Nast Stores has derived the following consumer credit-scoring model after years of data collecting and model testing:Accounts Receivable Management | 153 Y = (0.20 × EMPLOYMT) + (0.4 × HOMEOWNER) + (0.3 × CARDS) EMPLOYMT = 1 if employed full-time, 0.5 if employed part-time, and 0 if unemployed HOMEOWNER = 1 if homeowner, 0 otherwise CARDS = 1 if presently has 1–5 credit cards, 0 otherwise Nast determines that a score of at least 0.70 indicates a very good credit risk, and it extends credit to these individuals.

a. I f Janice is employed part-time, is a homeowner, and has six credit cards at present, does the model indicate she should receive credit?

b. J anice just got a full-time job and closed two of her credit card accounts. Should she receive credit? Has her creditworthiness increased or decreased, according to the model?

c. Y our boss mentions that he just returned from a trade-association conference, at which one of the speakers recommended that length of time at present residence (regardless of homeownership status) be included in credit-scoring models. If the weight turns out to be 0.25, how do you think the variable would be coded (i.e., 0 stands for what, 1 stands for what, etc.)?

d. S uggest other variables that Associated might have left out of the model, and tell how you would code them (i.e., 0, 1, 2 are assigned to what conditions or variables?).

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:

Here is the code help you to paste data into your R:

data6<-'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
'
data6n<-read.table(textConnection(object=data6),
header=TRUE,
sep="",
stringsAsFactors = FALSE)

a. 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.

b. 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.

Price, Variable Cost per Unit, Contribution Margin, Contribution Margin Ratio, Fixed Expense

For each of the following independent situations, calculate the amount(s) required.

Required:

1. At the break-even point, Jefferson Company sells 85,000 units and has fixed cost of $349,900. The variable cost per unit is $0.20. What price does Jefferson charge per unit? Round to the nearest cent.
$

2. Sooner Industries charges a price of $93 and has fixed cost of $481,500. Next year, Sooner expects to sell 19,300 units and make operating income of $175,000. What is the variable cost per unit? What is the contribution margin ratio? Round your variable cost per unit answer to the nearest cent. Enter the contribution margin ratio as a percentage, rounded to two decimal places.

3. Last year, Jasper Company earned operating income of $28,920 with a contribution margin ratio of 0.3. Actual revenue was $241,000. Calculate the total fixed cost. Round your answer to the nearest dollar, if required.
$

4. Laramie Company has variable cost ratio of 0.55. The fixed cost is $102,650 and 21,900 units are sold at breakeven. What is the price? What is the variable cost per unit? The contribution margin per unit? (Round answers to the nearest cent.)

Consuela Lopez is a dietitian for the basketball team at BBB College, and she is attempting to determine a nutritious lunch menu for the team. She has set the following nutritional guidelines for each lunch serving:

            1. Between 1,500 and 2,000 calories

            2. At least 5 mg of iron

            3. At least 20 but no more than 60 g of fat

            4. At least 30 g of protein

            5. At least 40 g of carbohydrates

            6. No more than 30 mg of cholesterol

She selects the menu from seven basic food items, as follows, with the nutritional contribution per pound and the cost as give:

The dietitian wants to select a menu to meet the nutritional guidelines while minimizing the total cost per serving.

a. Formulate a linear programming model for this problem

b. Solve the model using Excel solver

Please show step by step in excel

Before preparing Part A, answer in complete sentences these 2 questions:

1. Looking at the direct materials equations for Standard Costs and Actual Costs, is the materials

price variance favorable or unfavorable? Why?

2. Looking at the direct materials equations for Standard Costs and Actual Costs, is the materials

Problem A

Direct materials, direct labor, and factory overhead cost variance analysis

Obj. 3, 4Mackinaw Inc. processes a base chemical into plastic. Standard costs and actual costs for direct materials, direct labor, and factory overhead incurred for the manufacture of 40,000 units of product were as follows:

Each unit requires 0.3 hour of direct labor.

Instructions

1. Determine (A) the direct materials price variance, direct materials quantity variance, and total direct materials cost variance; (B) the direct labor rate variance, direct labor time variance, and total direct labor cost variance; and (C) the variable factory overhead controllable variance, fixed factory overhead volume variance, and total factory overhead cost variance.

10. Consider the simplified scenario for genetic determinants of height in humans, where there are three genes (A/B/C) with varying numbers of alleles (3/3/2) affecting height, and with different effects in males and females. (Assume additive contributions, thus the effect of having genotype A1A2 is +0.1” + +0.2” = +0.3”). Average height for men and women is 69” and 64”.

What is the expected height for a male with genotype A2A2B1B3C1C2 (3 points)?

11. Consider a cross between two heterozygotes.
What is the probability that their first offspring has recessive phenotype? (2 points)

What is the probability that their first offspring has recessive phenotype and the second offspring also has the recessive phenotype? (2 points)

What is the probability that out of their first offspring, one has dominant phenotype and one has recessive phenotype? (2 points)

15. The gene for petal color in a flower has incomplete dominance, so that individuals with two A1 alleles (A1A1) are black, individuals with two A2 alleles (A2A2) are white, and individuals with one of each allele (A1A2) are mottled.

In a cross between two black flowers, what is the probability of getting a mottled offspring? (2 points)

3"      4"

5" 6" 7" 8" 9" 10" 11" 12"

1"      2"

In a cross between a black flower and a mottled flower, what is the probability of getting a black offspring? (2 points)

In a cross between two mottled flowers, if there are two offspring, what is the probability of getting one black offspring and one mottled offspring? (2 points)

In a cross between two mottled flowers, if there are two offspring, what is the probability of getting one white offspring and one mottled offspring? (2 points)

In a cross between two mottled flowers, if there are nine offspring, what is the probability of getting exactly three mottled offspring? (2 points)

16. Two individuals that are heterozygous for a recessive autosomal trait have an offspring with dominant phenotype. What is the probability that that offspring is a carrier (heterozygote?) (3 points)

If that offspring has an offspring with an individual with the recessive condition, what is the chance their offspring has the condition? (2 points)

17. Most randomly occurring mutations that occur in humans do not have an effect on phenotype. Why is this? (4 points)

18. Imagine that coronavirus has a 0.002% incidence in the population. A test for the virus has a 0.001% false positive rate and no false negative rate (false positive rate means the chance that if an uninfected individual takes the test the test will falsely identify them as infected). If a random person takes the test and gets a positive result, what is the chance that they are infected? (Show your work to earn partial credit) (4 points)

Now consider the case in the future, where the incidence of the virus has increased to 1%. Now if a random person takes the test and gets a positive result, what is the chance that they are infected? (2 points)

19. Your colleague is studying long toes in the California vole (Microtus californicus). She proposes that this trait is due to to an X-linked dominant allele.

You go for a hike in Oakland, and notice that very few of the California voles you see have the long toe trait. Does this affect your colleague’s hypothesis? How? Why? (2 points)

You go for a walk in Golden Gate Park, and notice that, among California voles in the Golden Gate population, females are much less likely than males to have the long toe trait. Does this affect your colleague’s hypothesis? How? Why? (2 points)

20. You are a genetic counseler. A mother and father with a son and a daughter come to see you. The mother and the father both have a very rare condition that no one has ever studied, but neither their son or their daugther does. Karyotype analysis shows that the mother and the daugther are XX and the father and the son are XY. You think about it and realize that this pattern cannot be due to a number of simple inheritance patterns. Explain why:

Why can’t it be an autosomal dominant condition? (2 points) Why can’t it be Y-linked condition? (2 points)
Why can’t it be an X-linked dominant condition? (2 points) Why can’t it be an X-linked recessive condition? (2 points) Why can’t it be a mitochondrial condition? (2 points)

A new fuel injection system has been engineered for pickup trucks. The new system and the old system both produce about the same average miles per gallon. However, engineers question which system (old or new) will give better consistency in fuel consumption (miles per gallon) under a variety of driving conditions. A random sample of 31 trucks were fitted with the new fuel injection system and driven under different conditions. For these trucks, the sample variance of gasoline consumption was 53.6. Another random sample of 23 trucks were fitted with the old fuel injection system and driven under a variety of different conditions. For these trucks, the sample variance of gasoline consumption was 33.7. Test the claim that there is a difference in population variance of gasoline consumption for the two injection systems. Use a 5% level of significance. How could your test conclusion relate to the question regarding the consistency of fuel consumption for the two fuel injection systems?

(a) What is the level of significance?


State the null and alternate hypotheses.

H_o: σ₁² = σ₂²; H₁: σ₁² > σ₂²

H_o: σ₁² > σ₂²; H₁: σ₁² = σ₂²    

H_o: σ₂² = σ₁²; H₁: σ₂² > σ₁²

H_o: σ₁² = σ₂²; H₁: σ₁² ≠ σ₂²

(b) Find the value of the sample F statistic. (Round your answer to two decimal places.)


What are the degrees of freedom?

What assumptions are you making about the original distribution?

The populations follow independent normal distributions.

The populations follow independent chi-square distributions. We have random samples from each population.    

The populations follow dependent normal distributions. We have random samples from each population.

The populations follow independent normal distributions. We have random samples from each population.

(c) Find or estimate the P-value of the sample test statistic.

P-value > 0.200

0.100 < P-value < 0.200    

0.050 < P-value < 0.100

0.020 < P-value < 0.050

0.002 < P-value < 0.020

P-value < 0.002

(d) Based on your answers in parts (a) to (c), will you reject or fail to reject the null hypothesis?

At the α = 0.05 level, we reject the null hypothesis and conclude the data are not statistically significant.

At the α = 0.05 level, we reject the null hypothesis and conclude the data are statistically significant.    

At the α = 0.05 level, we fail to reject the null hypothesis and conclude the data are not statistically significant.

At the α = 0.05 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 sufficient evidence that the variance in consumption of gasoline is greater in the new fuel injection systems.

Reject the null hypothesis, there is insufficient evidence that the variance in consumption of gasoline is greater in the new fuel injection systems.    

Reject the null hypothesis, there is sufficient evidence that the variance in consumption of gasoline is different in both fuel injection systems.

Fail to reject the null hypothesis, there is insufficient evidence that the variance in consumption of gasoline is different in both fuel injection systems.

A new fuel injection system has been engineered for pickup trucks. The new system and the old system both produce about the same average miles per gallon. However, engineers question which system (old or new) will give better consistency in fuel consumption (miles per gallon) under a variety of driving conditions. A random sample of 41 trucks were fitted with the new fuel injection system and driven under different conditions. For these trucks, the sample variance of gasoline consumption was 54.8. Another random sample of 27 trucks were fitted with the old fuel injection system and driven under a variety of different conditions. For these trucks, the sample variance of gasoline consumption was 36.4. Test the claim that there is a difference in population variance of gasoline consumption for the two injection systems. Use a 5% level of significance.

How could your test conclusion relate to the question regarding the consistency of fuel consumption for the two fuel injection systems? (a) What is the level of significance? 0.05

State the null and alternate hypotheses. Ho: σ12 = σ22; H1: σ12 > σ22 Ho: σ12 > σ22; H1: σ12 = σ22 Ho: σ22 = σ12; H1: σ22 > σ12 Ho: σ12 = σ22; H1: σ12 ≠ σ22

(b) Find the value of the sample F statistic. (Round your answer to two decimal places.)

What are the degrees of freedom? dfN dfD

What assumptions are you making about the original distribution?

The populations follow independent normal distributions. We have random samples from each population.

The populations follow dependent normal distributions. We have random samples from each population.

The populations follow independent normal distributions.

The populations follow independent chi-square distributions. We have random samples from each population.

(c) Find or estimate the P-value of the sample test statistic.

P-value > 0.200 0.100 < P-value < 0.200 0.050 < P-value < 0.100 0.020 < P-value < 0.050 0.002 < P-value < 0.020 P-value < 0.002

(d) Based on your answers in parts (a) to (c), will you reject or fail to reject the null hypothesis?

At the α = 0.05 level, we reject the null hypothesis and conclude the data are not statistically significant.

At the α = 0.05 level, we reject the null hypothesis and conclude the data are statistically significant.

At the α = 0.05 level, we fail to reject the null hypothesis and conclude the data are not statistically significant.

At the α = 0.05 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 sufficient evidence that the variance in consumption of gasoline is greater in the new fuel injection systems.

Reject the null hypothesis, there is insufficient evidence that the variance in consumption of gasoline is greater in the new fuel injection systems.

Reject the null hypothesis, there is sufficient evidence that the variance in consumption of gasoline is different in both fuel injection systems.

Fail to reject the null hypothesis, there is insufficient evidence that the variance in consumption of gasoline is different in both fuel injection systems.

A new fuel injection system has been engineered for pickup trucks. The new system and the old system both produce about the same average miles per gallon. However, engineers question which system (old or new) will give better consistency in fuel consumption (miles per gallon) under a variety of driving conditions. A random sample of 41 trucks were fitted with the new fuel injection system and driven under different conditions. For these trucks, the sample variance of gasoline consumption was 53. Another random sample of 27 trucks were fitted with the old fuel injection system and driven under a variety of different conditions. For these trucks, the sample variance of gasoline consumption was 34.6. Test the claim that there is a difference in population variance of gasoline consumption for the two injection systems. Use a 5% level of significance. How could your test conclusion relate to the question regarding the consistency of fuel consumption for the two fuel injection systems?

(a) What is the level of significance?


State the null and alternate hypotheses.

H_o: σ₁² = σ₂²; H₁: σ₁² > σ₂²

H_o: σ₁² > σ₂²; H₁: σ₁² = σ₂²   

H_o: σ₂² = σ₁²; H₁: σ₂² > σ₁²

H_o: σ₁² = σ₂²; H₁: σ₁² ≠ σ₂²

(b) Find the value of the sample F statistic. (Round your answer to two decimal places.)


What are the degrees of freedom?

What assumptions are you making about the original distribution?

The populations follow dependent normal distributions. We have random samples from each population.

The populations follow independent normal distributions.    

The populations follow independent chi-square distributions. We have random samples from each population.

The populations follow independent normal distributions. We have random samples from each population.

(c) Find or estimate the P-value of the sample test statistic.

P-value > 0.200

0.100 < P-value < 0.200   

0.050 < P-value < 0.100

0.020 < P-value < 0.050

0.002 < P-value < 0.020

P-value < 0.002

(d) Based on your answers in parts (a) to (c), will you reject or fail to reject the null hypothesis?

At the α = 0.05 level, we reject the null hypothesis and conclude the data are not statistically significant.

At the α = 0.05 level, we reject the null hypothesis and conclude the data are statistically significant.  

   At the α = 0.05 level, we fail to reject the null hypothesis and conclude the data are not statistically significant.

At the α = 0.05 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 sufficient evidence that the variance in consumption of gasoline is greater in the new fuel injection systems.

Reject the null hypothesis, there is insufficient evidence that the variance in consumption of gasoline is greater in the new fuel injection systems.   

Reject the null hypothesis, there is sufficient evidence that the variance in consumption of gasoline is different in both fuel injection systems.

Fail to reject the null hypothesis, there is insufficient evidence that the variance in consumption of gasoline is different in both fuel injection systems.

*** It flagged the word support so job sub = job support

Gallatin Carpet Cleaning is a small, family-owned business operating out of Bozeman, Montana. For its services, the company has always charged a flat fee per hundred square feet of carpet cleaned. The current fee is $22.60 per hundred square feet. However, there is some question about whether the company is actually making any money on jobs for some customers—particularly those located on remote ranches that require considerable travel time. The owner’s daughter, home for the summer from college, has suggested investigating this question using activity-based costing. After some discussion, she designed a simple system consisting of four activity cost pools. The activity cost pools and their activity measures appear below:

The total cost of operating the company for the year is $379,000 which includes the following costs:

Resource consumption is distributed across the activities as follows:

Job sup consists of receiving calls from potential customers at the home office, scheduling jobs, billing, resolving issues, and so on.

Required:

1.Prepare the first-stage allocation of costs to the activity cost pools.

2. Compute the activity rates for the activity cost pools. (Round your answers to 2 decimal places.)

3. The company recently completed a 200 square foot carpet-cleaning job at the Flying N Ranch—a 52-mile round-trip journey from the company’s offices in Bozeman. Compute the cost of this job using the activity-based costing system.

Cost of job =

4. The revenue from the Flying Ranch was $45.20 (200 square feet @ $22.60 per hundred square feet). Calculate the customer margin earned on this job.

Customer Margin =