Questions
(Python) In a weather station, there is a sensor that measures the temperature three times a...

(Python) In a weather station, there is a sensor that measures the temperature three times a
day (in Celsius). Write a program that asks the user to input three numbers, corresponding to the
sensor's three readings for a particular day. Then, print the minimum, maximum and average value
of the three numbers.
Note: If one or two inputs are either less than -70, or greater than +50 degrees, you should ignore
those one or two inputs, and calculate the minimum, maximum and average using only the other
inputs. If all 3 inputs are either less than -70 or greater than 50, your code should print "Broken
sensor!" and not perform any calculations.
For this question, you must not use any built-in functions or functions from math
module except print(), input() or oat(). You must compute the minimum, maximum
and average values using if statement and arithmetic operators. This means that you
cannot use the built-in max() or min() functions.

In: Computer Science

Analysts expect that under new management the firm could increase it revenue and operating expenses by...

Analysts expect that under new management the firm could increase it revenue and operating expenses by 12% next year 10%and the following year 7%. Analysts believe the marginal cost to be 6%, the Wacc 8% and the tax to be 20%.

Assumptions. You must adjust numeric value of each assumption as necessary to project cash flow, income, assets & liabilities, etc.
Valuation. Construct a valuation using a DCF analysis to calculate the Enterprise and Equity Values. Apply an EBITDA multiple of 7 to calculate TV.
Commentary. Your commentary should focus on how much your would pay for this firm and why.
Actual Projected
2018 2019 2020 2021 2022 2023
Total Revenue     47,000.0     51,700.0     56,870.0     62,557.0     68,812.7     75,694.0
   Cost of Revenue     30,000.0     33,000.0     36,300.0     39,930.0     43,923.0     48,315.3
Gross Profit     17,000.0     18,700.0     20,570.0     22,627.0     24,889.7     27,378.7
Operating Expenses
   Depreciation           900.0           636.2           683.2           734.9           791.8           854.3
   S, G & A       7,800.0       8,580.0       9,438.0     10,381.8     11,420.0     12,562.0
   Non-recurring charge           500.0                  -                    -                    -                    -                    -  
Operating Income       7,800.0       9,483.8     10,448.8     11,510.3     12,677.9     13,962.4
   Interest Expense           335.0             30.1             30.1             30.1             30.1             30.1
Earnings before income taxes       7,465.0       9,453.7     10,418.7     11,480.2     12,647.8     13,932.3
   Income Taxes       1,513.0       1,890.7       2,083.7       2,296.0       2,529.6       2,786.5
Net Income       5,952.0       7,563.0       8,335.0       9,184.2     10,118.3     11,145.8
Balance Sheet
All numbers are in millions.
2018 2019 2020 2021 2022 2023
Cash 1,750.0          8,326.8       15,576.9       23,567.7       32,373.3       42,075.3
Receivables 4,097.0          4,506.7          4,957.4          5,453.1          5,998.4          6,598.3
Inventories 4,783.0          5,261.3          5,787.4          6,366.2          7,002.8          7,703.1
Current Assets 10,630.0       18,094.8       26,321.7       35,387.0       45,374.5       56,376.7
Net PPE 6,362.0          6,832.0          7,349.0          7,917.7          8,543.3          9,231.4
Goodwill 1,860.0 1,860.0 1,860.0 1,860.0 1,860.0 1,860.0
Total Assets 18,852.0       26,786.8       35,530.7       45,164.7       55,777.8       67,468.1
Payables 2,888.0          3,176.8          3,494.5          3,843.9          4,228.3          4,651.2
Other Liabilities 830.0             913.0          1,004.3          1,104.7          1,215.2          1,336.7
Long Term Debt 4,224.0          4,224.0          4,224.0          4,224.0          4,224.0          4,224.0
Common Equity 1,762.0          1,762.0          1,762.0          1,762.0          1,762.0          1,762.0
Retained Earnings 9,148.0       16,711.0       25,045.9       34,230.1       44,348.3       55,494.2
Total Liabilities & Equity 18,852.0       26,786.8       35,530.7       45,164.7       55,777.8       67,468.1
Depreciation 636.2 683.2 734.9 791.8 854.3
PPE
Beg       6,362.0       6,832.0       7,349.0       7,917.7       8,543.3
Additions       1,106.2       1,200.2       1,303.6       1,417.4       1,542.4
Depreciation or Disposals           636.2           683.2           734.9           791.8           854.3
End     6,362.0       6,832.0       7,349.0       7,917.7       8,543.3       9,231.4
Debt
Beg       4,224.0       4,224.0       4,224.0       4,224.0       4,224.0
Additions                  -                    -                    -                    -                    -  
Reductions                  -                    -                    -                    -                    -  
End     4,224.0       4,224.0       4,224.0       4,224.0       4,224.0       4,224.0
Interest Calculation
Beg Debt Level       4,224.0       4,224.0       4,224.0       4,224.0       4,224.0
Interest Rate 0.7% 0.7% 0.7% 0.7% 0.7%
            30.1             30.1             30.1             30.1             30.1
Cash
Beg       1,750.0       8,326.8     15,576.9     23,567.7     32,373.3
Operating Cash Flow       8,199.2       9,018.2       9,919.1     10,910.1     12,000.1
NWC         (516.2)         (567.8)         (624.7)         (687.0)         (755.8)
Debt Borrowings                  -                    -                    -                    -                    -  
Sources       7,683.0       8,450.4       9,294.4     10,223.1     11,244.3
Dividends                  -                    -                    -                    -                    -  
Capital Expenditures       1,106.2       1,200.2       1,303.6       1,417.4       1,542.4
Debt Payments
Uses       1,106.2       1,200.2       1,303.6       1,417.4       1,542.4
End 1750       8,326.8     15,576.9     23,567.7     32,373.3     42,075.3
Firm Name Food N Pak
Your Name Webster University
Initial Year 2018
Receivables % of Sales 8.7%
Inventories % of Sales 10.2%
Payables % of Sales 6.1%
Other Liabilities % of Sales 1.8%
Cost of Revenue % of Sales 63.8%
SGA % of Sales 16.6%
Interest Rate % of Debt 0.7%
Tax Rate % of EBT 20.0%
Dividend % of NI 0.0%
Discount Rate
Depreciation Life Years 10
Capital Expenditures (Asset/Sales Ratio) % of Chg Sales 10.0%
Growth Rate 1 10.0%
2 10.0%
3 10.0%
Terminal 10.0%
Non-recurring % of Sales 0.0%
Debt Growth % Growth Rate 0.0%
Debt Reduction % of O/S Balance 0.0%
Round Num of places 1

In: Finance

Write a Python program for the following: A given author will use roughly use the same...

Write a Python program for the following:

A given author will use roughly use the same proportion of, say, four-letter words in something she writes this year as she did in whatever she wrote last year. The same holds true for words of any length. BUT, the proportion of four-letter words that Author A consistently uses will very likely be different than the proportion of four-letter words that Author B uses. Theoretically, then, authorship controversies can sometimes be resolved by computing the proportion of 1-letter, 2-letter, 3-letter, ..., 13-letter words in the writing and then comparing it with the same statistics from known authors.

Your task is to write a Python program that computes the above statistics from any text file. Note that apostrophes do not count in the word length. For example, "he's" is a three-letter word. Words like hard-hearted should be replaced with two words with a space between them (hard hearted).

Name of input file: romeo_and_juliet.txt

Proportion of 1- letter words: 4.8% (1231 words)

Proportion of 2- letter words: 16.1% (4177 words)

Proportion of 3- letter words: 20.3% (5261 words)

Proportion of 4- letter words: 24.3% (6295 words)

Proportion of 5- letter words: 15.0% (3889 words)

Proportion of 6- letter words: 7.9% (2048 words)

Proportion of 7- letter words: 5.2% (1352 words)

Proportion of 8- letter words: 3.7% (953 words)

Proportion of 9- letter words: 1.5% (378 words)

Proportion of 10- letter words: 0.7% (190 words)

Proportion of 11- letter words: 0.3% (71 words)

Proportion of 12- letter words: 0.1% (20 words)

Proportion of 13- (or more) letter words: 0.0% (12 words)

Here the program is tested on the full text of Romeo and Juliet but it should work for any file. The sample run above shows the actual proportion and count of different sized words in the file. Hint: make sure to replace each character in ",.!?;:][-\"" in the text with a space before doing any splitting.

In: Computer Science

You are the manager of Compounders Ltd. The company mixes compound for smaller plastic extrusion companies....

You are the manager of Compounders Ltd. The company mixes compound for smaller plastic extrusion companies. Compounders Ltd has six (6) mixing machines with a maximum capacity (100%) of 250 ton per month. However, due to power cuts, the machines are currently being operated at 75% of installed capacity.

One (1) ton of a compound mixture consists of two (2) raw materials: 0.7 ton of Electrolyte and 0.3 ton of Copper Wire. Assume no wastage. There are no opening and closing inventories. All raw materials purchased are being used in the month of purchase, and all compound mixed are being sold in the month mixed.

Each mixing machine requires two (2) operators. The company is operating a nine (9) hour shift and each machine operator earns R75 per hour. No weekend time nor overtime is allowed.

The company is a price setter and the pricing policy is based on a mark-up of the total production cost at 50%.

The company incurred the following costs for the month:

1. Import (purchase) raw material for one month’s production. Material Electrolyte @ R60 per ton and Copper Wire @ R95 per ton.

2. The import costs amount to R1,000 per 250 ton of Material Electrolyte and R1,500 per R120 ton of Copper Wire.

3. Paid the wages based on a twenty (20) working days.

4. The factory foreman earns a salary of R15,000 per month.

5. The cost of security is as follows: Guard at the entrance of the factory R3,500 per month and the guard at the entrance to the admin offices R3,750 per month.

6. The monthly rental amounts to R25,000. Rent is allocated based on floor space occupied. The factory occupies 9,100 ??2 and the office block 3,900 ??2.

7. Office expenses amounts to R64,000 per month.

8. Compound delivery cost amount to R1,200 per 125 ton of compound delivered.

1.3 Calculate the contribution per ton produced. (2)

1.4 Calculate the break-even tons to be mixed (2)

In: Accounting

3. McHuffter Condominiums, Inc., of Pensacola, Florida, recently purchased land near the Gulf of Mexico and...

3. McHuffter Condominiums, Inc., of Pensacola, Florida, recently purchased land near the Gulf of Mexico and is attempting to determine the size of the condominium development it should build. Three sizes of develop-ment are being considered; Small, d1; Medium, d2; and large, d3. At the same time, an uncertain economy makes it difficult to ascertain the   demand for the new condominiums. McHuffter's management realizes that a large development followed by a low demand could be very costly to the company. However, if McHuffter makes a conservative small-development decision and then finds a high demand, the firm's profits will be lower than they might have been. With the three levels of demand-low, medium and high. McHuffter's management has prepared the following profit ($000). (20 pts.)

         payoff table

          -------------------------------------------

                                   Demand

            Decision    ----------------------------

         Alternatives       Low    Medium    High

         -------------------------------------------

           Small, d1         400      400      400

           Medium, d2        100      600      600

           Large, d3        -300      300      900

        --------------------------------------------

a) If nothing is known about the demand probabilities, what are the      recommended decision using the Maximax(optimistic), Maximin (pessi-    mistic), and Minimax regret approaches?

b) If P(low) = 0.20, P(medium) = 0.35, and P(high) = 0.45, What is the   recommended decision using the expected value approach?

c) What is the expected value of perfect information (EVPI)? You have         to use regret table to get EVPI.

Suppose that before making a final decision, McHuffter is considering

conducting a survey to help evaluate the demand for the new condominium

development. The survey report is anticipated to indicate one of two

levels of demand: weak(W) or strong(S). The relevant probabilities are as

follows: (25 pts)

    P(W)= 0.3 P(low/W)   = 0.50      P(low/S)   = 0.10

    P(S)= 0.7 P(medium/W)= 0.40      P(medium/S)= 0.25

               P(high/W) = 0.10      P(high/S) = 0.65

BDSC 340.001-3

   d) Construct a decision tree for this problem and analyze it.  

   e) What is McHuffter’s optimal decision?

   f) What is the expected value of the survey(sample) information?

     

In: Operations Management

This case deals with one of the pioneers in the electric scooter industry: Bird. Please read...

This case deals with one of the pioneers in the electric scooter industry: Bird. Please read the articles provided and answer the following questions:

1) Where is the demand for electric scooters coming from? How fast it is expected to grow? Why are investors buying into this industry? Elaborate. [It might be helpful to provide the target segment and its size to justify your answer].

2) What are the possible concerns impacting the demand of electric scooters? How attractive is this industry? [Use Porter’s five forces model to analyze the industry attractiveness]

3) The industry is at a nascent stage and there are already several competitors such as Lime and Skip (Uber and Lyft have also entered this arena). How should Bird position itself to differentiate from the competitors?

Article:

Bird’s electric scooters are getting more rugged to handle heavy use

A year ago, dockless electric scooters first appeared on the streets San Francisco and Santa Monica. The initial reaction was bewilderment, eventually giving over to annoyance and dismissal. The companies that were scattering these scooters everywhere, like Bird and Lime, seemed to epitomize tech-bro arrogance. Surely the fad would fade and the scooters would be shipped back overseas from whence they came, destined for some landfill in China.

Twelve months later, the scooters are in over 100 cities across the globe, and by most accounts, immensely popular. Bird and Lime have each reported over 10 million rides since their launch. Lime is valued at $1 billion; Bird at $2 billion. Ride-hailing giants Uber and Lyft are now getting in on the action, acquiring bike-share companies and applying for permits to operate their own e-scooters. Early complaints about vandalism, blocked sidewalks, and scofflaw riders — while still valid — have since given way to a realization that, hey, these things are kind of fun! And more than that, they could be a crucial link in helping cities solve crucial transportation challenges.

Against that backdrop, Bird CEO Travis VanderZanden spoke with The Verge about phase two in his plan to conquer the micro-mobility sector. Before founding Bird, VanderZanden was a ride-hail executive. He served as Lyft’s chief operating office until August 2014, when he left to join Uber. The move landed in him in hot water with his former employers, who filed a lawsuit claiming VanderZanden stole confidential material. The parties later settled for an undisclosed amount.

Now VanderZanden is out to steal Uber and Lyft’s customers, or at least the ones who use ride-sharing to take short trips across town. He spoke about Bird’s growth in ridership, building a more rugged scooter, and competition with his former employers in the ride-hailing sector.

The Verge: Congratulations on your one year anniversary.

Travis VanderZanden: Yeah. We’re super excited to announce the one year anniversary and take a minute to reflect on the last year. We’re now seeing that we’re doing 10 million rides, 100 cities with two million riders. The reason we get excited to get the numbers out is for us the first year was really... when we started the company it was suggested, can we use electric scooters to really get people out of cars? And we think the data from the first year it’s been kind of a big data point that people are willing to get out of cars and use electric scooters, so, excited to have the announcement.

What is the next stage, would you say, of the business?

Year two is all about, for us, doubling down on our efforts to work with cities and build out government technologies, call it our “GovTech” platform, where we’re spending a lot of our engineering resources building tools that the cities can use to have the insight into Bird’s data and also control Bird in their cities. So an example is that we just rolled out a geo-speed limiting feature where the Bird is already capped at 15 miles per hour, but when you enter a zone like the beach bike path in Santa Monica, the Bird will slow down to 8 miles per hour automatically. So we’re doing a bunch of cool things like that that help the cities. Year two is gonna be about doubling down on those efforts.

That also includes some geo-fencing, too, I understand, right?

Yeah, because there’s geo-fencing, the geo-speed limit’s going to work with geo-fencing on slowing you down. There’s also ‘no ride’ zones, there’s ‘no park’ zones... a bunch of cool things like that that we’re doing, and so we’re going to be continuing that in the second year.

I mean, it’s not that cool, right? For the first year it was ‘anything goes,’ ‘no rules,’ and now it’s like ‘okay, lots of rules that we have to contend with.’

Well, when we first launched the business, you know, we didn’t know if electric scooters were gonna work, we didn’t know if people would ride them. You know, companies have been trying to get Americans off cars for a long time and so it actually started as a small bet and what we found is people really enjoy riding the electric scooters, which we’re excited about. And we’ve been working with cities in year one as well, but we think year two is about doubling down on those efforts.

How are you adapting to cities introducing these pilot programs and wanting to have more control over the deployment and usage of the scooters?

Yeah, so you know, Ridesharing 1.0... we’re calling Bird Ridesharing 2.0 and two of the biggest changes from 1.0 are that we’re using environmentally friendly vehicles to help reduce carbon emissions and traffic. But the second big difference is really collaborating with cities and sharing data with them through the real-time API access, through the dashboards. And then building technology to control and manage Bird in their market.

What about the scooter itself? Are you guys sticking with the one you’ve got? Are you hoping to make any hardware upgrades?

Yeah, so we’ve been investing heavily over the last year. We built out a really big vehicle engineering team. We have the biggest vehicle engineering team in the industry. We’re working on future vehicles now. We’ve already started testing a new vehicle recently, which is a lot more ruggedized than our original vehicles and built specifically for the speedier sharing model

Can you give me any more details in terms of what that means?

The battery is 55 percent bigger. The shaft is built so it’s very durable. The brake cables aren’t exposed. The tires are solid core tires. We spent a lot of time trying to test tires that didn’t have air in them but still had a good rider experience, which was very important to us. We finally found we think the best tires in the world. So, big things like that, so we’re super excited to be testing these new vehicles.

How are you guys approaching the issue of safety? There have been recent reportsabout a rise in scooter related injuries. How are you hoping to deal with that problem, and how are you talking to the cities about that?“

Early on, Bird has prioritized safety over everything else, including growth. It’s easy to say that, but if you look at our actions, there’s a bunch of ways we’ve prioritized... So, three examples of us prioritizing safety over growth are we capped the vehicle speed at 15 miles per hour, even if the city doesn’t require us to do that. We require a driver’s license and the rider to be 18, even if the city doesn’t require us to do that. And we pick the Birds up at 9PM every night, even if the city doesn’t require it. And we also ship free helmets, even if the city doesn’t require it. It helps us sleep better at night, to really prioritize safety over growth.

Do you have any concern about personal injury attorneys filing class-action claims?

We think cars are dangerous. Our society is kind of built around cars, and cars can be dangerous. I’m sure you know the stat that 40,000 Americans died in car accidents last year. A stat you might not know is that another 6,000 people, pedestrians, died by getting run over by cars. It turns out any time you’re operating... or walking, or biking, or Birding around cars, it can be dangerous, and that’s why we try to educate the riders to wear a helmet. We’re working with cities and encouraging them to build more protected bike lanes. And really aligning with some of the bike advocates who’ve been wanting protected bike lanes for a long time.

In year two, obviously you’re gonna start to see competition from some of your former employers: Uber and Lyft are getting into the game. Are you concerned at all, sort of going up against them, considering obviously the amount of capital that they’re going to be bringing to the market?

No. I welcome Uber and Lyft into Ridesharing 2.0. We think Ridesharing 2.0 will make the world a better place, and we welcome them into that world. I think they’re kind of operating where we were a year ago, and so we think we’re much further ahead on vehicle engineering, on the government technology stuff. We share data with cities, which is something maybe they’re not used to in Ridesharing 1.0. We definitely welcome them.

So why do you think a user would choose a Bird over, say, a Lyft scooter at this point?

One, Bird’s in a hundred cities, and we have a lot more vehicles deployed, a lot more vehicles being manufactured and sent to us. There’s that. So the vehicles will be closer to users because we have more of them. In addition, we have built more ruggedized vehicles, while they’re still working on the vehicles we had a year ago, and haven’t figured out how to ruggedize them yet.

So you’re not worried that they might buy your supply chain out from underneath you?

No, we’re not concerned about it. We have great relationships that we’ve been building over the last year. In fact, we just signed an exclusive deal with the original manufacturer of the ruggedized scooter sharing company. It was the manufacturer that built the original Lime scooters. We have an exclusive deal with them. We continue to work with Ninebot and others. We think we’re far ahead on that, and I think we have access to the most supply right now. I understand a lot of others are having a hard time finding supply.

What’s the latest on bringing the scooters to New York? Obviously that would be a huge market for you guys.

I get excited about any market when there’s massive traffic and car problems, and certainly New York City’s high on that list. For us, we always wanna make sure that we’re legal before we go in. There are folks working with city and state officials to try to figure out how do we best fit in to the existing legal framework. I’m certainly excited about figuring it out. I think New York City would be way easier to get around on Bird than in a car, obviously.

Bird got shut out of San Francisco’s pilot program. Do you think there’s still a chance that you’ll be able to bring the scooters back to San Francisco at some point?

I haven’t spent much time digging into it. I think San Francisco’s just one city. We’re in a hundred cities now. It’s the only city we haven’t been able to stay operating in so far and get a permit. It doesn’t mean we don’t wanna be in San Francisco. We just haven’t spent a lot of time thinking about it right now, because there’s so many other cities that have been embracing the electric scooters. At some point, obviously, we would love to be in San Francisco. We’re just not spending a lot of time... we’re not protesting it or anything like that in the short term.

Yeah, but you did protest in Santa Monica before getting permits there.

Yeah. In Santa Monica, it’s our home state. We felt that’s where scooter sharing, where we originally invented and created scooter sharing. We felt maybe a little more sentimental about Santa Monica. Overall, we’re finding cities are really embracing these scooters. I think that the press tends to over focus on San Francisco. But we’re in a hundred cities now. When we talk to cities about our mission of reducing car trips and traffic and carbon emissions, it 100 percent aligns with the cities’ goals. They have the same goals. So it’s just a matter of figuring out how do we best fit in. Being in a hundred cities and doing 10 million rides in the first year is exciting and we have a lot of cities that are excited about electric scooters.

Bird has promised to provide funding for bike lanes. Are you doing that in every city that you’re operating in, or only just the cities that ask for that kind of thing?

We offer it in all cities and try to figure out who to pay, what initiative makes the most sense. For us, what’s important is investing in improving the bike infrastructure and scooter infrastructure in a city. The cities that have... a lot of cities have permits with their own permitting fees and then they use the permitting fees to go towards the bike infrastructure. An example is, you wanna use the money, you’re happy to help pay for dedicated bike lanes, to get dedicated parking spaces. There are dozens of parking spaces on the street per block, instead of taking that one space away from a car, you could probably fit 10-15 Birds in that same space... And we just think it’s a much more efficient use of space, but that said, we’re not asking for the city to pay us, and we’re not asking [for] a handout. We’re asking them to pay for that space. It’s just a matter of figuring out how do we make that happen. So we’ve certainly been trying.

Bird is in Paris and in Tel Aviv. Are you eyeing any other international cities?

Yeah. We just launched Brussels. We’re gonna be expanding throughout Europe and then next week we’ll have some more exciting announcements about some other international markets.

Did you ever expect this year to be as busy as it has been in terms of this business? Did you expect this to be as popular and as polarizing as it’s turned out to be?

I certainly didn’t expect it to be as polarizing. I think when I first thought about doing the business, I really felt like we could get people out of cars and using electric scooters. I didn’t think we would be able to do 10 million rides. By comparison, if you go back and look at... I think Lyft released an infographic and blog post about on their 15-month anniversary, and they did a million rides in that first 15 months. And to do 10 million rides in 100 cities has been very exciting to see. It doesn’t mean we don’t have a lot of work ahead, and we wanna continue to work with cities to see how do we make it less polarizing, how do we fit in, how do we get dedicated parking so that people don’t complain about the Birds being parked where they shouldn’t be. I think we’re... we’d like the team to work on that so we’ve gotten less polarizing... I know when the car was first introduced and everybody got around on horses, the car had a similar reaction as commuters now to scooters. I think if we can break this car addiction we have, I think it’s ultimately that we will make a road there.

In: Economics

1. A marketing research team at Optimum Nutrition is interested in knowing the proportion of Americans...

1. A marketing research team at Optimum Nutrition is interested in knowing the proportion of Americans who exercise at least three times a week. They send out a survey asking "Do you exercise more than 3 times a week?" to over 5,000 random Americans.

Given the following scenario, is this problem a One Mean, One Proportion, Two Independent Means, or Paired Means?

Group of answer choices

a. One Mean

b. Two Independent Means

c. Paired Means

d. One Proportion

2. On average, how much is the difference in calories burned between regular and standing desks? The amount of calories that 8 employees burned was recorded by using a regular desk for a day, and then with using a standing desk. The data is recorded in the table below. Compute a 95% confidence interval for the population mean difference. (dif = standing - regular)

Regular Desk Standing Desk
156 164
160 148
148 159
140 160
156 150
152 152
162 162
155 149

Group of answer choices

a. (-6.91, 10.66)

b. (-10.66, -6.91)

c. (-10.66, 6.91)

d. (6.91, 10.66)

3. A movie theater wanted to see if they could increase attendance by offering a free digital copy of a movie with ticket purchase. They randomly picked 10 different theaters to test the new program at and tested each of these theaters on two random days, once with the program and once without. The resulting attendance that was recorded is shown in the table below. Find dbar and sd using (with-without).

  

Theater #

With Program Without Program

1

162 173
2 178 170
3 155 147
4 201 198
5 183 183
6 147 139
7 182 185
8 157 154
9 182 177
10 149 151

Group of answer choices

a. dbar= 1.9 sd= 6.08

b. dbar= -1.9 sd= -1.14

c. dbar= 1.9 sd= -1.14

d. dbar= -1.9 sd= -6.08

In: Statistics and Probability

Daniel Fowler, senior vintner at Napa Winery, had been put in charge of developing an optimal...

Daniel Fowler, senior vintner at Napa Winery, had been put in charge of developing an optimal blending plan for the upcoming season. This assignment was the result of a recent Napa Winery board meeting where the CEO had presented her ideas regarding the use of analytics for enhancing profits while at the same time not affecting quality. Industry reports indicated that a growing number of the major wineries were using analytics to assist in the wine-blending process. The board meeting had concluded with the CEO tasking Fowler to develop an analysis and report his findings to the board at next month’s meeting.

The United State has become the largest wine market in the world, with sales approaching $40 billion annually. Typically, two types of wines are produced: varietals and blends. Wine blending is the process of combining several grape varieties to achieve a characteristic that is lacking in the original grapes. There are several reasons why a vintner might want to blend wines, including: (1) enhancing aroma; (2) improving the color; (3) raising or lowering the acidity level; (4) raising or lowering alcohol levels. The process of wine blending contains both objective and subjective components. Alcohol level is an example of an objective standard.

Napa Winery was one of the premium wine producers in the state and had recently begun to sell its products on a global basis. The winery produced and distributed a wide range of premium wine, including its flagship – CS Wine. The firm’s management was considering employing prescriptive analytics as a means of improving the wine-blending process. Typically, wines were produced from a blend of several types of grapes. In producing these blended wines, the vintner had to take into consideration both grape characteristics and government regulations. Each of the candidate blends was then subject to a series of taste tests. In those cases where the candidate wines were found to be unacceptable by the tasters, a set of new products was often produced. The vintner planned to use prescriptive analytics to help develop an optimal blending strategy and assumed that all bottles produced could be sold. More specifically, the vintner was going to undertake a comparative assessment of Napa Winery’ premier CS Wine product sector. The three specific production wines from this sector were:

Vintage CS Wine, which wholesaled for $9 per bottle

Non-vintage CS Wine, which wholesaled for $5.50 per bottle

Non-vintage M Wine, which wholesaled for $2.95 per bottle

Listed below are the winery objectives and government regulations.

Winery objectives and specifications

Maximize net profit.

The acidity level of CS Wine cannot exceed 0.7 grams per 100 milliliters.

The vintage CS Wine must not contain more than 0.2 per cent sugar.

The non-vintage CS Wine must not contain more than 0.3 per cent sugar.

The acidity level of M Wine cannot exceed 0.3 grams per 100 milliliters.  

Government regulations

All wines labeled varietal (e.g. CS Wine) must contain at least 75% of the named grape type.

All wines must contain at least 10% and no more than 15% alcohol level by volume.

All vintage-dated wines must contain 95% blending grapes from the year on the bottle label.

All vintage-dated wines must also report the viticulture area on the label and must contain at least 85% blending grapes from this area.

Presented in Exhibit 1 are the characteristics of the four blending grades along with available quantities and associated costs.

Exhibit 1. Grape type characteristics, quantities and costs

Grape Type

Viticulture

Vintage

Acidity (gm/100 ml)

Sugar (%)

Alcohol (%)

Quantity (bottles)

Cost ($/bottle)

CS grapes

Zone 1

2011

0.35

0.12

13.5

50,000

2.35

CS grapes

Zone 2

2010

0.75

0.25

15.3

60,000

2.60

CS grapes

Zone 2

2011

0.55

0.30

11.5

30,000

2.10

M grapes

Zone 1

2010

0.25

0.08

15.7

200,000

1.55

Questions:

What is the optimal blending plan that will help Napa Winery achieve simultaneously its own objectives and specifications, and meet the government regulations?

Are the government regulations adding more pressure on the company? What will be the optimal blending plan if those regulations will not exist? Are certain regulations more restrictive than others? Conduct a comparative analysis to identify which government regulations will be the most beneficial to company’s business.

What other aspects should Daniel Fowler take into consideration in his modeling approach before presenting the results to the CEO during the board meeting? (Hint: New optimization models might be required to sustain your recommendations)

In: Operations Management

Pyridine is a conjugate base which reacts with H+ (such as HCl) to form pyridine hydrochloride....

Pyridine is a conjugate base which reacts with H+ (such as HCl) to form pyridine hydrochloride. The pyridine hydrochloride dissociates to yield H+ with a pKa of 5.36. Describe the preparation of 1.0 liter of a 0.2 M pyridine buffer at pH 5.2 starting with 1.0 M pyridine and 0.5 M HCl.

In: Chemistry

Consider the reaction HCN(aq) H+(aq) +CN-(aq). the equilibrium constant is 6.2*10^-10. If you place 0.4 mols...

Consider the reaction HCN(aq) H+(aq) +CN-(aq). the equilibrium constant is 6.2*10^-10. If you place 0.4 mols of HCN in a 2.0 liter flask, what is the equilbrium of CN-? so far ive got to x=x(0.2)(6.2*10^-10)

In: Chemistry