FINANCIAL STATEMENT ANALYSIS with R programming:

Scenario: You are a Data Scientist working for a consulting firm. One of your colleagues from the Auditing

department has asked you to help them with financial statement of their organization.

You have been supplied with two vectors of data: monthly revenue and monthly expenses for the financial

year in question.

revenue in 12 months (14574.49, 7606.46, 8611.41, 9175.41, 8058.65, 8105.44, 11496.28, 9766.09,

10305.32, 14379.96, 10713.97, 15433.50)

expenses

in 12 months (12051.82, 5695.07, 12319.20, 12089.72, 8658.57, 840.20, 3285.73, 5821.12,

6976.93, 16618.61, 10054.37, 3803.96)

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Steps + sloutions:

revenue<- c(14574.49, 7606.46, 8611.41, 9175.41, 8058.65, 8105.44, 11496.28, 9766.09,10305.32, 14379.96, 10713.97, 15433.50)

expenses<- c(12051.82, 5695.07, 12319.20, 12089.72, 8658.57, 840.20, 3285.73, 5821.12,

6976.93, 16618.61, 10054.37, 3803.96)

profit for each month : profit<- revenue - expenses

- profit after tax for each month (the tax rate is 30%): ProfitAfterTax<- profit - profit *0.3

- profit margin for each month in percentage (hint: equals profit after tax divided by revenue): ProfitMargin<- round(profitAfterTax / revenue, 2) * 100

==================================

- good months - where the profit after tax was greater than the mean for the year (mean is computed with mean function as mean(x/n)) (5 points)

- bad months - where the profit after tax was less than the mean for the year (5 points)

- the best month - where the profit after tax was max for the year (5 points)

- the worst month - where the profit after tax was min for the year (5 points)

Hints: round() mean() max() min()

Silver Lining Inc. has a balanced scorecard with a strategy map that shows that delivery time and the number of erroneous shipments are expected to affect the company’s ability to satisfy the customer. Further, the strategy map for the balanced scorecard shows that the hours from ordered to delivered affects the percentage of customers who shop again, and the number of erroneous shipments affects the online customer satisfaction rating. The following information is also available:

• The company’s target hours from ordered to delivered is 40.
• Every hour over the ordered-to-delivered target results in a 0.5% decrease in the percentage of customers who shop again.
• The company’s target number of erroneous shipments per year is no more than 65.
• Every error over the erroneous shipments target results in a 0.5 point decrease in the online customer satisfaction rating and an added future financial loss of $500.
• The company estimates that for every 1% decrease in the percentage of customers who shop again, future profit decreases by $4,000 and market share decreases by 0.3%.
• The company also estimates that for every 1 point decrease in the overall online customer satisfaction rating (on a scale of 1 to 10), future profit decreases by $3,000 and market share decreases by 0.6%.

Using these estimates, determine how much future profit and future market share will change if:

• Average hours from ordered to shipped is 27.5.
• Average shipping time (hours from shipped to delivered) is 16.3.
• Number of erroneous shipments is 80.

a) Total decrease in future profit $

Round your answer to two decimal places.

b) Total decrease in future market share %

A sample of 31 people took a written driver’s license exam. Two variables were measured on them: The result of the exam (0 = fail, 1 = pass), and how much time (in hours) the person studied for the exam. Using the data, fit an appropriate regression model to determine whether time spent studying is a useful predictor of the chance of passing the exam. Formally assess the overall fit of the model. Formally assess whether time spent studying is a useful predictor (as always, providing numerical justification (test statistic and P-value) for your conclusion). Carefully interpret what the estimated model tells you about how the chance of passing the exam changes as the time spent studying changes. A prospective examinee named Matthew spent 3.0 hours studying for his written exam. Estimate (with a point estimate and with a 90% interval) his probability of passing the exam. Based on this estimate, predict whether he will pass or fail.

SAS code:

DATA three;
INPUT result hours;
/* result=0 is fail; result=1 is pass */
cards;
0 0.8
0 1.6
0 1.4
1 2.3
1 1.4
1 3.2
0 0.3
1 1.7
0 1.8
1 2.7
0 0.6
0 1.1
1 2.1
1 2.8
1 3.4
1 3.6
0 1.7
1 0.9
1 2.2
1 3.1
0 1.4
1 1.9
0 0.4
0 1.6
1 2.5
1 3.2
1 1.7
1 1.9
0 2.2
0 1.3
1 1.5
;
run;

(20.44) Cola makers test new recipes for loss of sweetness during storage. Trained tasters rate the sweetness before and after storage. Here are the sweetness losses ( sweetness before storage minus sweetness after storage) found by 10 tasters for one new cola recipe:

2 0.3 0.6 2.1 -0.4 2.2 -1.3 1.2 1.1 2.2

Take the data from these 10 carefully trained tasters as an SRS from a large population of all trained tasters. Is there evidence at the 5% level that the cola lost sweetness? If the cola has not lost sweetness, the ratings after should be the same as before it was stored.

The test statisic is t = ___ (±0.001)

No Yes .

There is evidence that cytotoxic T lymphocytes (T cells) participate in controlling tumor growth and that they can be harnessed to use the body's immune system to treat cancer. One study investigated the use of a T cell-engaging antibody, blinatumomab, to recruit T cells to control tumor growth. The data below are T cell counts (1000 per microliter) at baseline (beginning of the study) and after 20 days on blinatumomab for 6 subjects in the study. The difference (after 20 days minus baseline) is the response variable.

Baseline 0.04 0.02 0 0.02 0.31 0.29

After 20 days 0.18 0.27 1.2 0.05 1.02 0.34

Difference 0.14 0.25 1.2 0.03 0.71 0.05

Do the data give evidence at the 4 % level that the mean count of T cells is higher after 20 days on blinatumomab? The test statistic is

t =____ (±0.001)

Yes No

can you please show how to get the T on a TI-84.

MC0102: A student has a nickel, dime, quarter, and half-dollar (yes - let's just pretend) in her pocket. If she pulls 3 coins out of her pocket without replacement, what is the sample space of simple events? Assume that the order that she pulls out the coins does not matter (so pulling N, D, Q is the same as pulling Q, D, N, etc.). N=Nickel, D=Dime, Q=Quarter, and H=Half-dollar.

You are trying to develop a strategy for investing in two different stocks. The anticipated annual return for a​ $1,000 investment in each stock under four different economic conditions has the probability distribution shown to the right. Complete parts​ (a) through​ (c) below.

Probability Economic condition Stock_X Stock_Y

0.1 Recession -150 -170

0.2 Slow_growth    20 50

0.4 Moderate_growth 100 130

0.3 Fast_growth 160 210

a. Compute the expected return for stock X and for stock Y. The expected return for stock X is ? ​(Type an integer or a​ decimal.)

b. Compute the standard deviation for stock X and for stock Y.

c. Which of the following best describes the decision that should be​ made? Choose the correct answer below.

A.Based on the expected ​value, stock Y should be chosen. ​However, stock Y has a larger standard ​deviation, resulting  in a higher ​risk, which should be taken into consideration.

B.Since the expected values are approximately the​ same, either stock can be invested in.​ However, stock X has a larger standard​ deviation, which results in a higher risk. Due to the higher risk of stock X​, stock Y should be invested in.

C.Since the expected values are approximately the​ same, either stock can be invested in.​ However, stock Y has a larger standard​ deviation, which results in a higher risk. Due to the higher risk of stock Y​, stock X should be invested in.

D.Based on the expected ​value, stock X should be chosen. ​However, stock X has a larger standard ​deviation, resulting  in a higher ​risk, which should be taken into consideration.

Hot & Cold and Caldo Freddo are two European manufacturers of home appliances that have merged. Hot & Cold has plants in France, Germany, and Finland, where Caldo Freddo has plants in the United Kingdom and Italy. The European market is divided into four regions: North, East, West, and South. Plant capacities (millions of units per year), annual fixed costs (millions of euros per year), regional demand (millions of units), and variable production and shipping costs (euros per unit) are listed in the following table.

Each appliance sells for an average price of 300 euros. All plants are currently treated as profit centers, and the company pays taxes separately for each plant. Tax rates in the various countries are as follows: France, 0.25; Germany, 0.25; Finland, 0.3; UK 0.2; Italy, 0.35.

1. Before the merger, what is the optimal network for each of the two firms if their goal is to minimize costs? What is the optimal network if the goal is to maximize after-tax profits?

This is the HW question I cannot get the correct answer for. I've completed the first step but I cannot seem to get the correct numbers for EFN for 20, 25 and 30%!?!? See below for given financial statements and my table with the pro forma of 20, 25 and 30% numbers

Problem 2: (Revised 6.3) Magazine Advertising: In a study of revenue from advertising, data were collected for 41 magazines list as follows. The variables observed are number of pages of advertising and advertising revenue. The names of the magazines are listed as:

(use sas）

Adv Revenue

25 50

15 49.7

20 34

17 30.7

23 27

17 26.3

14 24.6

22 16.9

12 16.7

15 14.6

8 13.8

7 13.2

9 13.1

12 10.6

1 8.8

6 8.7

12 8.5

9 8.3

7 8.2

9 8.2

7 7.3

1 7

77 6.6

13 6.2

5 5.8

7 5.1

13 4.1

4 3.9

6 3.9

3 3.5

6 3.3

4 3

3 2.5

3 2.3

5 2.3

4 1.8

4 1.5

3 1.3

3 1.3

4 1

2 0.3

1. Fit a linear regression equation relating advertising revenue to advertising pages. Verify that the fit is poor.
2. Choose an appropriate transformation of the data and fit the model to the transformed data. Evaluate the fit.
3. You should not be surprised by the presence of a large number of outliers because the magazines are highly heterogeneous and it is unrealistic to expect a single relationship to connect all of them. Find outliers and high leverage points. Delete the outliers and obtain an acceptable regression equation that relates advertising revenue to advertising pages.
4. For the deleted data, check the homogeneity of the variance. Choose an appropriate transformation of the data and fit the model to the transformed data. Evaluate the fit.