1. Which of the following variables is an example of a categorical variable?

a) The amount of money you spend on eating out each month.

b) The time it takes you to write a test.

c) The geographic region of the country in which you live.

d) The weight of a cereal box.

2. Which of the following is an example of a discrete random variable?

a) The monthly electric bill for a local business.

b) The number of people eating at a local café between noon and 2:00 p.m.

c) The amount of time it takes for a worker to complete a complex task.

d) The percentage of people living below the poverty level in Boston.

3. A measurement scale that rates product quality as either 1 = poor, 2 = average and 3 = good is known as:

a) Nominal

b) Ordinal

c) Interval

d) Ratio

4. Which of the following statements involve descriptive statistics as opposed to inferential statistics?

a) The Alcohol, Tobacco and Firearms Department reported that Seattle had 1,825 registered gun dealers in 2013.

b) Based on a survey of 380 magazine readers, the magazine reports that 30% of its readers prefer double column articles.

c) The FAA samples 425 traffic controllers in order to estimate the percent retiring due to job stress related illness.

d) Based on a sample of 350 professional baseball players, a baseball magazine reported that 23% of the parents of all professional baseball players did not play baseball.

5. Suppose a survey is taken of 300 high school seniors out of a total of 1,000 seniors. This group is probably a:

a) Sample

b) Population

c) System

d) Process

6. Which of the following is a quantitative variable?

a) the make of a washing machine

b) a person's gender

c) price of a car in thousands of dollars

d) whether a person is a college graduate or not

7. Pareto's principle is applied to a wide variety of behavior over many systems. It is sometimes referred to as the:

a) "20-80" Rule

b) "80-20" Rule

c) "10-90" Rule

d) "90-10" Rule

8. Which of the following is most likely a continuous numerical variable?

a) the number of gallons of paint purchased

b) the number of reams of paper ordered

c) the population of Egypt in 2005

d) the number of miles of interstate highways

9. A company has developed a new battery, but the average lifetime is unknown. In order to estimate this average, a sample of 110 batteries is tested and the average lifetime of this sample is found to be 200 hours. The 200 hours is the value of a:

a) parameter

b) statistic

c) sampling frame

d) population

Read the PROBLEM SOLVING Case “Wanted by Honda: Engineers Who Love Small-Town Living”

Although the U.S.-based Big Three automakers General Motors, Ford, and Chrysler have announced cutbacks and layoffs recently, some auto companies are still hiring. Toyota, Nissan, Honda, and other companies have set up opera- tions in the United States. While they employ far fewer in the United States than the Big Three, their ranks are growing. Nearly one out of four jobs with auto companies in the United States are with companies other than the Big Three. Honda R&D Americas recently told a reporter that it was adding about 100 employees a year and had 50 positions it was trying to fill with engineers.
To staff those positions, Honda faces a chal- lenge: its location. The Honda research and development facility is located in an out-of-the- way spot in Ohio, the town of Raymond, located about 60 miles northwest of Columbus. Most automotive research facilities in the United States are located near Detroit, because so much of the industry talent lives and works in that area. The Honda plant sits on an 8,000- acre plot of land along with the company’s Transportation Research Center, and Honda operates two assembly plants in nearby Marysville and East Liberty. Surrounding this complex are cornfields.
Because of its location, Honda does not seek most of its recruits from other auto companies. It hires local residents to fill manufacturing jobs, and for engineers, it turns to schools in the region to find recent graduates. Carol Hadden, who
manages human resources, says one good source of engineering recruits has been Ohio State University.
Knowing that small-town life does not appeal to many recent grads, Honda requires applicants to visit the Raymond site for their first interview. Allen explains, “We make them come here to make sure they know where we are.” Those who look around and like the location have a better chance of being enthusiastic about a career at Honda R&D.

Questions –

Suggest three ways Honda R&D Americas could recruit engineers to fill jobs at its research and development facility in Raymond, Ohio.

If you were interviewing a candidate for a job at this facility, what would you ask to determine whether the candidate would be satisfied to stay at Honda?

How would Honda R&D’s emphasis on recruiting recent graduates, rather than experienced automotive engineers, affect your job if you were the supervisor of these employees? Would you want Honda to change its recruiting strategy? Why or why not?

12. An agricultural research company has developed two new types of soy bean seeds, call them "seed A" and "seed B". A study is conducted to determine which will produce a higher mean yield. To test the two types of seed, 20 similar plots of land were randomly placed into one of two groups. One group of ten plots was planted with "seed A", while the other ten plots were planted with "seed B". The yield of each field, in bushels per acre, was recorded in the table below.

1. Conduct a hypothesis test at a 0.050.05 level of significance to determine if the two types of soy beans produce different mean yields.

The test statistic is ________________________
The p-value is____________________________

Construct a 9595% confidence interval for the mean of the differences. Hint: with the data in your lists, use the two-independent sample t-INTERVAL option on your calculator.
__________________to________________________

13. A company owns 9 trucks of various makes and models. The manager recently heard that inflating tires with nitrogen may provide slightly better gas mileage. The manager wants to determine if there is a noticeable increase in the mean gas mileage for the 9 trucks when nitrogen is utilized. Over a period of time, a test is run in which the gas mileage of each truck is recorded both with and without nitrogen in the tires. The gas mileages of the 15 trucks with and without nitrogen in the tires are recorded here. (data is in miles per gallon)

(b) The test statistic is_____________________

(c) The p-value is________________________

14. A professor of nursing wonders if the female nursing students are more likely to drop out of a nursing program than the male nursing students. To check her intuition, several nursing programs are compiled and random samples of both male and female nursing students are selected. Of the 200 male nursing students selected, 17 of them did not attain their nursing degree. Of the 700 female nursing students selected, 68 of them did not attain their nursing degree. Test the claim that the proportion of females not completing their degree is higher than the proportion of males using a level of significance of 0.05.
The test statistic is _________________
The p-value is ____________________

Consider Commerce Clause, Dormant Commerce Clause, Supremacy & Preemption legal theory Golden is a privately-owned company engaged in the business of disposing toxic waste generated by mining companies. Golden operates pursuant to a license issued by the state of Alpha. This license authorizes Golden to contract with miners to provide the following services: (i) collection of toxic waste at mine sites, and (ii) transportation of that waste to Golden's disposal station, which is in Alpha, three miles from the border with the state of Beta. In accordance with the authority granted by its license for the past 10 years Golden has contracted to provide services to miners in Alpha. Recently, Golden expanded its business to serve the miners in Beta and emerging battery businesses across the border in Beta. Shortly after Golden extended its services to the Beta miners and plants, the residents of the town from which the toxic waste disposal station operates started complaining about the rash of skin irritations, and increased illness. Prior to Golden's expansion of service to the State of Beta miners and the battery business, the U.S. Congress has passed legislation promulgating standards for safe disposal of toxic materials including batteries. The residents petitioned the State of Alpha to close Golden's disposal station. Golden objected. The Commissioner held open hearings. Following the hearings, the state issued an order that the use of Golden's disposal station would be limited to toxic waste from Alpha miners only. The Beta miners and battery businesses were barred from disposing of their toxic waste through Golden. Both Golden and the State of Beta have filed suit against State of Alpha seeking to rescind the order. Develop an IRAC for the constitutional legal issues. Use proper labels for all parts of IRAC ISSUE: Single sentence which links parties and legal issue through a triggering fact. RULE: Start with a General rule statement and expand outward to include elements of each rule. This may take several paragraphs to present a logical and clear progression of the rule. ANALYSIS: Present a fact summary which allows you to develop your analysis of how the rules and elements of law apply to the facts of this case. This is a logical process proceeding through rules and facts so that there is a thorough understanding of the application of law. Prior case law is cited and explained to support your analysis. CONCLUSION: A single sentence answering the question raised in the Issue Statement along with a because statement which provides a fact pivotal to the conclusion of legal application.

Use Workbench/Command Line to create the commands that will run the following queries/problem scenarios.

Use MySQL and the Colonial Adventure Tours database to complete the following exercises.

1. List the last name of each guide that does not live in Massachusetts (MA).

2. List the trip name of each trip that has the type Biking.

3. List the trip name of each trip that has the season Summer.

4. List the trip name of each trip that has the type Hiking and that has a distance longer than 10 miles.

5. List the customer number, customer last name, and customer first name of each customer that lives in New Jersey (NJ), New York (NY) or Pennsylvania (PA). Use the IN operator in your command.

6. Repeat Exercise 5 and sort the records by state in descending order and then by customer last name in ascending order.

7. How many trips are in the states of Maine (ME) or Massachusetts (MA)?

8. How many trips originate in each state?

9. How many reservations include a trip price that is greater than $20 but less than $75?

10. How many trips of each type are there?

11. Colonial Adventure Tours calculates the total price of a trip by adding the trip price plus other fees and multiplying the result by the number of persons included in the reservation. List the reservation ID, trip ID, customer number, and total price for all reservations where the number of persons is greater than four. Use the column name TOTAL_PRICE for the calculated field.

12. Find the name of each trip containing the word “Pond.”

13. List the guide’s last name and guide’s first name for all guides that were hired before June 10, 2013.

14. What is the average distance and the average maximum group size for each type of trip?

15. Display the different seasons in which trips are offered. List each season only once.

16. List the reservation IDs for reservations that are for a paddling trip. (Hint: Use a subquery.)

17. What is the longest distance for a biking trip?

18. For each trip in the RESERVATION table that has more than one reservation, group by trip ID and sum the trip price. (Hint: Use the COUNT function and a HAVING clause.)

19. How many current reservations does Colonial Adventure Tours have and what is the total number of persons for all reservations?

Jason Ackerman is the management accountant for Central Restaurant Supply ​(CRS. Beth Donaldson, the CRS sales​ manager, and Jason are meeting to discuss the profitability of one of the​ customers, Mama Leone's Leone's Pizza. Jason hands Beth the following analysis of Mama Leone's activity during the last​ quarter, taken from Central ​activity-based costing​ system:

Sales $23,400

Cost of goods sold (all variable) 14,025

Order processing (25 orders processed at $300 per order) 7,500

Delivery (2,500 miles driven at $0.75 per mile) 1,875

Rush orders (3 rush orders at $165 per rush order) 495

Sales calls (3 sales calls at $150 per call) 450

Operating income $ (945)

Beth looks at the report and​ remarks, "I'm glad to see all my hard work is paying off with Mama Leone's. Sales have gone up 10 % over the previous​ quarter!"

Jason ​replies, "Increased sales are​ great, but​ I'm worried about Mama Leone's ​margin, Beth. We were showing a profit with Mama Leone's at the lower sales​ level, but now​ we're showing a loss. Gross margin percentage this quarter was 40 %​, down five percentage points from the prior quarter.​ I'm afraid that corporate will push hard to drop them as a customer if things​ don't turn​ around."

​"That's crazy," Beth responds.​ "A lot of that overhead for things like order​ processing, deliveries, and sales calls would just be allocated to other customers if we dropped Mama Leone's. This report makes it look like​ we're losing money on Mama Leone's when​ we're not. In any​ case, I am sure you can do something to make its profitability look closer to what we think it is. No one doubts that Mama Leone's is a very good​ customer."

Requirements

Assume that Beth is partly correct in her assessment of the report. Upon further​ investigation, it is determined that 10 % of the order processing costs and 20 % of the delivery costs would not be avoidable if CRS were to drop Mama Leone's. Would CRS benefit from dropping Mama Leone's​? Show your calculations.

Beth​'s bonus is based on meeting sales targets. Based on the preceding information regarding gross margin​ percentage, what might Beth have done last quarter to meet her target and receive her​ bonus? How might CRS revise its bonus system to address​ this?

Should Jason rework the​ numbers? How should he respond to Beth​'s comments about making Mama Leone's look more​ profitable?

Using OLS estimation methodology, the study of Morelli and Smith (2015) uses a cross sectional data of 2490 cars for the year 2013 to estimate the factors affecting the price of automobiles in the state of California. The estimation results of regressing the price variable on a set of explanatory variables are shown in Model (1), where the numbers in parentheses are the robust standard errors of the coefficients.

????? = 5647.02 + 5.77 ????ℎ? + 23.64 ??? + 3573.09 ???????      (1)

              (1042.20)      (1.50)              (13.74)            (1230)

???_?^2= 0.65, ? = 2490

Where price is in U.S. dollars, weight is in pounds, mpg is the number of miles per gallon, and foreign is a dummy variable that takes 1 if the ith car is foreign and 0 if domestic.

1. Interpret the above results and discuss whether the signs and statistical significance of the coefficients are as expected.
2. What is the predicted price for a Buick Regal car that weights 3,450 lbs. and with 22 mpg? And what is the predicted price for a Toyota Corolla that weights 2,310 lbs.and with 18 mpg?
3. If in the year 2013 the actual price of Buick Regal was $25,500 and that of Toyota Corolla was $23,640, use the results of point (b) to determine whether your model over or under predicting the price of each car?
4. In one specification, the authors have included the length of the ith car, length, as an additional regressor to Model (1), where length is measured in inches. The resulting regression results are shown in Model (2) as follows,

              ????? = 5524.02 + 6.54 ????ℎ? + 22.73 ??? + 3568.11 ??????? − 93.48 ?????ℎ       (2)

   (1033.10) (4.85)               (13.68)             (1232)                      (32.87)

???_?^2 = 0.92, ? = 2490

If the F-statistic of the coefficients of the four included variables in Model (2) is equal to 54.32, does the inclusion of the variable length in Model (2) creates an econometric problem? Explain in details.

5. In one last specification of the model, the authors have included the size of the trunk of the ith car, trunk, as an additional regressor to Model (1), where trunk is measured in cubic feet. The resulting regression results are shown in Model (3) as follows,

               ????? = 5631.24 + 4.95 ????ℎ? + 25.99 ??? + 3650.22 ??????? + 88.31 ????? (3)

                         (1144.67)    (1.62)              (13.54)             (1285.29)                 (44.38)

???_?^2 = 0.75, ? = 2490

Suppose that the correlations between the variable trunk and the variables price, weight, mpg, and foreign are equal to 0.25, 0.49, -0.38, and -0.36, respectively. Based on these correlations, refer to Model (1) and discuss the direction of the bias of each coefficient of the three included variables. What is your opinion about including the variable trunk as an additional regressor in Model (3)? Does the inclusion of the variable trunk violate any of the OLS assumptions? Explain in details.

Matt’s Landscaping Pty Ltd is registered for GST purposes. It accounts for GST on the accruals basis and submits its Business Activity Statements monthly. Assume that all amounts in the question include GST when applicable.

The business operates from Brisbane’s north-side and its main business is to design and establish new gardens at shopping centres and office parks, and to provide ongoing garden maintenance services to clients.

During October 2018, Matt’s Landscaping Pty Ltd was involved in the following transactions:

* Designing and establishing a new garden at the refurbished Westfield shopping centre at North Lakes. The invoice issued on 25 October 2018 totalled $27,600.

* Ongoing garden maintenance services for clients. Invoices issued in October 2018 totalled $55,200.

* Matt’s Landscaping Pty Ltd prepared plans for the elaborate gardens of a new hotel being built in Dubai in the United Arab Emirates. The plans were sent to Dubai by airfreight on 1 October 2018. Matt’s Landscaping Pty Ltd issued an invoice for $17,500 on 15 October 2018.

* Purchases of plants, fertiliser and decorative stones from Brunnings Warehouse, one of Australia’s largest household hardware chains, totalled $9,900.

* The company purchased 100 square meters of Buffalo lawn from a retired school teacher who decided to dig up the lawn of his acreage in Caboolture to put down asphalt so that he no longer had to mow his lawn. The school teacher charged Matt’s Landscaping Pty Ltd $660 on 19 October 2018.

*The company purchased a second-hand lawnmower from a large supplier in Perth for $990 on 1 October 2018. The lawnmower was delivered a day later by a nationwide courier company that charged $110 for this service.

* Salaries and wages paid to staff in October 2018 totalled $12,000.

* Fuel costs for the company’s vehicles, lawnmowers and hedge trimmers totalled $1,980 during October 2018.

* The business operated from rented offices in North Lakes owned by a listed property group. Rent for October 2018 totalled $1,000.

* The October invoice that Matt’s Landscaping Pty Ltd received from the electricity and gas supplier for the rental property totalled $275.

* Purchases of milk, sugar, tea bags and coffee powder from a grocery store totalled $100 in October 2018. These were placed in a tea room in the rented offices for the exclusive use of staff.

* On 1 October 2018, Matt’s Landscaping Pty Ltd purchased a new one and a half tonne utility vehicle for $82,500.

* The company purchased specialised pruning shears from a company in France during October 2018. The shears cost $1,500 and international freight and insurance cost $100.

* Interest paid to the Commonwealth Bank of Australia in October 2018 on an overdraft facility totalled $660.

You are required to:

Calculate the GST payable or GST refundable for October 2018. Show all your calculations and provide reasons for your answers

REM (rapid eye movement) sleep is sleep during which most dreams occur. Each night a person has both REM and non-REM sleep. However, it is thought that children have more REM sleep than adults†. Assume that REM sleep time is normally distributed for both children and adults. A random sample of n1 = 10 children (9 years old) showed that they had an average REM sleep time of x1 = 2.6 hours per night. From previous studies, it is known that σ1 = 0.8 hour. Another random sample of n2 = 10 adults showed that they had an average REM sleep time of x2 = 1.80 hours per night. Previous studies show that σ2 = 0.7 hour. Do these data indicate that, on average, children tend to have more REM sleep than adults? Use a 1% level of significance.

(a) What is the level of significance?

State the null and alternate hypotheses.

H₀: μ₁ = μ₂; H₁: μ₁ > μ₂

H₀: μ₁ = μ₂; H₁: μ₁ < μ₂

H₀: μ₁ < μ₂; H₁: μ₁ = μ₂

H₀: μ₁ = μ₂; H₁: μ₁ ≠ μ₂

(b) What sampling distribution will you use? What assumptions are you making?

The Student's t. We assume that both population distributions are approximately normal with known standard deviations.

The standard normal. We assume that both population distributions are approximately normal with unknown standard deviations.

The Student's t. We assume that both population distributions are approximately normal with unknown standard deviations.

The standard normal. We assume that both population distributions are approximately normal with known standard deviations.

What is the value of the sample test statistic? (Test the difference μ₁ − μ₂. Round your answer to two decimal places.)

(c) Find (or estimate) the P-value. (Round your answer to four decimal places.)

(d) Based on your answers in parts (a) to (c), will you reject or fail to reject the null hypothesis? Are the data statistically significant at level α?

At the α = 0.01 level, we fail to reject the null hypothesis and conclude the data are not statistically significant.

At the α = 0.01 level, we reject the null hypothesis and conclude the data are not statistically significant.

At the α = 0.01 level, we reject the null hypothesis and conclude the data are statistically significant.

At the α = 0.01 level, we fail to reject the null hypothesis and conclude the data are statistically significant.

(e) Interpret your conclusion in the context of the application.

Fail to reject the null hypothesis, there is insufficient evidence that the mean REM sleep time for children is more than for adults.

Reject the null hypothesis, there is sufficient evidence that the mean REM sleep time for children is more than for adults.

Reject the null hypothesis, there is insufficient evidence that the mean REM sleep time for children is more than for adults.

Fail to reject the null hypothesis, there is sufficient evidence that the mean REM sleep time for children is more than for adults.

Have you ever wondered what it means to click the “offset carbon emissions” button when you book a flight or train trip? It adds a small cost to your ticket, but how does this reduce emissions? The money is typically used to fund projects that reduce carbon emissions. One such project type is the introduction of more efficient cooking stoves into communities. Much of the world uses inefficient charcoal or wood stoves that result in excessive indoor air pollution, deforestation, and carbon emissions. Switching millions of families to more efficient stoves can result in a significant reduction in carbon emissions. You may read more about such a project here. In order for a project to claim carbon credits, they must provide accurate estimates of how much carbon that project is saving. An important parameter for cook-stove projects is the reduction in fuel that results from switching to the more efficient stove. Statisticians are needed to design the experiments; it is expensive to do these tests, so figuring out how big the sample size should be in order to get sufficiently accurate estimates, or to detect significant differences between the stove types, is important. The EXCEL file, stove.xlsx, for this lab contains data from a pilot study using 19 randomly selected cooks. The numbers refer to the weight of firewood (in kg) to cook a regular meal. Each row in the spreadsheet corresponds to the same cook cooking the same meal. Use this data to answer the following questions. You may assume the conditions to carry out a hypothesis test are satisfied. You can assume (based on many similar studies) that the population standard deviation of reduction of firewood used is 0.7kg. Try to store as many decimal places as possible in intermediate steps. Old Stove Improved Stove 3.9 1.8 3.8 2.65 3.65 1.5 3.2 2.2 2.6 1.25 2.4 1.65 2.3 1.4 2.25 1.7 2.2 2.15 2.1 1.8 2 1.4 2 1.05 1.9 0.8 1.9 1.75 1.8 0.55 1.55 0.9 1.4 1.3 1.4 1.1 1.15 0.75 5. Find the 90% CI for the true mean reduction in firewood used. You may assume the population standard deviation of reduction in firewood used is 0.7. What is the margin of error (round to 4 decimal places)? 6. For a project to qualify for carbon credits, the required precision for estimates of the amount of wood saved per new stove adopted is 90/10, i.e. the 90% confidence interval must have a margin of error no greater than 10% of the value of the estimate. Will the data from the pilot study enable the project to qualify for carbon credits? 7. What is the minimum sample size required to meet the 90/10 precision requirement? 1 8. We want to know if the weight of wood used with the improved stove is significantly less than the weight of wood used with the old stove. State the null and alternative hypotheses for such a test.