26. Suppose that over the last 30 years, company ABC has averaged a return of 10%. Over the same period, the Treasury bond rate has averaged 3%. The current estimate of the Treasury bond rate is 5%. Using the historical approach, what is the estimate of ABC’s expected return.

A. 13.0% B. 12.5%

C. 12.0%

D. 11.0%

27. Standard deviation measures:

A. systematic risk.

B. unsystematic risk.

C. total risk.

D. beta risk.

28. Investors can eliminate what type of risk by diversifying?

A. systematic risk

B. unsystematic risk

C. beta risk

D. total risk

29. Which type of risk affects many different securities?

A. return risk

B. variance risk

C. unsystematic risk

D. systematic risk

An employee of a small software company in Minneapolis bikes to work during the summer months. He can travel to work using one of three routes and wonders whether the average commute times (in minutes) differ between the three routes. He obtains the following data after traveling each route for one week.

Route 1 34 35 29 36 29

Route 2 21 28 25 30 24

Route 3 22 27 25 30 26

a-1. Construct an ANOVA table.

a-2. At the 1% significance level, do the average commute times differ significantly between the three routes. Assume that commute times are normally distributed.

b. Use Tukey’s HSD method at the 1% significance level to determine which routes' average times differ.

Following is partial information for the income statement of Audio Solutions Company under three different inventory costing methods, assuming the use of a periodic inventory system:

Required:

1. Compute cost of goods sold under the FIFO, LIFO, and average cost inventory costing methods. (Round intermediate calculations to 2 decimal places. Round your answers to the nearest whole dollar amount.)

	FIFO	LIFO	AVF COST
BEGINING INVENTORY (395 UNITS @ $27)	$10665	$10665	$10665
PURCHASES (469UNITS @ $ 35)	16415	16415	16415

2. Prepare an income statement through pretax income for each method.

Sales, 328 units; unit sales price, $53; Expenses, $1,640

3. Rank the three methods in order of income taxes paid (favorable cash flow).

The Bensington Glass Company entered into a loan agreement with the​ firm's bank to finance the​ firm's working capital. The loan called for a floating rate that was 27 basis points ​(0.270.27 percent) over an index based on LIBOR. In​ addition, the loan adjusted weekly based on the closing value of the index for the previous week and had a maximum annual rate of 2.16 percent and a minimum of 1.71 percent. Calculate the rate of interest for weeks 2 through 9

Date	LIBOR
Week 1	1.92%
Week 2	1.69%
Week 3	1.49%
Week 4	1.31%
Week 5	1.57%
Week 6	1.67%
Week 7	1.71%
Week 8	1.87%
Week 9	1.87%

The rate of interest for week 2 is %.
​(Round to two decimal​ places.)

Miller Manufacturing builds and markets laptop computers for home and small business use. During the past five years, sales have been as low as 10,000 units in a year and as high as 15,000 units in a year. The company has been approached by an outside supplier offering to provide completed screens to the company for $65 each. The company’s marketing director negotiated the deal personally and is thrilled about how much cheaper it will be to purchase the screens from outside. Producing the cost data outlined below, the manager proudly proclaims, “Look, a $25 per unit savings!”

Per

[Based on 15,000 units year] Unit

Direct materials $40

Direct labor 10

Variable manufacturing overhead 3

Fixed manufacturing overhead, direct 10

Fixed manufacturing overhead, indirect 27

Total cost $90

Assume that Miller Manufacturing determines that sales in future years will be 15,000 units per year. IF the company decides to BUY the screens from the outside supplier, what will be the impact on annual company net income?

Company net income will INCREASE by $30,000 if the company decides to buy the screens from the outside supplier.

Company net income will DECREASE by $30,000 if the company decides to buy the screens from the outside supplier.

Company net income will INCREASE by $375,000 if the company decides to buy the screens from the outside supplier.

Company net income will DECREASE by $375,000 if the company decides to buy the screens from the outside supplier.

Company net income will INCREASE by $225,000 if the company decides to buy the screens from the outside supplier.

Company net income will DECREASE by $225,000 if the company decides to buy the screens from the outside supplier.

Miller Manufacturing builds and markets laptop computers for home and small business use. During the past five years, sales have been as low as 10,000 units in a year and as high as 15,000 units in a year. The company has been approached by an outside supplier offering to provide completed screens to the company for $65 each. The company’s marketing director negotiated the deal personally and is thrilled about how much cheaper it will be to purchase the screens from outside. Producing the cost data outlined below, the manager proudly proclaims, “Look, a $25 per unit savings!”

Per [Based on 15,000 units year] Unit

Direct materials $40

Direct labor 10

Variable manufacturing overhead 3

Fixed manufacturing overhead,direct 10

Fixed manufacturing overhead, indirect 27

Total cost $90

Assume that Miller Manufacturing determines that sales in future years will be 12,000 units per year. IF the company decides to BUY the screens from the outside supplier, what will be the impact on annual company net income?

Company net income will INCREASE by $300,000 if the company decides to buy the screens from the outside supplier.

Company net income will DECREASE by $30,000 if the company decides to buy the screens from the outside supplier.

Company net income will INCREASE by $30,000 if the company decides to buy the screens from the outside supplier.

Company net income will DECREASE by $6,000 if the company decides to buy the screens from the outside supplier.

Company net income will INCREASE by $6,000 if the company decides to buy the screens from the outside supplier.

Company net income will DECREASE by $300,000 if the company decides to buy the screens from the outside supplier.

CASE CHAPTER 15: QUANTITATIVE DATA ANALYSIS: HYPOTHESIS TESTINGPERCEPTIONS OF ORGANIZATIONAL ATTRACTIVENESSINTRODUCTION When Song Mei Hui moved from being Vice President for Human Resources at Pierce & Pierce in Shanghai to her international assignment in New York, she was struck by the difference in perception of Pierce & Pierce as an employer in China and the United States. Pierce & Pierce in China stands for an attractive and popular place to work, as opposed to its image as an employer in the United States, which was one of an unattractive, traditional, and uninspiring place of work. This difference in perception was bothering Song Mei Hui, because a strong and appealing ‘employer brand’ has the capacity to attract (and retain) talent as denoted by the number of university graduates aspiring to work for companies such as SAS, Google, Cisco, and the Boston Consulting Group.According to Song Mei Hui, the drivers of employer attractiveness have evolved into a complex and challenging set in this day and age. Even though she believes that the success of the organization itself is at the cornerstone of being an attractive employer (and Pierce & Pierce is flourishing indeed), she feels that a wide variety of factors contribute to being successful in attracting and retaining talent. “For many employees, being a part of a profitable, thriving corporation is a reward on its own,” she says. “However, this is obviously not enough. Opportunities for empowerment, a feeling of achievement, a substantial compensation package, and a culture of grooming and development also play a major role in the decision making process of today’s young professionals. Job candidates are looking for a career, and not just for a job.”Song Mei Hui has hired a graduate student in management, Timothy Brice, to develop and test a model of employer attraction. The results of Timothy’s study should help Pierce & Pierce to become more popular as an employer in the United States and hence to attract and retain talented young professionals. Timothy has conducted a literature review and in-depth interviews with graduate students and young professionals who have just started their careers in order to establish the drivers of employer attractiveness. Based on the results of the literature review and the qualitative study, he has developed the following model. CONCEPTUAL MODEL AND HYPOTHESESFigure 1: A conceptual model of employer attraction EMPLOYER BRAND IMAGE From this model, Timothy has derived the following hypotheses. The effect of Brand Image on Employer attraction Employer brand image can be defined as the potential applicants’ perceptions of instrumental and symbolic attributes of an organization (cf. Backhaus and Tikoo, 2004; Lievens and Highhouse, 2003; Lievens, 2007; Martin, Beaumont, Doig and Pate, 2005). The instrumental dimension includes tangible attributes related to the job and/or the organization such as ‘job opportunities’, whereas the symbolic dimension includes (the perception of) intangible attributes of an employer (as if it were a person) such as ‘sincerity’ and ‘being exciting’. Both instrumental and symbolic attributes have been found to affect applicant attraction to an employer (Backhaus and Tikoo, 2004; Cable and Turban, 2001; Turban and Greening, 1997). Therefore, the following hypotheses are proposed:H1a: The more positive the perception of instrumental attributes of an employer, the stronger applicant attraction to the organization. H1b: The more positive the perception of symbolic attributes of an employer, the stronger applicant attraction to the organization. Feelings of significant others.If significant others in someone‘s surrounding (e.g., family and friends) tell this person that a company is a much better employer than other employers, someone’s level of attraction to Instrumental attributes:-Workplace atmosphere-Job opportunities-Industry characteristicsEmployer attractionSymbolic attributes:-Excitement-Sincerity-PrestigeSubjective normsCONCEPTUAL MODEL AND HYPOTHESESFigure 1: A conceptual model of employer attraction EMPLOYER BRAND IMAGE From this model, Timothy has derived the following hypotheses. The effect of Brand Image on Employer attraction Employer brand image can be defined as the potential applicants’ perceptions of instrumental and symbolic attributes of an organization (cf. Backhaus and Tikoo, 2004; Lievens and Highhouse, 2003; Lievens, 2007; Martin, Beaumont, Doig and Pate, 2005). The instrumental dimension includes tangible attributes related to the job and/or the organization such as ‘job opportunities’, whereas the symbolic dimension includes (the perception of) intangible attributes of an employer (as if it were a person) such as ‘sincerity’ and ‘being exciting’. Both instrumental and symbolic attributes have been found to affect applicant attraction to an employer (Backhaus and Tikoo, 2004; Cable and Turban, 2001; Turban and Greening, 1997). Therefore, the following hypotheses are proposed:H1a: The more positive the perception of instrumental attributes of an employer, the stronger applicant attraction to the organization. H1b: The more positive the perception of symbolic attributes of an employer, the stronger applicant attraction to the organization. Feelings of significant others.If significant others in someone‘s surrounding (e.g., family and friends) tell this person that a company is a much better employer than other employers, someone’s level of attraction to Instrumental attributes:-Workplace atmosphere-Job opportunities-Industry characteristicsEmployer attractionSymbolic attributes:-Excitement-Sincerity-PrestigeSubjective norms that particular organization will grow. It is generally recognized that potential applicants often consult other people (e.g., family, friends, and/or acquaintances) about jobs and organizations(e.g., Van Hoye and Lievens, 2007)”. What’s more, Turban (2001) found that university personnel’s beliefs about organizations affect students’ attraction to that organization. Kilduff (1990) also found that in the early stages of job search, college students are heavily influenced by the beliefs of their friends and classmates. These findings all point at the relevance of social influences to potential applicants in influencing the level of employer attraction. Hence, the following hypothesis is proposed: H2: The more positive significant others are about an organization, the stronger applicant attraction to the organization. To test these hypotheses, Timothy has undertaken a quantitative field study. He has collected data using a questionnaire measuring the variables in his model and a couple of respondent characteristics such as age, gender, and level of education with closed-ended questions. The results of this study are provided next. RESULTSTable 1 provides the means and standard deviations of the variables of interest to this studyand the results of a multiple regression analysis that was conducted to test the hypotheses of this study. Table 1 Summary statistics and results of the regression analysis Adjusted R2dfFMSDBSEtpRegression.3657, 897.304-----.000aConstant--2.213.5224.238.000Instrumental attributesWorkplace atmosphere4.32.75.088.152.577.565Job opportunities4.73.75.390.1362.868.005Industry characteristics4.24.74.275.1861.473.144Symbolic attributesExcitement3.78.91.071.149.474.637Sincerity5.13.80.109.137.794.429Prestige4.05.81.146.1151.268.208Subjective norm4.981.13.317.1003.169.002 Employer attraction3.711.23----Note. df = degrees of freedom; F = F-statistic; M = Mean; SD = Standard deviation; B = Unstandardized beta coefficient; SE = standard error; t = t-statistic; p = significance level; Scale 1-7 a. Predictors: (Constant), Workplace atmosphere, Job opportunities, Industry characteristics, Excitement, Sincerity, Prestige, Subjective norm.b. Dependent Variable: Employer Attraction.N= 197 (88 men and 109 women). QUESTIONS1. a. Discuss the following statement: “One of the most important issues in regression analysis concerns model specification (the determination of which independent variables should be included in or excluded from a regression equation).” b. Do you like Timothy’s model? Is it, for example, in line with Song Mei Hui’s ideas? 2. What’s the difference between simple regression analysis and multiple regression analysis?3. Why can’t Timothy run a series of simple regressions (for instance three or seven) to test the hypotheses of his study? 4. Provide the equation of Timothy’s model. 5. Interpret the results of the regression analysis. Discuss: a. the model fit; b. the significance of the model; c. the constant; d. the statistical validity of the beta coefficients; e. the face validity of the results.6. A common problem encountered in regression analysis is multicollinearity. a. What is multicollinearity and how does it affect the estimates of the regression coefficients?b. Describe two ways to test for multicollinearity. Which one do you prefer?c. Suppose that multicollinearity is a problem in this study. What can Timothy do about it? d. Do you expect that multicollinearity is a problem in this study? Explain.7. Timothy suggests that Pierce & Pierce should create more exciting jobs to attract more employees since the mean of the independent variable “excitement” is relatively low. Do you agree?8. What managerial conclusions can you draw based on the results of the regression analysis? 9. Song Mei Hui believes that the gender of potential employees may affect the original relationship between prestige and employer attraction. She asks Timothy to test this idea.a. How can Timothy test this idea? b. Provide a new equation of the model: include Song’s ideas about the moderating effect of gender on the relationship between prestige and employer attraction.10. Discuss the following statement: “Regression analysis does not address the issue of causality.”

Questins!!!!

Risks: Describe the risks that Koala Fun faced as a company.

Management: In what ways was Koala Fun not being managed to obtain optimum performance from its assets?

Explain. Decisions: How does this case demonstrate the importance of analyzing financial data when making financial decisions?

Recommendations: What recommendations regarding risk and profitability would you make to Koala Fun’s owners to improve their company? Briefly describe your recommendations.

Ratio Type	2012	2013
Current (times)	(2,136,800/573,200) = 3.73	(2,619,700/764,100) = 3.43
Quick (times)	[(2,136,800-765,400)/573,200] = 2.39	[(2,619,700-1,222,300)/764,100} = 1.83
Debt (%)	[(316,000+573,200)/2,361,100] = 37.66%	[(764,100+252,800)/2,879,500] = 35.32%
Times interest earned (times)	(322,400/37,900) = 8.51	(367,100/31,600) = 11.62
Inventory turnover (times)	(4,896,700/765,400) = 6.40	(5,866,200/1,222,300) = 4.80
Total asset turnover (times)	(6,572,800/2,361,100) = 2.78	(7,811,500/2,879,500) = 2.71
Average collections period (days)	[365/(6,572,800/1,004,200)] = 55 days	[365/(7,811,500/1,106,600)] = 51 days
Return on equity (%)	[170,700/(948,000+524,000)] = 11.60%	[201,300/(1,137,600+725,000)] = 10.81%

FINANCIAL CONCERNS Owen and Tessa loved their company but were inexperienced in business matters. Owen asked his mother, Amy, an accountant, for assistance. After studying the ledgers and other records, she reported that there was a signifi- cant working capital problem with declining cash, unsold inventory (mostly old Koala Fun games), and vendors who had not been paid. Tessa had been handling this side of the company, but that had mostly involved writing checks to employees and for payables while waiting around airports. Files were misplaced, documents were missing, and some money was unaccounted for. The problems appeared to be more related to failing to priori- tize financial matters rather than any deliberate mistakes. Owen’s first reaction was to consider the sale of his half interest in KF. Though he has enjoyed the creative side of the business, he was upset by his mother’s report and by Tessa’s apparent failure to take care of that responsibil- ity. Periodically, some of the resellers KF deals with have encountered finan- cial problems and have strung out their payments, which often caused a mad scramble for cash at KF. And if Owen decides to sell, he knows that he is likely provide it.” Owen is skeptical of this argument and wonders if there isn’t a more efficient way of providing good service. He also questions Tessa’s credit standards and collection procedures, and believes that Tessa has been quite generous in granting payment extensions to customers. At one point, nearly 45 percent of the company’s receivables were more than 90 days overdue. Furthermore, Tessa would continue to accept and ship orders to these resellers even when it was clear that their ability to pay was marginal. Tessa’s position is that she doesn’t want to lose sales and that the difficult times are only temporary. Owen wonders about the wisdom of passing up trade discounts. Vendors frequently offer KF terms of 11?2/10, net 30. That is, KF receives a 11?2 percent discount if a bill is paid in 10 days and in any event full payment is expected within 30 days. Tessa rarely takes these discounts because she “wants to hold onto our cash as long as possible.” She also notes that “the discount isn’t espe- cially generous and 981?2 percent of the bill must still be paid.” FINAL THOUGHTS Despite all of Owen’s concerns, however, the relationship between the two partners has been relatively smooth over the years. And he admits that he may be unduly critical of Tessa’s management decisions. “After all,” he concedes, “she seems to have reasons for what she does, and we have never lost money since we started, which is an impressive record, really, for a firm in our business.” Owen has discussed with two advisors the possibility of selling his half of the firm. Since KF is not publicly traded, the market value of the company’s stock must be estimated. The consultants believe that KF is worth between $35 and $40 per share, figures that appear reasonable to Owen.

Data Mining - Milestone One

Page length requirements: One Paragraph

Question: Based on the scenerio below: What is the purpose of the analytic method/approach/strategy you are using? What typeof information does it yield?

The scenario: Bubba Gump Shrimp Company is a successful retailer of regional food, both in its restaurants and through other retail channels. Bubba Gump began as a small, privately owned restaurant. Thanks to unexpected exposure from a blockbuster movie, Bubba Gump grew rapidly from its humble beginnings and now operates several restaurants, sells branded merchandise through an online retail site, and wholesales its branded merchandise to other retail outlets. Bubba Gump's growth was initially very rapid in response to a strong demand and high name recognition that followed from its movie exposure. After its first few years of rapid growth, sales increased at slower rates and finally leveled off. Sales have declined in each of the last two years. Bubba Gump Shrimp Company has collected a large amount of data about its business, including restaurant point-of-sale (POS) data, web channel sales performance, customer information through restaurant loyalty programs, and customer and sales transaction data through its website and retail partners. Bubba Gump's leadership has decided to commission an analysis of the company's vast data assets to better understand its customers and look for ways to create new revenue growth. You have been assigned to plan, conduct, and report on this data mining initiative for Bubba Gump Shrimp Company. The company data that is available to you includes Bubba Gump's restaurant point-of-sale (cash register, credit card) data, its customer database (collected from its restaurant loyalty program and online sales channel), its web store sales transaction data, and customer and sales data from third-party retailers. All of Bubba Gump's data has recently been integrated in a data warehouse. That enterprise data warehouse was built specifically to support data mining initiatives like the one you have been assigned to conduct, by consolidating data from multiple operations and channels in one place and integrating the data across sources for a complete view of the customer experience. For the first time, Bubba Gump analysts can link sales transactions to specific customers at specific restaurants, for example. It also means that you can link customer transactions across channels; that is, for any given customer, you can link to both their restaurant purchases, their online purchases, and (in some cases) their purchases from third-party retail partners. You have been selected to develop and execute the data mining analysis plan for Bubba Gump's customer analysis project. Your project will be the first major data mining project conducted against the new Bubba Gump data warehouse. Because Bubba Gump's data was not previously integrated in a single data warehouse, company leadership has never been able to analyze its customers across their complete experience. In other words, customer restaurant purchases, online purchases, and third-party retailer purchases could not be analyzed together previously; each channel had to be analyzed separately. As a first step, a sample of 500 customers has been selected from the analytics data warehouse and given a survey in exchange for purchase credits at one of Bubba Gump's sales channels. The survey sample was selected from the universe of customers who have made purchases from at least one Bubba Gump outlet (restaurant, web store, etc.). Responses to various customer satisfaction questions were recorded, and historical purchase information has been extracted from the data warehouse for each customer in the sample.

Consider the database of a car rental company that contains three tables drivers, cars and reservation tables.

Drivers:                                           Reservation:                              Cars:

Dno	Dname	age		Dno	Cno	Day		Cno	Cmake	Color
22	Dustin	45		22	101	10/10		101	BMW	Blue
29	Brutus	33		22	102	10/10		102	VW	Red
31	Lubber	55		22	103	10/8		103	OPEL	Green
32	Andy	25		22	104	10/7		104	FIAT	Red
58	Rusty	35		31	102	11/10
64	Horatio	35		31	103	11/6
71	Zorba	16		31	104	11/12
74	Horatio	35		64	101	9/5
85	Art	25		64	102	9/8
95	Bob	63		74	103	9/8
23	Alice	15		23	104	9/11

1. Write DDL statements to create the tables

Drivers(Dno, Dname, age)

Reservation(Dno, Cno, Day)

Cars(Cno, Cmake, Color)

Where:

• no field could be empty except the age of the Driver.
• The company does not own more than one car from one maker     
• the colors of the cars should not be other than the following group (blue, white, red , green)

2. Write Queries for the following:
   1. Insert the sample data shown above into the tables

3. Write Queries for the following:
   1. Find the names of drivers who have reserved car no 103.
   2. Find the names of Drivers who have reserved red or Green cars.( use IN, UNION, =SOME/=ALL, and JION    each in separate query)For this segment, 4 responses are required, using the operations shown in parentheses
   3. Find the driver Dno of drivers with age over 20 who have not reserved a read car.
   4. Find the names of drivers who have reserved all cars.
   5. List the name of the drivers along with the day they rent cars in descending order
   6. List the name of the drivers whom rent more than 3 times along with the number of the times.
   7. Change the age of Alice to 18 years old
   8. Delete the information of the drivers younger than 20 years old