1. (A) If an increase in pollution abatement or environmental quality would increase social net benefit, what change in the allocation of society’s scarce resources between “other things” and the environment would be necessary to capture the increase in net benefits?

(B) Define what is revenue, how is it generated, and what change in the allocation of society’s scarce resources would be created by an increase in revenue.

(C) What is cost, how is it generated, and what change in the allocation of society’s scarce resources would be create by an increase in the cost of an input.

(D) Explain how a current user of land, to produce a private good such as agriculture or timber, would become a producer of a public good such as wildlife, biodiversity or carbon sequestering.

(E) Explain why having no price required to be paid for using or consuming environment services results in underproduction of environmental services.

You are the Finance Director of a start-up that delivers online ads to end users and you are about to approve the budget for the next fiscal year. You notice that your team has projected the annual revenue goal through equal increase of monthly ad deliveries, which assumes least number of deliveries in January and the most number of deliveries in December. Before approving the budget, you want to make sure that there is indeed such a difference between the monthly number of ads delivered. You pull out the data for the current year to perform analysis of variance on the mean number of ads delivered per month. Describe: (1) which method for analysis of variance you will choose and why; (2) what statistical results you want to see in order to approve the proposed revenue plan as it is.

Please refer 2 items as below from Microsoft’s Letter to Shareholders as below. And refer them to Porter’s five forces.

Data and AI

Our customers will increasingly need to build their own AI to extract insights from the ever-increasing amount of data they collect — and we are investing to make Azure the best cloud for their comprehensive data estates. We are democratizing data science and AI with Azure Cognitive Services, Azure Machine Learning and data services such as Azure Cosmos DB — the first globally distributed, multi-model database — to help organizations of all sizes convert their data into insights and experiences for competitive advantage. In less than a year, Azure Cosmos DB has already exceeded $100 million in annualized revenue. Azure Database for MySQL and PostgreSQL makes it even easier to bring open source-powered applications to Azure, expanding our opportunity in this space. And we are seeing rapid customer adoption of Azure Databricks for data preparation, advanced analytics and machine learning scenarios. We are leading in the field of AI research, achieving human parity with object recognition, speech recognition, machine reading and — this year — language translation. But that is not enough. We are committed to translating these breakthroughs into toolsets our customers can use. More than 1 million developers have already used our Cognitive Services to quickly and easily create AI applications. Our Azure Bot Service has nearly 300,000 developers, and we are driving new advances in our underlying cloud infrastructure, building the world’s first AI supercomputer in Azure. Microsoft Translator brings AI-powered translation to developers where their data is, whether in the cloud or on the edge. Our pending acquisition of GitHub recognizes the increasingly vital role developers will play in value creation and growth across every industry, and will enable us to bring our tools and services to new audiences while enabling GitHub to grow and retain its developer-first ethos.

Gaming

We are pursuing an expansive opportunity in gaming — from the way games are created and distributed to how they are played and viewed — surpassing $10 billion in revenue this year for the first time. We are investing aggressively in content, community and cloud services across every endpoint to expand usage and deepen engagement with gamers. Xbox Live now has 57 million monthly active users, and we are investing in new services like Mixer — which blurs the line between watching and playing — and Game Pass, our new unlimited subscription service. The addition of five new gaming studios this year bolsters our first-party content development to support our fast-growing gaming services. And our acquisition of PlayFab accelerates our vision to build a world-class cloud platform for the gaming industry across mobile, PC and console. I’m excited about our opportunity in the fast-growing $100 billion gaming market and what’s to come.

The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, yˆ=b0+b1x , for predicting the number of bids an item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Price in Dollars 25 27 28 30 45 Number of Bids 1 4 6 8 9 Table Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places. Step 3 of 6: Find the estimated value of y when x=30 . Round your answer to three decimal places Step 4 of 6: Determine the value of the dependent variable yˆ at x=0 Step 5 of 6: Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the value of the independent variable is increased by one unit, then find the change in the dependent variable yˆ. Step 6 of 6: Find the value of the coefficient of determination. Round your answer to three decimal places.

The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, yˆ=b0+b1xy, for predicting the number of bids an item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant.

Step 1 of 6: Find the estimated slope. Round your answer to three decimal places.

Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places.

Step 3 of 6: Find the estimated value of y when x=31. Round your answer to three decimal places.

Step 4 of 6: Determine the value of the dependent variable yˆy^ at x=0x=0.

answer choice: (a) b0 (b) b1 (c) x (d) y

Step 5 of 6: Determine if the statement "Not all points predicted by the linear model fall on the same line" is true or false.

Step 6 of 6: Find the value of the coefficient of determination. Round your answer to THREE decimal places.

a.If n = 21, x¯ = 44, and s = 10, construct a confidence interval at a 99% confidence level. Assume the data came from a normally distributed population. Give your answers to three decimal places. =    < u <

b.Assume that a sample is used to estimate a population mean μ . Find the 80% confidence interval for a sample of size 1058 with a mean of 65.2 and a standard deviation of 10.1. Enter your answer as a tri-linear inequality accurate to 3 decimal places.=    < μ <

c. The effectiveness of a blood-pressure drug is being investigated. An experimenter finds that, on average, the reduction in systolic blood pressure is 63.1 for a sample of size 27 and standard deviation 13.5. Estimate how much the drug will lower a typical patient's systolic blood pressure (using a 99% confidence level). Assume the data is from a normally distributed population. Enter your answer as a tri-linear inequality accurate to three decimal places.= <μ<   

d. Assume that a sample is used to estimate a population proportion p. Find the 98% confidence interval for a sample of size 209 with 21% successes. Enter your answer as an open-interval (i.e., parentheses) using decimals (not percents) accurate to three decimal places.
CI=

e. If n = 590 and X = 472, construct a 99% confidence interval for the population proportion, p. Give your answers to three decimals

Keep the Old Car or Buy a Used Car
Manny is an online student who currently owns an older car that is fully paid for. He drives, on average, 160 miles per week to commute to work. With gas prices currently at $2.02 per gallon, he is considering buying a used, fuel-efficient car, and wants to know if it would be a good financial decision.

The old car Manny owns currently gets 15 miles per gallon for average fuel efficiency. It has been a great vehicle, but with its age, it needs repairs and maintenance that average $800 per year (as long as nothing serious goes wrong).

He is considering buying a newer used car that will cost a total of $7,500 over a three-year loan process. The used car gets 27 miles per gallon and would only require an average of $10 per month for general maintenance. To help make a decision Manny wants to calculate the total costs for each scenario over three years. He decides to use the Quantitative Reasoning Process to do this.

Find the total costs (gas, maintenance/repairs, purchase price) for each scenario over the three years.

Round your answers to the nearest dollar.

An engineer suspects that the surface finish of a metal part is influenced by the feed rate and the depth of cut. He selects three feed rates and four depths of cut. He then conducts a factorial experiment and obtains the following data:

Produce the following for each problem:

• Residuals table
• Table to produce a Normal Probability Plot
• Normal probability plot in Normal paper
• Conclusion about Normal probability plot
• Residuals vs. Fitted values plot
• Residuals vs. Factor plot (for each factor)
• Conclusions after each plot
• Final conclusion about the adequacy of the model

Use MiniTab to produce the plots and models

Connor is a statistics student interested in the number of games won by each team per season during the past 12 years for a certain professional baseball league. He records the total number of wins x for each team each season and the probability of each value P(x), as shown in the table provided. Use Excel to find the mean and the standard deviation of the probability distribution. Round the mean and standard deviation to three decimal places. Number of wins, x P(x) 54 0.003 55 0.009 56 0.015 57 0.012 58 0.006 59 0.018 60 0.024 61 0.036 62 0.027 63 0.045 64 0.036 65 0.045 66 0.039 67 0.054 68 0.051 69 0.060 70 0.054 71 0.071 72 0.059 73 0.045 74 0.042 75 0.030 76 0.033 77 0.036 78 0.027 79 0.024 80 0.021 81 0.018 82 0.012 83 0.015 84 0.015 85 0.009 86 0.006 87 0.003