If you have a chance please answer as many as possible, thank you and I really appreciate your help experts!

Question 6 2 pts

A scientist claims that the mean gestation period for a fox is 51.5 weeks. If a hypothesis test is performed that rejects the null hypothesis, how would this decision be interpreted?

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Question 7 2 pts

A marketing organization claims that less than 15% of its employees are paid minimum wage. If a hypothesis test is performed that fails to reject the null hypothesis, how would this decision be interpreted?

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Question 8 2 pts

A sprinkler manufacturer claims that the average activating temperatures is at least 132 degrees. To test this claim, you randomly select a sample of 32 systems and find the mean activation temperature to be 133 degrees. Assume the population standard deviation is 3.3 degrees. Find the standardized test statistic and the corresponding p-value.

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Question 9 2 pts

A consumer group claims that the mean acceleration time from 0 to 60 miles per hour for a sedan is 7.0 seconds. A random sample of 33 sedans has a mean acceleration time from 0 to 60 miles per hour of 7.6 seconds. Assume the population standard deviation is 2.3 seconds. Find the standardized test statistic and the corresponding p-value.

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Question 10 2 pts

A consumer research organization states that the mean caffeine content per 12-ounce bottle of a population of caffeinated soft drinks is 37.8 milligrams. You find a random sample of 48 12-ounce bottles of caffeinated soft drinks that has a mean caffeine content of 35.2 milligrams. Assume the population standard deviation is 12.5 milligrams. At α=0.05, do you support or reject the organization’s claim using the test statistic?

Developmental Psychology

Reflect on the following case study:

1. What are the risk factors and the protective factors when it comes to "successful aging" for Frank? For Ellen?

2. Reflect on how the current situation might impact Frank and Ellen's coping with the psychosocial crisis of Generativity vs. Stagnation, and entering the next stage of Integrity vs. Despair.

Case Study: Frank and Ellen Schaeffer

Frank, age 66, and Ellen, age 64, have declared bankruptcy, and their home is in foreclosure. They have had to move about 60 miles away from their old home, and are new to the community. They are seeking assistance, especially ways to pay for Ellen's prescription drug costs, which amount to approximately $600 per month, above what is covered by Medicare. The drugs are for diabetes management, high blood pressure, and pain management from a degenerating spine. They have managed to find a place to rent within the past month (which is about half of the size of their old home), but it costs about 43% of their fixed income from Social Security and a small pension that Frank receives from his 23 years of working for a telecommunications company. Because of the bankruptcy, they have no credit cards and use cash/checks for all transactions.

Both are exhibiting signs of extreme stress. Frank says "he's fine," but upon questioning, reports a noticeable loss of weight in the past 3 months, trouble sleeping, and his smoking has increased. He appears irritable, and he expresses sarcasm when asked about their financial situation, the past several months of trying to look for employment, or their attempts to work with banks and government agencies. Ellen reports a significant increase in her smoking, insomnia, but no change in her weight (although she is noticeably overweight for her height). She discloses that she cries about 1-2 times a week, for the past 6-8 months. Ellen mentions that both she and Frank have trouble with remembering things sometimes, especially lately. She is especially concerned about Frank.

Frank and Ellen have been married for 43 years, and have three sons and a daughter. The adult children live about 70 miles away. They help out as much as they can financially, and they are in contact with Frank and Ellen at least once a week. Frank and Ellen both report a strong marriage -- but noticeable estrangement from their own families of origin, their brothers and sisters. Ellen has one friend whom she sees about once a month. Most of their time is spent watching TV, and Frank works on a vintage car in the garage. They call themselves spiritual, but they do not practice any religion nor are they members of any religious organization.

Frank and Ellen both have high school diplomas, but no higher education. Frank has gone through many technical training programs in the course of his work for the telecommunications company, where he worked for 23 years in a variety of capacities, but most of that time involving the installation of computer/ telecommunications networks for office buildings. For the past 15 years, Frank has been working for a different company that contracts out to his original employer, for installing networks. The past 4 years, Frank has worked for this smaller satellite company as a contract worker, on call for different office building contracts. These projects are sporadic, involving stints of work for 2-3 weeks at a time. Frank obviously wants to work, but is clearly frustrated by the lack of job opportunities and feels that no one will hire someone his age. Ellen spent many years taking care of children in their home, but now can no longer do that because of pain and mobility problems, and the loss of their home of 35 years.

2.        Shauna Coleman is single. She works as an architectural designer for Streamline Design (SD).For 2018, she correctly calculated her AGI to be $107,000. However, she wasn’t sure how to compute the rest of her taxable income. She provided the following information with hopes that you could use it to determine her 2018 federal income tax return.

a.           Shauna paid $4,680 for medical expenses for care from a broken ankle sustained in a biking accident. Blake, Shauna’s boyfriend, drove Shauna (in her car) a total of 115 miles so that she could receive care for the broken ankle.

b.          Shauna paid a total of $3,400 in health insurance premiums during the year (not through an exchange). SD did not reimburse any of this expense. Besides the health insurance premiums and the medical expenses for her broken ankle, Shauna had Lasik eye surgery last year and she paid $3,000 for the surgery (she received no insurance reimbursement). She also incurred $450 of other medical expenses for the year.

c.           SD withheld $1,800 of state income tax, $7,495 of Social Security tax, and $14,500 of federal income tax from Shauna’s paychecks throughout the year.

d.          In 2018, Shauna was due a refund of $250 for overpaying her 2017 state taxes. On her 2017 state tax return that she filed in April of 2018, she applied the overpayment towards her 2018 state tax liability. She wasn’t sure but she estimated that her state tax liability for 2018 will be $2,300.

e.           Shauna paid $3,200 of property taxes on her personal residence. She also paid $500 to the developer of her subdivision, because he had to replace the sidewalk in certain areas of the subdivision.

f.            Shauna paid a $200 property tax based on the state’s estimate of the value of her car.

g.           Shauna has a home mortgage loan in the amount of $220,000 that she secured when she purchased the home. The home is worth about $400,000. Shauna paid interest of $12,300 in interest on the loan this year.

h.          Shauna made several charitable contributions throughout the year. She contributed stock in ZYX Corp. to the Red Cross. On the date of the contribution, the FMV of the donated shares was $1,000 and her basis in the shares was $400. Shauna originally bought the ZYX Corp. stock in 2008. Shauna also contributed $300 cash to State University and religious artifacts she has held for several years to her church. The artifacts were valued at $500 and Shauna’s basis in the items was $300. Shauna had every reason to believe the church would keep them on display indefinitely. Shauna also drove 200 miles doing church-related errands

i             Shauna paid $250 in investment advisory fees and another $150 to have her tax return prepared (that is, she paid $150 in 2018 to have her 2017 tax return prepared).

j.            Shauna is involved in horse racing as a hobby. During the year, she won $2,500 in prize money (which she is including in income) and incurred $10,000 in expenses. She has never had a profitable year with her horse racing activities, so she acknowledges that this is a hobby for federal income tax purposes.

k.              Shauna sustained $2,000 in gambling losses over the year (mostly horse-racing bets) and   only had $200 in winnings (which she is including in income)

Required: Determine Shauna’s 2018 taxable income starting with Adjusted Gross Income of $107,000 reported on line 7 of Form 1040 and complete page 2 of Form 1040 through Taxable Income, line 10. Also complete Schedule A, Itemized Deductions.

Is the percentage average room rate increase from May to August affected by the number of stars of a hotel? In order to answer this question you are asked to use one way analysis of variance. 1.1 Compute the percentage Average Room Rate Increase from May to August for each hotel in the sample, rounding up to the second decimal. Call this variable PCT_ARR_INCREASE. 1.2 State the null and alternative hypotheses. 1.3 Test the null hypothesis at the 5% significance level. 1.4 What can you conclude from the above findings? 1.5 A friend of yours insists that the data clearly show that 5-star hotels have larger percentage average room rate increases than lesser star hotels so he/she is confident that the number of stars affects the percentage average room increase. What would be your answer to him/her be?

STARS   ARR_MAY   ARR_AUG
5 95 160
5 94 173
5 81 174
5 131 225
5 90 195
5 71 36
5 85 114
4 70 159
4 64 109
4 68 148
4 64 132
4 59 128
4 25 63
3 76 130
3 40 60
3 60 70
3 51 65
3 65 90
2 45 55
1 35 90
4 22 51
4 70 100
3 60 120
3 40 60
3 48 55
2 52 60
2 53 104
2 80 110
2 40 50
1 59 128
4 90 105
3 94 104
2 29 53
2 26 44
1 42 54
1 30 35
2 47 50
1 31 49
1 35 45
1 40 55
1   40 55
1   35 40
3   40 55
4   57 97
2   35 40
5   113 235
5   61 132
5   112 240
5   100 130
4   87 152
4   112 211
4   95 160
4   47 102
4   77 178
4   48 91
3   60 104
3   25 33
5   68 140
4   55 75
3   38 75
3   45 70
3   45 90
5   100 180
4   180 250
3   38 84
3   99 218
3   45 95
2   28 40
2   30 55
1   16 35
3   40 70
2   60 100
1   16 20
2   22 41
2   55 100
1   40 100
1   80 120
1   80 120
1   18 35
3   80 100
2   30 45
1   40 65
1   30 50
1   25 70
1   30 35
4   215 265
4   133 218
2   35 95
2   100 150
2   70 100
5   60 90
5   119 211
5   93 162
5   81 138
5   44 128
5   100 187
5   98 183
5   100 150
5   102 211
5   103 160
4   40 56
4   69 123
4   112 213
4   80 124
3   53 91
4   73 134
4   94 120
4   70 100
3   40 75
3   50 90
3   70 120
3   80 95
3   85 120
3   50 80
3   30 68
3   30 100
2   32 55
2   50 90
2   70 120
2   30 73
2   94 120
4   100 180
2   70 120
2   19 45
2   35 70
2   50 80
1   25 45
1   30 50
2   55 80
3   95 120
1   25 31
1   16 40
1   16 40
1   19 23
1   30 40 THREE COLUMNS (STARS -ARR_MAY-ARR_AUG)

PLEASE ANSWER QUESTION 1.3,1.4,1.5

THANKS IN ADVANCE

JAVA Programming.

How Long is this Gonna Take?

Undergraduate students are surprised to learn that as much intellectual energy has been invested in sorting and searching as almost any other part of Computer Science. Think of Duke Energy's customer database—it’s huge. New customers have to be added, former ones deleted, bills must be sent out, customers send in their payments and inquire about their accounts. An efficient data organization is required for Duke to function at all. The first attack on organizing data involves sorting data elements into some order, and exploiting that order when trying to retrieve a particular element.

Hundreds of sorting algorithms have been developed, and like all sorting algorithms, Selection Sort accomplishes its task by making comparisons and data movements. We often compare algorithms by counting the number of comparisons and movements required—the fewer the better. This begs the question, how many comparisons and movements does the Selection Sort make? And, are these actions affected by the initial arrangement of data values in the array? This is the focus of this lab.

Objectives

By the end of this lab students should be able to

• Allocate arrays
• Initialize an array with random numbers
• Initialize an array to be contain monotonically increasing and decreasing values
• Sort arrays
• Explain how sorting time increases as the number of elements to be sorted increases

Collecting Sorting Data

Start with the SelectionSort class in the zip file attached to this item. Keep the name SelectionSort, and add a main method to it.

• Modify the selectionSort method to have two counters, one for the number of comparisons, and one for the number of data swaps. Each time two data elements are compared (regardless of whether the items are in the correct order—we're interested in that a comparison is being done at all), increment the comparison counter. Each time two data items are actually swapped, increment the data swap counter.
• At the end of the selectionSort method, print the size of the sorted array, and the counters. (Be sure to identify which counter is which in your print message
• In your main method,
  • Declare a final int, NUM_ELEMENTS. Initially set NUM_ELEMENTS to 10 to debug your program.
  • Declare and create three double arrays of NUM_ELEMENTS length, lo2Hi, hi2Lo, random.
  • Initialize the first array, lo2Hi, with values 1.0, 2.0, …, NUM_ELEMENTS
  • Initialize the second array, hi2Lo with values NUM_ELEMENTS, 24.0,…, 1.0
  • Initialize the third array, random, with random double values between 0.0 and less than 1.0
  • call the selectionSort method using each array. (Note: you might want to print the array elements themselves for debugging purposes when NUM_ELEMENTS is small, but you’ll not want to print them with larger values for NUM_ELEMENTS.)
• Run your program three times with different values for NUM_ELEMENTS: 1000, 2000 and 4000.

In your submission write some text describing the relationship between the number of comparisons of the various values of NUM_ELEMENTS. For example, what do we find if we divide the number of comparisons for 2000 elements by the number of comparisons for 1000 elements? What do we find if we divide the number of comparisons for 4000 elements by the number of comparisons for 2000 elements?

Epilog: As you can tell, Selection sort doesn’t scale very well. The number comparisons increase quadradically as a function of number of elements. There comes a point that, because of array size, it’s impractical to use Selection sort. The good news is there are hundreds of sorting algorithms. Some suffer from the same performance shortcomings as Selection sort, but others that are almost “magical” in that increasing the number of elements has minor impact on performance. If you’re interested, take a look at chapter 23 Sorting.

Reporting Sorting Data

Submit, in addition to your program, submit the following information in some understandable form (it doesn’t have to be this exact table, but your submission should contain this information).

Grading Elements

• use class SelectionSort with the selectionSort method
• instrument selectionSort with comparisonCnt and swapCnt, and print the number of array elements and the comparisonCnt and swapCnt values
• write a main method with final int NUM_ELEMENTS
• declare and create three double arrays of length NUM_ELEMENTS
• initialize the arrays as specified
• call selectionSort with each array
• Run the SelectionSort with different values for NUM_ELEMENTS: 1000, 2000 and 4000.
• Document the 18 data values described above.
• Document the ratio of comparisonCnt values for 2000 elements and 1000 elements.
• Document the ratio of comparisonCnt values for 4000 elements and 2000 elements

SelectionSort.java 
public class SelectionSort {
  /** The method for sorting the numbers */
  public static void selectionSort(double[] list) {
    for (int i = 0; i < list.length - 1; i++) {
      // Find the minimum in the list[i..list.length-1]
      double currentMin = list[i];
      int currentMinIndex = i;

      for (int j = i + 1; j < list.length; j++) {
        if (currentMin > list[j]) {
          currentMin = list[j];
          currentMinIndex = j;
        }
      }

      // Swap list[i] with list[currentMinIndex] if necessary;
      if (currentMinIndex != i) {
        list[currentMinIndex] = list[i];
        list[i] = currentMin;
      }
    }
  }
}

The purpose of this assignment is to practice working with marketing research data, searching for patterns in the numbers that might lead you to a new understanding about consumers, their behaviors or their preferences. Download the McSandwich Excel spreadsheet that lists the responses given by 50 customers of the fast food restaurant. The customers were asked questions about the food (quality & variety), service (friendly, fast & competent), pricing, the overall experience (recommend to a friend, general satisfaction), and some personal information (gender, frequency of dining there, and how close to the restaurant they lived). Sort the responses by gender (0 = male, 1 = female) and use the “Average” function to determine if males and females had different opinions about the restaurant’s food, service, pricing and overall experience. Sort the responses again, this time by usage (0 = infrequent diner, 1 = frequent diner). Once again, use the “Average” function to determine if frequent diners and infrequent diners had different opinions about the restaurant’s food, service, pricing and overall experience. Sort the responses one last time, this time by home location (1 = less than a mile from the restaurant, 2 = 1-5 miles from the restaurant, 3 = more than 5 miles from the restaurant). Again, use the “Average” function to determine if nearby and more distant consumers had different opinions about the restaurant’s food, service, pricing and overall experience. In a 2 page document, summarize your conclusions from the three different ways you examined the data. Please include the specific numeric data that led you to those conclusions. Then, describe at least 3 recommended marketing actions for McSandwich, based on those conclusions.

Chloe has done the accounting through August 16, the first sixteen days of business for her company. She has given you her trial balance as of August 16, 2016 below.

Chloe’s Cleaning Services

UNADJUSTED TRIAL BALANCE

August 16, 2016

Chloe Sanderson, a friend of yours from business school, decided to be her own boss and start a business cleaning homes and offices after graduation. Although she was a general business major in college, she always enjoyed accounting; but she’s a little uncertain about what type of accounting system might be best for her fledgling business. She has already hired two employees to work for her, so she would like your help as soon as possible to set things up correctly.

Chloe already has three clients and two vendors, so she’d like to use two subsidiary ledgers: one for accounts receivable and one for accounts payable.

In addition, since would like to streamline her accounting by using four special journals she recalls from business school: a revenue journal, cash receipts journal, purchases journal, and cash payments journal.

Using what she remembers from business school, Chloe has prepared a list of accounting tasks for her business, and would like you to review it.

Determine whether each item should be on a given list. If so, select “Correct.” If not, select “Error,” choosing the correct list for the item.

Chloe has prepared the table below, showing the balances as of August 16 for her Accounts Receivable Subsidiary Ledger and Accounts Payable Subsidiary Ledger.

You’ve received a list of the remaining August transactions from Chloe.

Review the transactions, and then complete the table to give Chloe instructions on how to enter the transactions in her accounting system, using the following abbreviations. The transactions should be entered without considering end-of-month posting of totals, adjusting entries, or closing entries..

As a part of the federal Clean Air Act Amendments Congress established a national goal of preventing future and resolving existing regional haze in national parks and wilderness areas when the visibility impairment results from manmade air pollution. The law requires states to submit implementation plans to the United States Environmental Protection Agency (EPA). The implementation plans must include identifying major industrial sources of air pollution that have caused or contributed to visibility impairment in national park and wilderness areas.

In the state implementation plan, any facility identified as a major source of air pollution must reduce air pollution by installing the best available retrofit technology (BART)—as determined by the state. To determine the BART, the law requires the following factors be considered: (1) the technology available, (2) the costs of compliance, (3) the energy impacts and non-air quality environmental impacts of compliance, (4) any pollution control equipment currently being used at the source, (5) the remaining useful life of the source, and (6) the degree of improvement in visibility reasonably anticipated to result from the use of such technology. The law requires the EPA Regional Administrator—“after an opportunity for a public hearing”—to approve or disapprove a state’s determination of the BART and the emission limits for any identified source. The legislative history for the Clean Air Act doesn’t indicate what type of hearing is required or the specific procedures to be used in the “public hearing.”

A party may request the EPA Administrator reconsider the approval or disapproval of the state’s BART determination, but that request for reconsideration doesn’t extend the time for filing a petition for judicial review or postpone the effectiveness of the action. Any Petition for Judicial Review of the BART determination must be filed in the District of Columbia Court of Appeals within 60 days of the Regional Administrator’s decision of the approval or disapproval of the BART determination.

If a facility fails to install the air pollution control measures required by the BART determination by the deadline set forth in the determination, the EPA can bring an action in court to enforce the BART determination, which could include imposing a substantial fine.

The state of West Dakota has identified the Poison Valley Power Plant—a coal-fired power plant in West Dakota—as a major source of air pollution contributing to visibility impairment in White Hills National Park. The West Dakota Department of Natural Resources issued a determination that the best available retrofit technology (BART) for the Poison Valley Power Plant is Selective Noncatalytic Reduction (SNCR) technology and set an emission limit of 0.20 lbs/MMBtu (pounds per million British thermal units).

In its determination, the state rejected a proposal by the Stormy Plateau Tribe, an Indian tribe with a reservation located within a mile of the Poison Valley Power Plant, and an environmental group, Citizens Advocating Renewable Energy (CARE) to use Selective Catalytic Reduction (SCR) technology—a more costly but more effective emission-reducing technology. The state also rejected the Poison Valley Power Plant’s proposal, which was that no additional emissions controls should be installed because the new pollution control equipment would be too expensive and could close the plant. The basis for the state’s BART determination was that additional emission controls were required because Poison Valley Power Plant was a substantial contributor to the haze problem in White Hills National Park. In terms of the choosing SNCR over SCR, the state determined the estimated 5 percent increase in visibility improvement using SCR technology was outweighed by the increased cost of SCR. State documents estimated SNCR technology would cost about $4.3 million per year compared to $16.3 million per year for SCR technology.

The Region 25 Office of the United States EPA issued the attached notice to interested parties on July 15, 2017. The notice was posted on the EPA Region 25 Facebook page and the notice was emailed to all the parties who participated and offered comments to the state of West Dakota DNR in its BART proceeding.Poison Valley Power Plant, Stormy Plateau Tribe, and CARE all opposed West Dakota’s determination of the BART (for different reasons). Each objected to the “open-house” process outlined in the notice and contended a trial-type hearing was required by the US Constitution and federal APA to challenge West Dakota’s determination of the BART and the emission limits. In addition, Poison Valley Power Plant, Stormy Plateau Tribe and Care requested the underlying data used by West Dakota officials in making its BART determination be disclosed and an opportunity to cross-examine a DNR official about the data. Regional Administrator Giva Hoot denied the requests for a trial-type hearing, disclosure of data, and cross-examination. The parties provided written and oral comments at the open house. Regional Administrator Giva Hoot approved West Dakota’s determination that SNCR technology is the BART for Poison Valley Power Plant and approved the 0.20 lbs/MMBtu limit on NOx, but she offered no reasons for her action. Instead, on October 1, 2017, she mailed a letter to all those participating in the open house and posted a statement on www.facebook.com/EPA/Region25 stating she had the discretion to approve or deny the BART determination and no law or rule required her to give her reasons. The statement simply

July 15, 2017                          NOTICE

ENVIRONMENTAL PROTECTION AGENCY ANNOUNCES PROPOSED BEST AVAILABLE RETROFIT TECHNOLOGY (BART) DETERMINATION, OPEN HOUSE, AND REQUEST FOR PUBLIC COMMENT

The Region 25 Office of the United States Environmental Protection Agency (EPA) requests public comment on a proposed state implementation plan for implementing Best Available Retrofit Technology (BART) at Poison Valley Power Plant located near Peabody, West Dakota. The Clean Air Act’s Regional Haze Rule requires the use of BART at older coal-fired power plants like PVPP to reduce haze and improve visibility in nearby national parks and wilderness areas.

EPA is proposing to approve West Dakota’s determination that Selective Non-catalytic Reduction (SNCR) technology is the BART for Poison Valley Power Plant and its limits on emissions of nitrogen oxide (NOx) is set at 0.20 lbs/MMBtu (pounds per million British thermal units), which must be implemented by January 1, 2020.

EPA is holding an open house on the proposal and an opportunity for the public to comment on September 1, 2017, at the Peabody High School in Peabody, West Dakota. Any person may provide written comments and/or oral comments regarding our proposal at the open house.

If you have questions about the public hearings or how to submit comments, please contact Giva Hoot, EPA Region 25 Administrator at 415-947-4139, or at [email protected]. Please bring this notice to the attention of all persons who may have an interest in our proposal.

Posted on www.facebook.com/EPA/Region25 and sent to interested parties

GIVA HOOT

Region 25 Administrator

Poison Valley Power Plant, Stormy Plateau Tribe, and CARE all opposed West Dakota’s determination of the BART (for different reasons). Each objected to the “open-house” process outlined in the notice and contended a trial-type hearing was required by the US Constitution and federal APA to challenge West Dakota’s determination of the BART and the emission limits. In addition, Poison Valley Power Plant, Stormy Plateau Tribe and Care requested the underlying data used by West Dakota officials in making its BART determination be disclosed and an opportunity to cross-examine a DNR official about the data. Regional Administrator Giva Hoot denied the requests for a trial-type hearing, disclosure of data, and cross-examination. The parties provided written and oral comments at the open house. Regional Administrator Giva Hoot approved West Dakota’s determination that SNCR technology is the BART for Poison Valley Power Plant and approved the 0.20 lbs/MMBtu limit on NOx, but she offered no reasons for her action. Instead, on October 1, 2017, she mailed a letter to all those participating in the open house and posted a statement on www.facebook.com/EPA/Region25 stating she had the discretion to approve or deny the BART determination and no law or rule required her to give her reasons. The statement simply concluded “West Dakota’s determination is approved.”

In individual petitions for judicial review filed in federal court on November 1, 2017, Poison Valley Power Plant, Stormy Plateau Tribe, and CARE all challenged Regional Administrator Giva Hoot’s decision to approve West Dakota’s BART determination and emission limit for the Poison Valley Power Plant and the process used to approve the determination as violating the Constitution and the federal APA. None of the parties requested reconsideration of the decision before filing their lawsuits.

In its complaint, Poison Valley Power Plant alleged the approval violated the Clean Air Act and was arbitrary and implementing SNCR technology would cause economic hardship for the company.

In its complaint, Stormy Plateau Tribe alleged that the approval violated the Clean Air Act, just rubber-stamped the state’s action, and ignored the evidence that Poison Valley Power Plant’s mercury emissions were causing health problems for tribal members, which would be reduced by implementing Selective Catalytic Reduction (SCR) technology.

CARE’s members all reside in South Dakota and its complaint alleged that the EPA’s selection of SNCR technology as the BART for Poison Valley Power Plant might be used as precedent in its upcoming review of South Dakota’s state implementation plan. CARE alleged its members are concerned about the haze problems in Mount Rushmore and Badlands National Parks in South Dakota and contend that only SCR technology will fix the pollution problems with the South Dakota power plants.

You are the judge and must write a decision analyzing the legality of EPA Regional Administrator Giva Hoot’s actions, and in doing so, address the following points (make sure you define and explain the important terms and principles mentioned below):

Assume the decision can be reviewed by the court in answering all the questions below.

Applying the principles of Citizens to Preserve Overton Park v. Volpe, explain what you—as the reviewing judge—would do to overcome the failure of the EPA Regional Administrator to provide any justification for her decision and why??

Volkswagen in Russia In the mid-2000s, Volkswagen announced that it would invest directly in automobile production in Russia. The decision to invest was driven by a number of factors. Russia’s economy was growing rapidly at the time and living standards were rising, while the level of car ownership per capita was still low by European standards. This suggested that demand for cars would grow rapidly going forward. Indeed, forecasts predicted that by 2020, Russia would surpass Germany to become the largest car market in Europe. Moreover, Volkswagen’s global rivals, including most notably Toyota, General Motors, and Ford, were also investing in production facilities in Russia, so Volkswagen felt that it had to make direct investments in order to avoid being preempted by its rivals. The Russian government also createdPage 238 incentives for carmakers to invest directly in Russian production facilities, allowing them to avoid import tariffs and a punitive tax on imports of parts if they produced at least 25,000 cars in the country. In 2011, the government announced that it would keep tariffs on imported components at 0.3 percent if a foreign automaker built at least 300,000 in the country by 2020 and produced 60 percent of the value of the car locally. Spurred on by such incentives, in 2007 Volkswagen opened a plant in Kaluga, 160 miles southwest of Moscow, to build some of its VW and Skoda car brands. The plant was projected to have a peak capacity of 150,000 units a year and employ 3,000 people. Initially all vehicles at the plant were assembled from semi-knocked-down kits imported from Germany. In October 2009, however, the plant launched full-scale production, including welding and painting of vehicles. In October 2011, Volkswagen announced that, together with a local partner, GAZ Group, it would open a second plant near St. Petersburg, as it strove to reach the 300,000 units of local production by 2020. In 2013, Volkswagen made an additional investment in Kaluga when it pledged 300 million euros to build an engine plant near to its assembly operation. The engine plant opened in September 2015. All told, by this point Volkswagen had invested over $1 billion in production in Russia. General Motors and Toyota had also announced investments of over $1 billion to boost Russian production up to 300,000 units by 2020, and Fiat had indicated that it would make investments to bring its Russian production up to 300,000 as well. In total, foreign carmakers had invested over $5 billion in Russian assembly operations by 2014. Meanwhile, analysts continued to predict that the Russian car market would grow at a healthy pace and exceed that of Germany by 2020. In 2014, however, the market took a sharp turn for the worse. Russia is a major oil producer. Since the mid-2000s, much of the country’s economic growth had been powered by high oil prices. In the second half of 2014, however, global oil prices started to fall rapidly as increased production in America and weak demand in China conspired to create a global glut of oil. By early 2016, oil prices had fallen 80 percent from their peak. To make matters worse, following hard on the heals of its hostile takeover of the Crimea region from Ukraine, Russia had become embroiled in a smoldering civil war in eastern Ukraine. Western nations responded to what they perceived as Russian aggression by imposing sanctions on Russia. Hit by these twin blows, the Russian economy weakened significantly in 2014 and 2015, and the ruble declined precipitously, losing 50 percent of its value against the U.S. dollar. Suddenly the bright hopes that foreign automakers had for the Russian market seemed to be tarnished. Faced with falling demand, Volkswagen cut production at its Kaluga plant to 120,000 vehicles from a planned 150,000. With the new engine plant scheduled to come on line and no resolution to Russia’s economic crisis insight, Volkswagen’s excess capacity problem may get worse. Looking forward, Volkswagen has to decide whether to keep investing in Russia in order to hit the magic 300,000 local output figure by 2020 or to pull back from a market whose future suddenly looks highly uncertain. At this point, it looks as if Volkswagen is staying the course. In late 2015, a Volkswagen board member noted that “We need to continue to strengthen our partnership (in Russia) despite the current situation”.* Sources: Sarah Sloat, “Volkswagen to Halt Production at Russian Plant for 10 Days,” The Wall Street Journal, September 7, 2014; Clare Nuttall, “Foreign Car Firms Invest Heavily in Russia,” The Telegraph, April 28, 2011; Staff reporter, “Volkswagen Russia Shows the Way,” Automotive Supply Chain, July 2, 2013; Staff reporter, “Volkswagen Slashes Car Production at Russian Plat,” Reuters, September 7, 2014.

Question: Volkswagen has signaled that it is going to stay the course in Russia, despite current political and economic headwinds. Why do you think it made this decision? What are the pros and cons of this decision?