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You collated a dataset from existing literature summarizing observed daytime col

You collated a dataset from existing literature summarizing observed daytime collision rates (bpt y-1 = birds per turbine per year) at individual wind farms across Europe that varied in number and density of turbines. All observations were recorded by daytime visual observation during the summer.
Using the data in sheet 2, fit a simple GLM to test if collision rate differed between the species groups. Then plot and analyse the data to determine whether collision rate was influenced by wind farm size and/or turbine density. Your analysis should initially be done for the two species groups separately fitting a model of the form:
bpt = nt + dt,
where nt = number of turbines and dt = density of turbines (km-2).
You can then do an analysis with both species together using the model:
bpt = nt + dt + spp
where spp = species group.
However this does not allow you to test rigorously whether the effect of nt on bpt, or of dt on bpt, is the same for both species. To do this, you must fit another model with the appropriate interactions:
bpt = nt + dt + spp + (nt x spp) + (dt x spp)
Explain the behavioural and ecological reasons for the patterns observed, and what these results mean for the way windfarms should be designed generally.
Support your answers using clearly labelled figures (with 1-2 sentence legends) and using appropriate statistical analyses.
Please hand in your write-up to the office by stated deadline. Maximum 3 pages including figures, but you can put model outputs in Appendices which you can refer to in the text. Keep figures small and label all axes clearly with correct name and units

Introduction As we learned from the Tufte book, the issue with visualization of

Introduction
As we learned from the Tufte book, the issue with visualization of

Introduction
As we learned from the Tufte book, the issue with visualization of time series is that time does not always represent the cause. The book suggested few ways to improve data series visualizations. One is to introduce another variable(s) that would also be changing in time and demonstrate the cause of the change in the reporting variable. If the change occurs ones or small number of times, the time series can be visualized as before-after or a set of images representing the state after each change. Directions
You will be asked to sketch a data series visualization using either a pen (then scan or photo the results) or any software for drawing on your computer. You may also use any other tool to draw the chart (e.g. Excel, Tableau), but it is not required.
The source link can be found at ( https://www.kaggle.com/datasets/yingwurenjian/chicago-divvy-bicycle-sharing-data) and it will provide you data of a daily use of Chicago bike sharing system (Divvy) for October-December 2017. This dataset also includes some weather information for the same period.
Make a preliminary analysis of the relation between weather data and the number of rides. Select at least one weather variable that has the strong effect on the number of rides.
Choose an appropriate type of visualization. Sketch a visualization of the use of the bike sharing systems over time explaining at least two reasons for the number’s fluctuation from day to day.
The sketch does not have to show all data points, but it has to give an idea of the causes of fluctuations.
Provide commentary explaining what effects and how did you illustrate with your sketch.
STUDENT REMARKS: I have already drafted the content for this assignment; however, I need assistance with creating the diagrams/charts. Please see the attachment.

You collated a dataset from existing literature summarizing observed daytime col

1.ABCD company is an office equipment company that produces two types of desks:

1.ABCD company is an office equipment company that produces two types of desks: standard and deluxe. Deluxe desks have oak tops, more expensive hardware and require additional time for finishing and polishing. Standard desks require 80 square feet of pine and 10 hours of labor, while deluxe desks require 60 square feet of pine, 18 square feet of oak, and 16 hours of labor. For the next week, the company has 5,000 square feet of pine, 750 square feet of oak, and 400 hours of labor available. Standard desks net a profit of $150, while deluxe desks net a profit of $320. All desks can be sold to national chains shops.
Instructions:
Develop a linear optimization model to determine how many of each type of desk the ABCD company should make next week to maximize profit contribution [Assume: S = units of standard desk produced and D = units of deluxe desk produced. No need to solve the model, neither graphically nor by Solver: just develop the mathematical model for this part]
2.ABCD company is an office equipment company that produces two types of desks: standard and deluxe. Deluxe desks have oak tops, more expensive hardware, and require additional time for finishing and polishing. Standard desks require 80 square feet of pine and 10 hours of labor, while deluxe desks require 60 square feet of pine, 18 square feet of oak, and 16 hours of labor. For the next week, the company has 5,000 square feet of pine, 750 square feet of oak, and 400 hours of labor available. Standard desks net a profit of $150, while deluxe desks net a profit of $320. All desks can be sold to national chains shops.
Instructions:
If the spreadsheet and Excel Solver results are given to you as follows (see Table 1 below), address the following questions:
What are your Binding Constraints?
What is your Optimum profit [hint: maximized profit]?
What are your slack values for Pine, Oak, and Labor?
Looking at the Shadow prices, how much would the objective profit increase by if you were to increase labor hours by 50?
If the optimum solution for standard desk stays the same, but deluxe desk numbers increased, what would be your estimated deluxe desks in this case? Would you recommend this option? Why? Hints: Notice that by increasing labor hours by 50, the S stays as an original optimum solution given in the information of Solver, but D will increase. The question is asking you to find how much the objective profit would go up and what would be the estimated number for D [calculated from your constraints. Decimal number is accepted].
What would be the changes in objective profit $, if we increase the Pine by one unit and the Oak by one unit, i.e., Pine available=5001 and Oak available=751.
What % of available Oak can be reduced without it affecting the current (given) optimum solution?
What % of available Pine can be reduced without affecting the current (given) optimum solution?
How much should the standard desk unit profit of $150 be increased by in order for Standard desks to be produced (i.e. become a positive number)?
Given results after developing the excel LP and Solver:
Excel program
Standard
Deluxe
Availability
Pine
80
60
5000
Oak
0
18
750
Labor
10
16
400
Profit/unit
$150
$320
Number produced
0
25.0
Total (per week)
Profit contribution
$0
$8,000
$8,000
Amount Used
Pine
1500
Oak
450
Labor
400
Solver Sensitivity Report:
Variable Cells
Final
Reduced
Objective
Allowable
Allowable
Cell
Name
Value
Cost
Coefficient
Increase
Decrease
$B$21
Number produced Standard
0
-50
150
50
1E+30
$C$21
Number produced Deluxe
25
0
320
1E+30
80
Solver Constraints
Final
Shadow
Constraint
Allowable
Allowable
Cell
Name
Value
Price
R.H. Side
Increase
Decrease
$B$25
Pine Amount Used
1500
0
5000
1E+30
3500
$B$26
Oak Amount Used
450
0
750
1E+30
300
$B$27
Labor Amount Used
400
20
400
266.6666667
400
Use a graphical procedure and manual calculation to determine the optimal solution to the following linear program for decision-making purposes. Excel Linear Programing has been used to generate the following graph on the objective and constraints (please notice that you do not need to create this program in Excel, just use the outcomes given here to answer the questions):
Objective: Minimize cost C C= 0.5 Xa + 0.4 Xb Subject to: 2Xa + 5Xb >= 10 3Xa + Xb >= 9 Xb >= 2 Where Xa and Xb are >= 0 Please notice Xa is taken on x-axis and Xb on y-axis Instructions:
Note: Questions should be answered by looking at your objective and constraints and the provided Excel’s graphical results (No Excel program needs to be developed): Identify the feasible region by the areas bounded with the letters. For example, you could identify your feasible solution region as: Area EBJ (just as an example). Hint, you need to test a point in each of the inequalities to determine the solution for each of them, and then decide what will be the final feasible solution region that matches all these inequalities.
Show your optimum corner on the graph, as an example, point H, D, F, or whatever you think the correct optimum corner is. Calculate the coordinates (Xa and Xb) for this optimum point using the intersection of the 2 lines that create this optimum corner (mathematically and exact values, not just guessing from the graph). Hints, there are 2 trial cost lines plotted on the graph [C=1 and C=0.5] to show the direction of minimizing the cost within the feasible region.
What is your minimized cost value for this model
VanMetals has $3500 available for the production of new products. Wall Inc. will buy all the products they can produceAfter an initial screening, VanMetals reduced the production alternatives to tables and chairs. Each table can be produced with a cost of $400. Each chair can be produced for $350.VanMetals can devote up to 100 hours to these new products; each table is expected to require 16 hours, and each chair is expected to require 8 hours. The selling prices are $600 per table and $400 per chair.VanMetals’s owner would like to use all-integer linear programming without relaxation to determine the number of tables and the number of chairs to produce to maximize revenue.
What are the decision variables? (2 points)
What is the objective function for revenue? (3 points)
What are the constraints? (4 points)
What is the number of tables and the number of chairs to be produced to maximize revenue? (4 points)
What is the Maximum revenue they can expect? (3 points)
Draw the graphical solution of the all-integer problem. (4 points)
take a picture of all your work and upload the files. (You can use Excel Solver)
=====================================================TM and Mayota are the only companies serving a market. TM can introduce a new line of vehicles to the market. In response Mayota can introduce a new line of vehicles as well. They both know their competitive advantages and each sale of one will reduce the market share of the other.
The table below shows the expected gain in market share for TM thousands of units
Mayota
SedanSUVVanSportCoup
TMSedan123-24
SUV03-143
Van22123
Sport22343
Coup01432
What is the best strategy for TM? (2 points)
What is the best strategy for Mayota? (2 points)
If TM decides to produce SUV, what will be the best choice of production for Mayota? (2 points)
If Mayota decides to produce SUV, what will be the best choice of production for TM? (2 points)
Does this game have a pure strategy? (2 points)
Show you calculations and upload 6. Expected value Applied to Business ApplicationABCD Manufacturing Company (ABCD) has developed a new product.The functionality and feasibility of the product has been proven, but each sale will require significant customer support. ABCD must make a decision regarding the level of sales and dedicated to this product. Finally, a complete division (d1~ 4) consisting of about twelve people may be created to fully automate the product and engage in an extensive marketing campaign.The potential profit from each decision alternative depends on the market acceptance or demand for this product which may be high, moderate, or low. If market acceptance is high, each of the four decision alternatives, d1 through d4, will yield a profit of -200, 0, 300, and 900 thousand dollars respectively. If there is a moderate demand, the profits are likely to be 100, 100, 200, and -200 thousand dollars respectively. If the demand turns out to be low, then the profits will be 200, 150, -200, and -500 thousand dollars respectively.The industry experience with such products provides a probability estimate of demand to be high, moderate, and low as 0.3, 0.5, and 0.2 respectively. Which of the four decision alternatives should be selected by ABCD? What will be the expected profit from this decision? If a market research firm can provide perfect information about demand to ABCD (i.e., whether it will be high, moderate, or low) before a product launch decision is made, how much is that information worth to ABCD?
Hints: To structure this decision-making problem, we begin by constructing a payoff table. Our payoff table will, therefore, have 4 rows and 3 columns. The numbers inside the payoff table will represent the profit we will make for each combination of demand and decision alternative. Demand of Events/Decision AlternativeLowModerateHigh
D1
D2
D3
D4
Hint: Probability of each event: The most common approach to solve such decision-making problems with known probabilities is to use the expected value approach.

1.ABCD company is an office equipment company that produces two types of desks:

Introduction As we learned from the Tufte book, the issue with visualization of

Introduction
As we learned from the Tufte book, the issue with visualization of

Problem 1 [28 Marks] Swift Shipping is a 20-year-old Glasgow-based clothing reta

Problem 1 [28 Marks]
Swift Shipping is a 20-year-old Glasgow-based clothing reta

Problem 1 [28 Marks]
Swift Shipping is a 20-year-old Glasgow-based clothing retailer specialising in next-day
delivery of its affordable, stylish office attire for working women. Recently, Swift has struggled
to maintain its competitive edge as more clothing brands focus on speedy shipping. Swift
prides itself on using only local Scottish couriers for reliability. Lately, tensions between
management and couriers’ unions have increased. The possibility of postal strikes could
severely impact Swift’s shipments right before its busy season ramps up.
Swift’s Operations Manager must decide whether to ship orders now as usual via its Scottish
couriers or wait to see if strikes occur. If Swift ships as normal and strikes happen, costs from
delays and rerouting through England would total £60,000. If no strikes occur, regular Scottish
shipping would run £4,000. If Swift postpones Scottish shipping pre-emptively, delay costs
would hit £10,000 regardless of strikes. The Operations Manager knows Strikes could seriously
impact the company’s shipping capacity right before the busy season. But postponing
shipping may upset customers expecting Swift’s signature next-day delivery. She must
carefully weigh the costs and benefits of potential actions based on the likelihood of strikes
occurring. Let p equal the probability that strikes affect Swift’s courier shipments.
a. For what values of p does Swift minimize expected total cost by postponing shipping?
Build a decision tree with trial values of p and determine the approximate probability p
that minimises expected cost. [Consider using data table to determine EMV for various
values of p] [6]
b. Suppose Swift pays £1000 to purchase strike likelihood data. Based on similar strike threats
in the past, the company assesses that if there will be a strike, the information will predict
a strike with probability 0.75, and if there will not be a strike, the information will predict
no strike with probability 0.85. Provided that p=0.15, what strategy should Swift Shipping
pursue to minimize its expected total cost? [8]
c. Using the analysis in Part B, find the EVI when p=0.15. Then use a data table to find EVI for
p from 0.05 to 0.30 in increments of 0.05. and chart EVI versus p. [5]
d. Write a formal report that summarises your analysis and provides recommendations to the
Operations Manager at Swift Shipping. The report should include: [9]
4
– An executive summary highlighting the key findings from your analysis in question
a, b, and c. (3)
– Clearly stated recommendations on whether Swift should postpone shipping or
proceed as normal before the postal strike threat. (2)
– Quantitative support for your recommendations using calculations from the
questions. (2)
– A discussion of the limitations, risks, and mitigation strategies related to your
recommendation. (2)
Problem 2 [23 Marks]
The credit union branch at Newcastle University frequently sees mismatches between
customer demand and service staffing levels. Customers face long queues on busy days, yet
idle staff at other times. Branch manager Michael Kaluuya sees this issue but lacks data
analytics expertise to optimize staff scheduling.
Michael believes accurate demand forecasting is key to balancing staff productivity, costs and
customer service. He compiled a dataset with over a year’s worth of daily customer arrival
figures, along with potential demand drivers like the day of the week, whether the day was a
staff or faculty payday, and whether the day was the day before or after a holiday. Data for this
problem is in the file “Problem 2_Data”. However, Michael cannot reliably analyse the patterns
himself to create robust forecasts of each day’s customer arrivals.
a. Build a statistical forecasting model to predict the credit union branch’s daily customer
arrivals using Michael’s dataset. [Hint] you will need to create Dummy variables. [8]
b. Develop an improved model using only significant variables. You might want to consider
if the first day of the month influences the demand. [6]
c. In your consulting report for Michael: [9]
– Concisely explain your final model methodology, variables, parameter estimates,
overall fit, etc. (3)
– State model assumptions and evaluate their validity. (4)
– Assess strengths / limitations in capturing customer demand patterns (2)
5
Problem 3 [26 Marks]
The management of Zahret Company is trying to determine the amount of each of two
products to produce over the coming planning period. The following information concerns
labour availability, labour utilisation, and product profitability.
Table 1
Labor-Hours Required (hours/unit)
Department Product 1 Product 2 Hours Available
A 1.00 0.35 100
B 0.30 0.20 36
C 0.20 0.50 50
Profit contribution/unit £30.00 £15.00
a. Develop a linear programming model formulation of the Zahret Company problem. Solve
the model using Solver and determine the optimal production quantities of products 1 and
2. [8]
b. In computing the profit contribution per unit, management does not deduct labour costs
because they are considered fixed for the upcoming planning period. However, suppose
that overtime can be scheduled in some of the departments. Which departments would
you recommend scheduling for overtime? How much would you be willing to pay per hour
of overtime in each department? [5]
c. Suppose that 10, 6, & 8 hours of overtime may be scheduled in departments A, B, and C,
respectively. The cost per hour of overtime is £18 in department A, £22.50 in department
B, and £12 in department C. Formulate and solve a linear programming model that can be
used to determine the optimal production quantities if overtime is made available. What
are the optimal production quantities, and what is the revised total contribution to profit?
How much overtime do you recommend using in each department? What is the increase
in the total contribution to profit if overtime is used? [8]
d. In the report, summarise answers to the above questions and discuss any additional insights
that would support decision making. [5]
6
Problem 4 [23 Marks]
Management of Paxon Pharma, a leading UK manufacturer of generic prescription drugs, is
trying to control inventory costs for one of its highest volume products – the antibiotic drug
amoxicillin. The weekly holding cost for 1,000 cases (one unit) of amoxicillin is £30. The
marketing team estimates the average weekly demand from NHS trusts and UK pharmacies is
120 units, with a standard deviation of 15 units. Unmet demand is considered lost sales.
The production team at Paxon’s Manchester plant can manufacture at one of three weekly
rates: 110 units; 120 units; or 130 units. Changeover and recalibration between production
rates carries a fixed cost of £3,000.
Management aims to test the following production planning policy:
– If current UK amoxicillin inventory is below 30 units, produce 130 units next week.
– If inventory is above 80 units, produce 110 units next week.
– Otherwise, continue last week’s output rate.
Current UK inventory is 60 units following last week’s production of 120 units.
a. Build a 52-week Excel simulation model of this policy. Graph UK inventory over time and
calculate total cost (Inventory cost plus production cost). [7]
b. Run the simulation for 500 iterations by varying the upper threshold U from 30 to 80 units.
Estimate the average 52-week cost at each value of U. Keep L = 30 throughout. [5]
c. Determine the sample mean and standard deviation of costs for each value of U. Using the
simulated results, is it possible to construct valid 95% confidence intervals for the average
52-week cost for each value of U? In any case, graph the average 52-week cost versus U.
Identify the optimal U when lower threshold L is fixed at 30 units. [6]
d. Summarize findings and recommendations in a formal report. Synthesize numerical
analysis and qualitative context into strategic, actionable guidance for Paxon’s UK
executive team and manufacturing planners. Consider if other production policies could
be more useful to investigate?

In Milestone One, you recommended an innovation option (incremental or discontin

In Milestone One, you recommended an innovation option (incremental or discontinuous) to the organization from the course scenario. Now that senior management of the company has approved your recommendation, your task is to find an efficient process for your cross-functional team to follow during the development of your innovation. Remember that your perspective is still that of a middle manager for one of the top U.S. producers of luxury and mass-market automobiles and trucks.
You and your team are considering using Cooper’s stage-gate process for new product development. This is a standard process that shows the journey of an idea from conceptualization to the market. You will create a detailed flowchart to share with your cross-functional team on one possible process for implementing the innovation recommendation you have made.
Prompt
Create a PowerPoint presentation with the following requirements, including a detailed flowchart. Ensure the presentation is useful in helping your team understand the stage-gate process. Your presentation should include the following:
Describe the major elements of the stage-gate process (1–2 slides).How many stages are in the process?
What is the purpose of each stage?
Create a stage-gate process flowchart (1 slide) using proper shapes for each step in your flowchart.In the flowchart or speaker notes, list an example of an activity at each stage.
In the flowchart or speaker notes, list a decision criterion at each stage using the company. Some examples of decision criteria include:Filter ideas to the preliminary investigation
Filter projects to business opportunities
Filter projects to product or process development
Filter products to limited launch
Filter products to international marketing
Discuss the implications of using the stage-gate process (1–2 slides).When is the use of the stage-gate process appropriate?
How could the stage-gate process slow down innovation?
Is the stage-gate process more conducive to an incremental or discontinuous innovation?
What to Submit
Using PowerPoint, create a presentation that is 3 to 5 slides with detailed speaker notes that highlight the important points you want to emphasize to your team. If references are included

Reply to this post with a written entry will no less than 100 words and up to 25

Reply to this post with a written entry will no less than 100 words and up to 250 words. Each entry must contain some reference to either the course book (page) or an external reference (URL for example). You also must reply to another post (at least a response with at least two sentences). Please click on the icon with the three vertical dots on the upper right of the Canvas page to see the rubric for this assignment. Discussion question
As the CEO of one of the largest firms in the west coast of Florida, you have seen challenges with customer retention and product delivery for the past 6 months. The numbers don’t look good, and your board is questioning the company’s outlook. Answer the following:
Identify which combination of business analytics type would you pursue.
Briefly explain your reasoning.

In the data set for this homework, you will find that the first six variables ho

In the data set for this homework, you will find that the first six variables hold data linked to the employees’ demographic profiles and the remaining variables provide employees responses on 1 ‘strongly disagree’ to 5 ‘strongly agree’ response scale to assess organizational citizenship behavior (OCB: employees’ voluntary actions that contribute positively to the organization beyond their job duties) and job satisfaction (JSat: positive state toward current job). The variables are as follows:
1.ID (unique employee identifier – categorical variable)
2.Gender (categorical variable)
3.Tenure (quantitative variable)
4.Ethnicity (categorical variable)
5.Department (categorical variable)
6.Salary (quantitative variable)
7.ocb1 (I work harder than my job requires; quantitative variable)
8.ocb2 (I put a huge amount of effort in my job; quantitative variable)
9.ocb3 (I help out my team mates; quantitative variable)
10.ocb4 (I go the extra mile; quantitative variable)
11.JobSat1 (I am satisfied in my job; quantitative variable)
12.JobSat2 (My job is good; quantitative variable)
1.Create a new variable in the dataset labeled “OCB” that is the average of ocb1, ocb2, ocb3, and ocb4.
2.Find the and interpret the Cronbach’s alpha for OCB.
3.Create a new variable in the dataset labeled JSat that is the sum of JSat1 and JSat2.
4.Find and interpret the Cronbach’s alpha for JSat.
5.How could you assess the validity of OCB and job satisfaction? (Note: you do not have to do any analyses, but you can if it is helpful).
6.Create a new variable in the dataset labeled as logSalary that represents the logarithm of salary.
7.Create a new variable in the dataset labeled as sqrtTenure that represents the square root of the Tenure variable.
8.Conduct a t-test to determine the difference in OCB between genders. Write up your results here:
9.Conduct a t-test to determine the difference in job satisfaction between genders. Write up your results here:
10.Conduct an analysis of variance (ANOVA) to determine the difference in job satisfaction among the five departments. Write up your results here:
11.Please submit both this filled in worksheet and your new excel file.
R Output: