The data below is the mileage (thousands of miles) and age of your cars .

Year Miles Age

2017    8.5    1

2009 100.3    9

2014   32.7    4

2004 125.0   14

2003 115.0   15

2011   85.5    7

2012   23.1    6

2012   45.0    6

2004 123.0   14

2013   51.2    5

2013 116.0    5

2009 110.0    9

2003 143.0   15

2017   12.0    1

2005 180.0   13

2008 270.0   10

Please include appropriate Minitab Results when important

a. Identify terms in the simple linear regression population model in this context.

b. Obtain a scatter diagram for the sample data. Interpret the scatter diagram.

c. Obtain a scatter diagram with the least squares regression line included. Interpret the intercept and slope in the context of this problem.

d. In theory what ought to be the value of the population model intercept? Explain.

e. What is the informal prediction for what the mileage should be on your car? What is the error in the prediction of the mileage for your car?

f .Use some statistical reasoning to assess whether or not the prediction for the mileage on your car was “accurate”?

g. How would you respond if someone asks “about” how many miles do students drive per year?

Exercise 11-12

In 1993, Nash Company completed the construction of a building at a cost of $2,040,000 and first occupied it in January 1994. It was estimated that the building will have a useful life of 40 years and a salvage value of $59,200 at the end of that time.

Early in 2004, an addition to the building was constructed at a cost of $510,000. At that time, it was estimated that the remaining life of the building would be, as originally estimated, an additional 30 years, and that the addition would have a life of 30 years and a salvage value of $20,400.

In 2022, it is determined that the probable life of the building and addition will extend to the end of 2053, or 20 years beyond the original estimate.

A.) Using the straight-line method, compute the annual depreciation that would have been charged from 1994 through 2003.(Per year)

B.) Compute the annual depreciation that would have been charged from 2004 through 2022. (Per year)

C.) Prepare the entry, if necessary, to adjust the account balances because of the revision of the estimated life in 2021. (If no entry is required, select "No entry" for the account titles and enter 0 for the amounts. Credit account titles are automatically indented when amount is entered. Do not indent manually.)

D.) Compute the annual depreciation to be charged, beginning with 2022. (Round answer to 0 decimal places, e.g. 45,892.)

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Question 1 of 29 Total

A firm’s corporate strategy is driven largely by its top management team. One method of gauging the influence of marketing on corporate strategy is to measure the proportion of firms with a chief marketing officer on their top management team. Over the 5-year period from 2000 to 2004, 42% of firms had a chief marketing officer on their top management team. [Source: Pravin Nath and Vijay Mahajan, “Chief Marketing Officers: A Study of Their Presence in Firms’ Top Management Teams,” Journal of Marketing, 70 (2007).] To test the hypothesis that the influence of marketing on corporate strategy today is different from its influence in the 2000–2004 period, a random sample of 91 U.S. firms is selected. Of these, 26 firms have a chief marketing officer on their top management team. The test is conducted at a significance level of α = 0.01. Let p be the true proportion of firms with a chief marketing officer currently on their top management team.

To conduct the hypothesis test, the null and alternative hypotheses are formulated as: A. H₀: p ≥ 0.42; Ha: p < 0.42 B. H₀: p̄ = 0.42'; Ha: p̄ ≠ 0.42 C. H₀: p = 0.42; Ha: p ≠ 0.42 D. H₀: p ≤ 0.42; Ha: p > 0.42 If the null hypothesis is true, the sampling distribution of the sample proportion p̄ can be approximated by ____ with a mean of ____ and a standard deviation of ___ . The test statistic is ____. Use the Distributions tool to develop the rejection region. According to the critical value approach (with α = 0.01), when do you reject the null hypothesis? Reject H₀ if t ≤ –2.632 or if t ≥ 2.632 Reject H₀ if z ≤ –2.576 Reject H₀ if z ≤ –2.576 or if z ≥ 2.576 Reject H₀ if z ≤ –2.326 or if z ≥ 2.326 Use the provided Distributions tool to determine the p-value. The p-value is ____. Using the critical value approach, the null hypothesis is (not rejected/rejected), because ___. Using the p value approach, the null hypothesis is (not rejected/rejected), because ____. Therefor you (can/cannot) conclude that the influence of marketing on corporate strategy today is different from its influence in the 2000–2004 period.

Lainney Inc decides to offer its consulting services valued at $125,000 to Ari Inc. Ari pays $16,000 down and Lainney agrees to accept a three-year instalment note for the balance owing. Notes of similar risk charge interest at 11.51% The instalment note requires Ari to make three annual equal payments of $45,000. Each payment pays down part of the note’s principal and interest due to Lainney. Required: i. Prepare the entry on Lainney’s books to record the issuance of the note receivable ii. Using the effective interest method, set up an amortization table with the following headings to show the amount of interest revenue booked each period and the carrying value of the note receivable at the end of each period for Lainney. Period Cash Received Interest Revenue Payment on the Note Receivable Carrying value – Note receivable iii) Prepare the journal entry to record cash received, interest revenue and note repayments for each year. iv) Prepare a partial statement of financial position for Lainney at the end of Year 1 to show how the note would be presented. v) From Lainney’s perspective, what are the advantages of an installment note compared with a non-interest bearing long term note? Be specific. Do not use point form. Use proper sentence structure

Compute and Interpret Liquidity, Solvency and Coverage Ratios
Selected balance sheet and income statement information from Verizon Communications follows.

(a) Compute the current ratio for each year and discuss any trend in liquidity. (Round your answers to two decimal places.)
2005 current ratio = Answer

2004 current ratio = Answer

What additional information about the numbers used to compute this ratio might be useful in helping you assess liquidity? (Select all that apply)
Answeryesno The maturity schedule of current liabilities
Answeryesno The average stock price for the industry
Answeryesno The average current ratio for the industry
Answeryesno The amount of current assets that is concentrated in relatively illiquid inventories

(b) Compute times interest earned, total liabilities-to-equity, and net cash from operating activities to total debt ratios for each year. (Round your answers to two decimal places.)
2005 times interest earned = Answer
2004 times interest earned = Answer

2005 total liabilities-to-equity = Answer
2004 total liabilities-to-equity = Answer

2005 net operating cash flow to total debt = Answer
2004 net operating cash flow to total debt = Answer

Which of the following best describes the extent of Verizon's financial leverage and the company's ability to meet interest obligations?

Verizon's times interest earned ratio has decreased, total liabilities-to-equity has increased, and net operating cash flow to total debt ratio has remained the same, which suggests the company will meet its obligations.

Verizon's times interest earned ratio has increased, total liabilities-to-equity has increased, and net operating cash flow to total debt ratio has decreased, which suggests the company will not meet its obligations.

Verizon's times interest earned ratio has increased, total liabilities-to-equity has decreased, and net operating cash flow to total debt ratio has remained the same, which suggests the company will meet its obligations.

Verizon's times interest earned ratio has increased, total liabilities-to-equity has decreased, and net operating cash flow to total debt ratio has decreased, which suggests the company will not meet its obligations.

(c)Verizon's capital expenditures are expected to increase substantially as it seeks to respond to competitive pressures to upgrade the quality of its communications infrastructure. Which of the following best describes Verizon's liquidity and solvency in light of this strategic direction?

The company's profitability and operating cash flow are fairly strong, both are particularly high in relation to the company's liabilities and interest costs. The capital expenditures can be made with no borrowing or additional equity.

The company's profitability and operating cash flow are fairly weak, both are very low in relation to the company's liabilities and interest costs. The company is on the verge of bankruptcy.

The company's profitability and operating cash flow are fairly weak, both are very low in relation to the company's liabilities and interest costs. The company cannot fund any capital expenditures.

The company's profitability and operating cash flow are fairly strong, neither is particularly high in relation to the company's liabilities and interest costs. The capital expenditures may have to be funded with higher-cost equity.

For application case 4.6 – Data Mining Goes to Hollywood, describe the research study, the methodology, the results and the conclusion.

Data Mining Goes to Hollywood: Predicting Financial Success of Movies

Predicting box-office receipts (i.e., financial success) of a particular motion picture is an interesting and challenging problem. According to some domain experts, the movie industry is the “land of hunches and wild guesses” due to the difficulty associated with forecasting product demand, making the movie business in Hollywood a risky endeavor. In support of such observations, Jack Valenti (the longtime president and CEO of the Motion Picture Association of America) once mentioned that “…no one can tell you how a movie is going to do in the marketplace…not until the film opens in darkened theatre and sparks fly up between the screen and the audience.” Entertainment industry trade journals and magazines have been full of examples, statements, and experiences that support such a claim. Like many other researchers who have attempted to shed light on this challenging real-world problem, Ramesh Sharda and Dursun Delen have been exploring the use of data mining to predict the financial performance of a motion picture at the box office before it even enters production (while the movie is nothing more than a conceptual idea). In their highly publicized prediction models, they convert the forecasting (or regression) problem into a classification problem; that is, rather than forecasting the point estimate of box-office receipts, they classify a movie based on its box-office receipts in one of nine categories, ranging from “flop” to “blockbuster,” making the problem a multinomial classification problem. Table 5.4 illustrates the definition of the nine classes in terms of the range of box-office receipts.

Data

Data was collected from variety of movie-related databases (e.g., ShowBiz, IMDb, IMSDb, AllMovie, etc.) and consolidated into a single data set. The data set for the most recently developed models contained 2,632 movies released between 1998 and 2006. A summary of the independent variables along with their specifications is provided in Table 5.5. For more descriptive details and justification for inclusion of these independent variables, the reader is referred to Sharda and Delen (2007). Business Intelligence Spring 2017

Methodology

Using a variety of data mining methods, including neural networks, decision trees, support vector machines, and three types of ensembles, Sharda and Delen developed the prediction models. The data from 1998 to 2005 were used as training data to build the prediction models, and the data from 2006 was used as the test data to assess and compare the models’ prediction accuracy. Figure 5.15 shows a screenshot of IBM SPSS Modeler (formerly Clementine data mining tool) depicting the process map employed for the prediction problem. The upper-left side of the process map shows the model development process, and the lower-right corner of the process map shows the model assessment (i.e., testing or scoring) process (more details on IBM SPSS Modeler tool and its usage can be found on the book’s Web site).

Results

Table 5.6 provides the prediction results of all three data mining methods as well as the results of the three different ensembles. The first performance measure is the percent correct classification rate, which is called bingo. Also reported in the table is the 1-Away correct classification rate (i.e., within one category). The results indicate that SVM performed the best among the individual prediction models, followed by ANN; the worst of the three was the CART decision tree algorithm. In general, the ensemble models performed better than the individual predictions models, of which the fusion algorithm performed the best. What is probably more important to decision makers, and standing out in the results table, is the significantly low standard deviation obtained from the ensembles compared to the individual models. Business Intelligence Spring 2017

Conclusion

The researchers claim that these prediction results are better than any reported in the published literature for this problem domain. Beyond the attractive accuracy of their prediction results of the box-office receipts, these models could also be used to further analyze (and potentially optimize) the decision variables in order to maximize the financial return. Specifically, the parameters used for modeling could be altered using the already trained prediction models in order to better understand the impact of different parameters on the end results. During this process, which is commonly referred to as sensitivity analysis, the decision maker of a given entertainment firm could find out, with a fairly high accuracy level, how much value a specific actor (or a specific release date, or the addition of more technical effects, etc.) brings to the financial success of a film, making the underlying system an invaluable decision aid.