代做QBUS3330、c++，Python编程设计代写
- 首页 >> Python编程 QBUS3330 S2 2024 Assignment 1
Page 1
This is an individual assignment. It is worth 10% of your final grade. It consists of three
questions. Each question is worth different marks. It is due on Friday 6 September at 11:59pm
and must be submitted through Canvas using Turnitin.
The submission will comprise two separate parts:
1. A typed report (PDF please) that addresses all questions and contains images all of
relevant tables, charts and decision trees within the report.
2. An Excel file with Precision Tree enabled containing all the original tables, charts and
decision trees. The report must be able to be read as a standalone document. The
Excel file is provided for backup and corroboration purposes.
Failure to submit both files by the due date will result in late penalties being applied.
Additional instructions occur after the questions.
Question 1 (25 marks)
Motivated by the looming Paris Olympics, back in 2023 the Australian Institute of Sport (AIS)
had to decide whether to introduce mandatory drug testing for athletes. Knowing that drug
tests are not completely reliable, they want to use decision tree analysis to see whether the
benefits outweigh the costs.
Probabilities:
If an athlete is tested for a particular drug, the test result will either be positive or negative.
However, as these tests are not completely accurate some athletes who are drug free test
positive (a false positive) and some athletes who are drug users test negative (a false
negative). The best data we have available suggests that 8% of all athletes use drugs. 2.5% of
all tests on DF athletes result in false positives and 7.5% of all tests on drug using athletes
result in false negatives.
Monetary Values:
The monetary values are difficult to assess but include the following:
The benefit B from correctly identifying a drug user and banning them.
The direct cost, C1, of a test.
The cost, C2, of violating a non-users privacy by performing the test.
The cost C3, of falsely accusing a non-user and banning them.
The cost C4, of not identifying a drug user and allowing them to participate.
We measure the benefit and costs by indexing them against cost C1, which we assign a value
of minus one (-1). This does not mean the direct cost of testing an athlete is $1, it just means
that we express all other monetary values in multiples of C1. The index values are shown in
Table 1.1 on the following page.
QBUS3330 S2 2024 Assignment 1
Page 2
Table 1.1
Cost/benefit Index
C1 -1
C2 -2
C3 -20
C4 -10
B +25
Questions:
1. In Excel create two net benefit pay-off tables that map the net benefit of either testing
(four different states) or not testing (two different states) against the decision to ban
or not ban an athlete. Include the pay-off tables in your report. Note: the first table
should be expressed in index notation (+B, -C1, -C2 etc) while the second table should
state the net benefit in numerical terms based on values indicted in table 3.1. For
example, if a positive test is obtained for a non-drug user and this athlete is banned,
there are three associated costs: Cost of the test (-1), the cost of violating the athlete's
privacy (-2) and cost of falsely accusing the athlete (-50). (6 marks)
2. Calculate the relevant posterior probabilities. Include any Bayes tables generated in
Excel in your report. (4 marks)
3. Based on the values in the net benefit pay-off table and the Bayesian probabilities,
create a decision tree using Precision Tree that will help the AIS decide whether they
should implement mandatory drug testing. Note: Be careful to avoid double counting
the costs. Include your decision tree in your report. (8 marks)
4. For the given assumptions around the cost and benefit, outline the best strategy and
its net benefit and discuss this solution. (2 marks)
5. Conduct a brief sensitivity analysis giving reasons why you might change the relative
index values. Discuss how this might impact the original solution. (5 marks)
Question 2 (35 marks)
Intelligent Computing (iC) has been invited to submit by the University of Sydney s
procurement office. The contract calls for the supply of 200 generic desktop computers and
associated accessories which will be used for digital in-place exams. All vendors must fulfil the
order within 6 weeks of contract award.
Despite the urgency the contract specifications are generic and so the university has informed
all bidders that the low bid will win the contract. iC believes that the cost of preparing the bid
will be $10,000 and the cost of supplying the computers will be $190,000.
QBUS3330 S2 2024 Assignment 1
Page 3
The bids are sealed, so iC has no information about the value of the bids their competitors
will submit. However, in the last 12 months iC has managed to poach several key employers
away from vendors who are competing for the contract and so iC has a good understanding
of how the competitors may behave. In summary iC believes that the size and probability of
a low competitor bid will be as follows:
Table 2.1
Low Bid Probability
Less than $230,000 0.20
Between $230,000 - $240,000 0.40
Between $240,000 - $250,000 0.30
More than $250,000 0.10
In addition, because of supply chain constraints, iC think there is a 30% chance there will be
no rival bid.
Part A (20 marks)
1. Based on this information create a pay-off table in excel which outlines iC s most
logical bid prices against potential competitor bid options. Include relevant
probabilities. (6 marks)
2. Based on the pay-off table and any other relevant information use Precision Tree to
create a decision tree which sets out the problem. Include an image of the whole tree
in your report. (10 marks)
3. Using this decision tree, indicate the strategy that maximises EMV for iC. What is that
optimum value? (4 marks)
Part B (15 marks)
Use the sensitivity analysis function on the Precision Tree tool bar to vary the following inputs:
? Bid Preparation Costs: +/-10% in 1% increments
? Supply Cost: +/-10% in 1% increments
? No competing bid percentage: A minimum of 0% to a maximum of 60% in 5%
increments
1. Run a one-way sensitivity analysis on the entire decision tree model selecting one of
either the tornado graph or the spider graph. Include an image of the chosen graph in
your report and provide a short interpretation of the graph. (5 marks)
2. Run a second one-way sensitivity analysis on the bid value decision node (not the
entire tree) and create a strategy region graph. Include an image of the graph - that
plots the probability of no competing bids against Expected Value - in your report
along with a short interpretation of the graph. (5 marks)
QBUS3330 S2 2024 Assignment 1
Page 4
3. Run a two-way sensitivity analysis on the bid value decision node and create another
strategy region graph including an image of the graph in your report along with a short
interpretation. (5 marks)
Question 3 (40 marks)
The following table outlines the potential pay-offs for three separate investments.
Table 3.1
Investment A Investment B Investment C
Pay-off ($'000) Probability ($'000) Probability ($'000) Probability
1 18.0 10% 27.0 20% 18.0 20%
2 36.0 30% 45.0 30% 45.0 40%
3 61.0 30% 61.0 20% 72.0 20%
4 90.0 30% 99.0 30% 90.0 20%
Write a report for potential investors which ranks the three investments in terms of their
attractiveness. Your report should be approximately 500 words. All diagrams and tables used
to support your analysis should be generated in Excel using Precision Tree. As you do not
know the individual risk preferences of investors you should consider all risk types.
Other Instructions
Word count
1,000 words +/-10% excluding tables, decision trees and charts and references. Any words
beyond 1,100 will not be marked. Submissions below 900 words may be penalised.
Style
This is a business report not an essay. The report should:
- Have a suitable cover page.
- Be divided into 3 distinct sections.
- The text should be concise. Using bullet points is acceptable.
- Avoid the use of personal pronouns.
- Be professionally and logically laid out with good grammar and spelling.
- Marks will be deducted for submissions that do not meet these requirements.
QBUS3330 S2 2024 Assignment 1
Page 5
Rubric
There general rubric relating to this assignment in the Assignment 1 Canvas module where
this brief is located that provides detailed information regarding the quality expectations of
the submission.
Late penalties
Reports submitted after the due date will incur a late penalty of 5% per day or part thereof.
Reports more than 10 days late will not receive a mark.
Academic integrity
This is an individual assignment. Collaboration is permitted to help understand the questions
otherwise all written work, research and analysis needs to be your own.
The university acknowledges that most students have access to generative artificial
intelligence (AI) technologies such as ChatGPT.
Students are permitted to use artificial intelligence (AI) tools such as ChatGPT etc. to generate
material that they will then evaluate, analyse and edit for incorporation into their reports.
Students must indicate when and where AI tools have been used. AI generated text cannot
be used or represented as original, self-authored work. Failure to declare the use of AI tools
will be reported as a major breach of policy for investigation.
Students are not permitted to use artificial intelligence (AI) tools such as ChatGPT etc. to
generate material that will be submitted unevaluated and unedited as part of their report. AI
tools cannot be relied upon to generate responses that will adequately address the
requirements of the assessment. Their undeclared use will be reported as a major breach of
policy for investigation.
In line with the Academic Integrity Procedures (2022), minor breaches of academic integrity
(including poor paraphrasing, failure to acknowledge the work of others or incorrect citations)
may be subject to a penalty of up to 15% of total available marks at the point of grading.
Major breaches of the Policy will be submitted for investigation to the Faculty's Academic
Integrity staff.
Page 1
This is an individual assignment. It is worth 10% of your final grade. It consists of three
questions. Each question is worth different marks. It is due on Friday 6 September at 11:59pm
and must be submitted through Canvas using Turnitin.
The submission will comprise two separate parts:
1. A typed report (PDF please) that addresses all questions and contains images all of
relevant tables, charts and decision trees within the report.
2. An Excel file with Precision Tree enabled containing all the original tables, charts and
decision trees. The report must be able to be read as a standalone document. The
Excel file is provided for backup and corroboration purposes.
Failure to submit both files by the due date will result in late penalties being applied.
Additional instructions occur after the questions.
Question 1 (25 marks)
Motivated by the looming Paris Olympics, back in 2023 the Australian Institute of Sport (AIS)
had to decide whether to introduce mandatory drug testing for athletes. Knowing that drug
tests are not completely reliable, they want to use decision tree analysis to see whether the
benefits outweigh the costs.
Probabilities:
If an athlete is tested for a particular drug, the test result will either be positive or negative.
However, as these tests are not completely accurate some athletes who are drug free test
positive (a false positive) and some athletes who are drug users test negative (a false
negative). The best data we have available suggests that 8% of all athletes use drugs. 2.5% of
all tests on DF athletes result in false positives and 7.5% of all tests on drug using athletes
result in false negatives.
Monetary Values:
The monetary values are difficult to assess but include the following:
The benefit B from correctly identifying a drug user and banning them.
The direct cost, C1, of a test.
The cost, C2, of violating a non-users privacy by performing the test.
The cost C3, of falsely accusing a non-user and banning them.
The cost C4, of not identifying a drug user and allowing them to participate.
We measure the benefit and costs by indexing them against cost C1, which we assign a value
of minus one (-1). This does not mean the direct cost of testing an athlete is $1, it just means
that we express all other monetary values in multiples of C1. The index values are shown in
Table 1.1 on the following page.
QBUS3330 S2 2024 Assignment 1
Page 2
Table 1.1
Cost/benefit Index
C1 -1
C2 -2
C3 -20
C4 -10
B +25
Questions:
1. In Excel create two net benefit pay-off tables that map the net benefit of either testing
(four different states) or not testing (two different states) against the decision to ban
or not ban an athlete. Include the pay-off tables in your report. Note: the first table
should be expressed in index notation (+B, -C1, -C2 etc) while the second table should
state the net benefit in numerical terms based on values indicted in table 3.1. For
example, if a positive test is obtained for a non-drug user and this athlete is banned,
there are three associated costs: Cost of the test (-1), the cost of violating the athlete's
privacy (-2) and cost of falsely accusing the athlete (-50). (6 marks)
2. Calculate the relevant posterior probabilities. Include any Bayes tables generated in
Excel in your report. (4 marks)
3. Based on the values in the net benefit pay-off table and the Bayesian probabilities,
create a decision tree using Precision Tree that will help the AIS decide whether they
should implement mandatory drug testing. Note: Be careful to avoid double counting
the costs. Include your decision tree in your report. (8 marks)
4. For the given assumptions around the cost and benefit, outline the best strategy and
its net benefit and discuss this solution. (2 marks)
5. Conduct a brief sensitivity analysis giving reasons why you might change the relative
index values. Discuss how this might impact the original solution. (5 marks)
Question 2 (35 marks)
Intelligent Computing (iC) has been invited to submit by the University of Sydney s
procurement office. The contract calls for the supply of 200 generic desktop computers and
associated accessories which will be used for digital in-place exams. All vendors must fulfil the
order within 6 weeks of contract award.
Despite the urgency the contract specifications are generic and so the university has informed
all bidders that the low bid will win the contract. iC believes that the cost of preparing the bid
will be $10,000 and the cost of supplying the computers will be $190,000.
QBUS3330 S2 2024 Assignment 1
Page 3
The bids are sealed, so iC has no information about the value of the bids their competitors
will submit. However, in the last 12 months iC has managed to poach several key employers
away from vendors who are competing for the contract and so iC has a good understanding
of how the competitors may behave. In summary iC believes that the size and probability of
a low competitor bid will be as follows:
Table 2.1
Low Bid Probability
Less than $230,000 0.20
Between $230,000 - $240,000 0.40
Between $240,000 - $250,000 0.30
More than $250,000 0.10
In addition, because of supply chain constraints, iC think there is a 30% chance there will be
no rival bid.
Part A (20 marks)
1. Based on this information create a pay-off table in excel which outlines iC s most
logical bid prices against potential competitor bid options. Include relevant
probabilities. (6 marks)
2. Based on the pay-off table and any other relevant information use Precision Tree to
create a decision tree which sets out the problem. Include an image of the whole tree
in your report. (10 marks)
3. Using this decision tree, indicate the strategy that maximises EMV for iC. What is that
optimum value? (4 marks)
Part B (15 marks)
Use the sensitivity analysis function on the Precision Tree tool bar to vary the following inputs:
? Bid Preparation Costs: +/-10% in 1% increments
? Supply Cost: +/-10% in 1% increments
? No competing bid percentage: A minimum of 0% to a maximum of 60% in 5%
increments
1. Run a one-way sensitivity analysis on the entire decision tree model selecting one of
either the tornado graph or the spider graph. Include an image of the chosen graph in
your report and provide a short interpretation of the graph. (5 marks)
2. Run a second one-way sensitivity analysis on the bid value decision node (not the
entire tree) and create a strategy region graph. Include an image of the graph - that
plots the probability of no competing bids against Expected Value - in your report
along with a short interpretation of the graph. (5 marks)
QBUS3330 S2 2024 Assignment 1
Page 4
3. Run a two-way sensitivity analysis on the bid value decision node and create another
strategy region graph including an image of the graph in your report along with a short
interpretation. (5 marks)
Question 3 (40 marks)
The following table outlines the potential pay-offs for three separate investments.
Table 3.1
Investment A Investment B Investment C
Pay-off ($'000) Probability ($'000) Probability ($'000) Probability
1 18.0 10% 27.0 20% 18.0 20%
2 36.0 30% 45.0 30% 45.0 40%
3 61.0 30% 61.0 20% 72.0 20%
4 90.0 30% 99.0 30% 90.0 20%
Write a report for potential investors which ranks the three investments in terms of their
attractiveness. Your report should be approximately 500 words. All diagrams and tables used
to support your analysis should be generated in Excel using Precision Tree. As you do not
know the individual risk preferences of investors you should consider all risk types.
Other Instructions
Word count
1,000 words +/-10% excluding tables, decision trees and charts and references. Any words
beyond 1,100 will not be marked. Submissions below 900 words may be penalised.
Style
This is a business report not an essay. The report should:
- Have a suitable cover page.
- Be divided into 3 distinct sections.
- The text should be concise. Using bullet points is acceptable.
- Avoid the use of personal pronouns.
- Be professionally and logically laid out with good grammar and spelling.
- Marks will be deducted for submissions that do not meet these requirements.
QBUS3330 S2 2024 Assignment 1
Page 5
Rubric
There general rubric relating to this assignment in the Assignment 1 Canvas module where
this brief is located that provides detailed information regarding the quality expectations of
the submission.
Late penalties
Reports submitted after the due date will incur a late penalty of 5% per day or part thereof.
Reports more than 10 days late will not receive a mark.
Academic integrity
This is an individual assignment. Collaboration is permitted to help understand the questions
otherwise all written work, research and analysis needs to be your own.
The university acknowledges that most students have access to generative artificial
intelligence (AI) technologies such as ChatGPT.
Students are permitted to use artificial intelligence (AI) tools such as ChatGPT etc. to generate
material that they will then evaluate, analyse and edit for incorporation into their reports.
Students must indicate when and where AI tools have been used. AI generated text cannot
be used or represented as original, self-authored work. Failure to declare the use of AI tools
will be reported as a major breach of policy for investigation.
Students are not permitted to use artificial intelligence (AI) tools such as ChatGPT etc. to
generate material that will be submitted unevaluated and unedited as part of their report. AI
tools cannot be relied upon to generate responses that will adequately address the
requirements of the assessment. Their undeclared use will be reported as a major breach of
policy for investigation.
In line with the Academic Integrity Procedures (2022), minor breaches of academic integrity
(including poor paraphrasing, failure to acknowledge the work of others or incorrect citations)
may be subject to a penalty of up to 15% of total available marks at the point of grading.
Major breaches of the Policy will be submitted for investigation to the Faculty's Academic
Integrity staff.