaction
b) Pour Time and Mold Temp * Pour Time interaction
c) Mold Temp and Mold Temp * Set Time interaction
d) Pour Time and Pour Time * Set Time interaction
e) None of the above

 
B. Which effects appear significant for the lowering the standard deviation? (Examine the residual plots)
a) Mold Temperature
b) Pour Time and Set Time
c) Mold Temp and Set Time
d) There are no significant effects

 
 

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