Boatbound

Serial entrepreneur Aaron Hall took note of the “sharing economy” that emerged during the last recession and launched Boatbound, a peer-to-peer boat rental company that brings together boat owners who are willing to rent their boats when they are not in use and people who want a fun boating experience without the cost of owning a boat. Hall realized that 12.2 million boats are registered in the United States, yet the average owner uses his or her boat just 26 days per year. Boatbound screens all potential renters, verifies the condition and the safety of each boat, carries ample insurance on each boat, and covers general liability. Boat owners select their renters from Boatbound’s pool of applicants and set daily rental fees, and Boatbound collects 35 percent of the fee. Boatbound has rented every kind of boat, from kayaks to yachts with captains. Fees range from $200 to $8,500 per day. “As a boat owner and someone in the marine industry, I’ve been waiting for something like this my whole life,” says Aabad Melwani, owner of a marina. “I just didn’t know it.”

Henrybuilt

Scott Hudson, CEO of Henrybuilt, had created a profitable niche designing and building upscale kitchens that ranged from $30,000 to $100,000. In 2006, Hudson opened a New York City showroom, which doubled in size in just 18 months. By 2008, the company had more than 200 jobs in the United States, Mexico, and Canada. When the recession hit, however, new projects came to a standstill, and customers began cancelling orders. In response, Hudson launched a subsidiary, Viola Park Corporation, that provides customers lower-cost remodeling options that use its software rather than an architect to create “custom” variations on Henrybuilt designs. The result is a process that produces a kitchen much faster and at half the cost of a Henrybuilt kitchen. Henrybuilt sales have recovered, but Viola Park accounts for 20 percent of sales and is growing twice as fast as Henrybuilt. Unequal Technologies Robert Vito started Unequal Technologies in 2008 to supply protective clothing and gear, including bullet-proof vests, to military contractors. The protective gear is made from a lightweight yet strong composite material that he developed and patented. Two years later, the equipment manager of the Philadelphia Eagles called to ask whether Unequal Technologies could create a special garment for one of its star players who had suffered a sternum injury. Vito modified the bullet-proof vest for the player and soon had other players in the National Football League asking for protective gear. Unequal technologies went on to develop Concussion Reduction Technology (CRT), peel-and-stick pads for football helmets that are made from before it reaches the skull. Independent tests show that CRT reduces the risk of head injuries from impact by 53 percent. The company now supplies equipment to 27 of the NFL’s 32 teams and has its sights set on an even larger market: amateur sports. Vito says Unequal’s technology gives the company a competitive edge that has allowed it to increase sales from $1 million to $20 million in just one year.

(Source: Scarborough and Cornwall, 2016)

1. Select one of these small businesses (Boatbound or Henrybuilt) and explain how the said business used six (6) of the 10 types of innovation to bolster its success.   

15. Marks)

When you determine if there is an association between two variables, it is also important for you to determine how strong or weak that association is. This is why, when you have data for two quantitative variables, you calculate what is called the coefficient for correlation.

Instructions

1. Suppose you are determining the association between the weight of a car and the miles per gallon that the car gets. Answer the following questions in a Word document:

• define correlation and explain how you can use correlation to determine the relationship between these two variables.
• Before you look at some data, what kind of association do you think will exist between the weight of a car and the miles per gallon that the car gets? Will it be positive or negative?
• Given the data below, use Excel or other technology to calculate the correlation coefficient for this data:

Model

City MPG

Weight

Mazda MX-5 Miata

25

2365

Mercedes/Benz SLK

22

3020

Mitsubishi Eclipse

23

3235

Pontiac Firebird

18

3545

Porsche Boxster

19

2905

Saturn SC

27

2420

• Now that you have calculated the correlation, what does this value represent? What does it tell you about the relationship between these two variables?

*** PLEASE ANSWER ALL QUESTIONS IN PARAGRAPH FORMAT.

The following case study provides information for a hotel chain. They have recently conducted a customer satisfaction survey. Given these research results and the other information in the case, what advice would you give them? This is a good exercise in utilizing the results of market research.

ACTIVITY/TASK

The Quick-Stop Hotel Chain

Quick-Stop Hotels is a small hotel chain located along on the north coast of New South Wales. This chain consists of five different hotel complexes located several hours drive apart along the main coastal highway between Sydney and Brisbane.

Their prime target market is the family segment. This is because families often choose to drive from Sydney to Brisbane (or Brisbane to Sydney) and back again for their holidays. As this trip is around a 12-hour drive, many travelers choose to stop overnight in order break up their journey. Therefore, Quick-Stop has deliberately chosen popular stopover towns for their hotels.

In line with this location strategy, they promote themselves with the slogan, “the “perfect place for a break”.

Their individual hotels vary a little in quality, but all have either a 3 or a 4 star rating. This means that they are either medium (3 star) or good (4 star) quality in terms of facilities and general standard of accommodation. On average, they each have around 80 rooms and a fairly broad range of facilities (that is, a heated swimming pool, room service, restaurant and bar, a kid’s club during school holidays, a small gym, and some have tennis courts and a couple of stores).

In terms of promotion, they are heavy outdoor (billboard) advertisers on the coastal highway. They also advertise in various holiday and travel directories, and on the government tourism website.

As you can see from the table below, they vary pricing throughout the year. Pricing is generally used as a tool to increase demand in the low season and to increase revenue in the high season. This is necessary as they have highly seasonal demand, being frequently being booked out over the Christmas holiday period, and with very high demand in other school holiday periods.

The table also shows the results of a customer satisfaction survey for Quick-Stop Hotels. On average, 80% of customers indicated that they were satisfied with their stay and 10% were delighted with their stay. However, 10% indicated they were dissatisfied. These figures vary by season, whether the customer was a first-time customer, and by the quality of the individual hotel. Additionally, the table includes information on average room rates (per night) and occupancy levels. (Note: The occupancy level is the percentage of rooms occupied per night.)

QUESTIONS

1. Review the customer satisfaction information. Does it make sense? Why/why not?
2. Given these research results and the other information in the case, what advice would you give this firm.
3. Which of the above metrics did you find helpful? Which did you ignore?
4. What other information would have been helpful?

1. Generate a hypothesis about the difference between two groups in a dataset.
   • State null hypothesis and alternative hypothesis as an explanation and math equation.
2. Identify the appropriate statistical test of the difference between two groups in a dataset.
   • Provide your statistical rationale.
3. Perform appropriate statistical test of the difference between two groups in a dataset.
4. Interpret statistical results of a data analysis and state whether to accept or reject the null hypothesis based on the p-value and an alpha of .05.
   • Interpret p-value and statistical significance.
5. Summarize practical, administration-related implications of the hypothesis test.

Dataset:                      

1. Generate a hypothesis about the difference between two groups in a dataset.
   • State null hypothesis and alternative hypothesis as an explanation and math equation.
2. Identify the appropriate statistical test of the difference between two groups in a dataset.
   • Provide your statistical rationale.
3. Perform appropriate statistical test of the difference between two groups in a dataset.
4. Interpret statistical results of a data analysis and state whether to accept or reject the null hypothesis based on the p-value and an alpha of .05.
   • Interpret p-value and statistical significance.
5. Summarize practical, administration-related implications of the hypothesis test.

Dataset:                      

SPRING TRAINING INC.  

Balance Sheet                            

December 31, 2017

ASSETS                                                         LIABILITIES

Cash                              $25,000             Accounts Payable                 $50,000

Accounts Rec.                   5,000             Mortgage Payable                 50,000

Inventory                        14,000              

Supplies                            2,000             Total Liabilities                                  $100,000

Land                                18,000

Buildings      $220,000                             STOCKHOLDER EQUITY

    Acc. Depr. <20,000> 200,000          

Equipment     200,000                             Common Stock $5 Par      $30,000

    Acc. Depr <14,000> 186,000             Excess of Par                     $300,000

                                                                  Retained Earnings               20,000

      Total Equity                                     $350,000

TOTAL ASSETS        $450,000              TOTAL LIAB. & EQUITY         $450,000

Jan. 2]     Sold 200,000 shares of common stock for $2,600,000.

Jan. 3]    Purchased on account $40,000 of inventory for resale to customers. Terms

              were 5/60 net 90.

Jan. 10] Paid $5,000 for promotion & marketing expenses. Promotion would run

   through the month of January 2018.

Jan. 15] Purchased a 3-year insurance policy for $3,600 in cash. Effective date is

   January 1, 2018 to December 31, 2020.

Jan. 27]   Paid in full for purchases acquired January 3, 2018.

Feb. 1]    Paid $3,000 as a mortgage payment. The balance on the mortgage is listed

    on the balance sheet dated December 31, 2017. Interest Rate is 8 per cent.

Feb. 10] Sales revenue generated was $400,000. $10,000 in cash received this date

    the balance on account. Terms 4/60 net 60 days.

Feb. 27]   Paid wages for the months of January and February 2018. Total wages

     that was paid for the two months was $40,000.

Mar. 1]   Acquired $200,000 of equipment. Useful life is 10 years. Signed a note

    (12%) for entire amount.

Mar. 1]    Declared a dividend of 50 cents per share.

Mar. 1]    Customer returned $25,000 of items acquired on February 10, 2018.

Mar. 1]    Signed a lease for warehouse space rental period is from April 1, 2018 to

                 December 31, 2018. A $10,000 deposit was paid on March 1.

Mar. 1]    Borrowed $80,000, and signed a note for this amount at 10%.

Mar. 3]    Paid the February Mortgage payment only this time $7,000 was paid.

Mar. 6]   Sales on account to customers amounted to $200,000. Terms are 10/60 net

     90 days.

Mar. 15]   Received full amount due from the February 10 sale.

Mar. 15]   Customer returned items that were sold for $35,000 on March 6, 2018.

Mar. 17]   Purchased $40,000 of inventory and terms were 8/30 net 90. This was a

      cash purchase.

Mar. 30]   Supplies were now determined to be $500.

Mar. 31]   Customer paid in full for the March 6 sale.

Mar. 31]   Spring Training paid $20,000 in wages for the month of March.

Mar. 31]   Paid $30,000 on the equipment note entered on March 1, 2018.

OTHER INFORMATION

1. Tax rate is 20%.

2. All equipment has a useful life of ten years.

4. Building has useful life of 20 years.

5. Ending Inventory for Spring Training Inc. is $20,000.

Rquirement:

PREPARE A SET OF FINANCIAL STATEMENTS FOR THE QUARTER ENDING MARCH 31, 2018

Please prepare for T accounts, Journal Entry, Income statement, Balance sheet and statement of Retained Earnings

My Research Methods class (N = 14) was interested in whether studying alone or in groups would result in better grades on their third assignment. Half of the class (n = 7) studied for the assignment alone, while the other half (n = 7) studied as a group. Their grades are summarized in the below tables:

1. What are the upper and lower boundaries of the range of differences between two μs that you can say with 95% confidence contains the difference represented by the above sample?

2. Using Cohen’s d, calculate the effect size of studying alone vs. in a group on the grade obtained. What is the strength of this relationship and why?

What kind of quantity is length?
ratio
ordinal
interval
nominal

What type of graph is best for expressing percentages of a whole?

We are selecting seven CD's out of twelve to take the mountains. How many possible selections are there, given that order doesn't matter?

Karen scored a 76 on an exam whose mean is 74 and whose standard deviation is 8. Find her z score.

At a college, 60% of the students are women. If we select 7 students at random, what is the probability that exactly 5 of tyen are women (to the nearest hundredth)?

The heights of students or normally distributed with a mean of 59" and a standard deviation of 5" what is the probability that a randomly selected student will be between 57 and 65" tall?

We are to select a president vice president secretary and treasurer out of a club with 15 members assuming that no one can hold more than 1 office how many selections are possible?

3. Below are data for n = 20 individuals indicating the resting pulse rate of each person, and whether or not that person regularly exercises.

Exercise and pulse rate data

1. Assuming this is a random sample from a larger population, carry out a hypothesis test to determine whether the mean pulse rate differs between those who do regularly exercise and those who don't regularly exercise.  Use alpha = .05, and show all four steps.