Questions
BuoyBuoy manufactures flotation vests in Atlanta comma GeorgiaAtlanta, Georgia. Buoy'sBuoy's contribution margin income statement for the...

BuoyBuoy

manufactures flotation vests in

Atlanta comma GeorgiaAtlanta, Georgia.

Buoy'sBuoy's

contribution margin income statement for the most recent month contains the following​ data:

Buoy

Contribution Margin Income Statement (Variable Costing)

For Sales Volume of 31,000 Units

Total

Sales revenue

$434,000

Less variable expenses:

Variable manufacturing costs (DM, DL, Variable MOH)

93,000

Variable operating expenses (selling and administrative)

108,000

Contribution margin

$233,000

Less fixed expenses:

Fixed manufacturing overhead

$121,000

Fixed operating expenses (selling and administrative)

95,000

Operating income (loss)

$17,000

Requirement 1. Prepare an incremental analysis to determine whether

BuoyBuoy

should accept this special sales order. ​(Enter a​ "0" for any zero balances. Use parentheses or a minus sign to indicate a negative contribution margin​and/or a decrease in operating income from the special​ order.)

Total Order

Incremental Analysis of Special Sales Order Decision

Per Unit

(5,100 units)

Revenue from special order

Less variable expense associated with the order:

Variable manufacturing costs

Contribution margin

Less: Additional fixed expenses associated with the order

Increase (decrease) in operating income from the special order

​Decision:

Accept the special sales order.

Reject the special sales order.

Requirement 2. Identify​ long-term factors

BuoyBuoy

should consider in deciding whether to accept the special sales order.

In addition to determining the special​ order's effect on operating​ profits,

BuoyBuoy​'s

managers also should consider the​ following:

A.

How will

BuoyBuoy​'s

competitors​ react? Will they retaliate by cutting their prices and starting a price​ war?

B.

Will lowering the sale price tarnish

BuoyBuoy​'s

image as a quality​ brand?

C.

Will

BuoyBuoy​'s

other customers find out about the lower sale price

BuoyBuoy

accepted from

OvertonOverton​?

If​ so, will these other customers demand lower sale​ prices?

D.

All of the above.

E.

None of the above.

In: Accounting

42. Besides just offering low prices, how can could a firm make their product or service...

42. Besides just offering low prices, how can could a firm make their product or service more inelastic?

A. Offering WOW customer service and studying new ways to generate repeat business
   B. Improving the quality of the product or service
   C. Offering loyal customers some type of reward like free air and hotel travel to Las Vegas   
   D. All of the above

43. Which item below represents a non-price marketing strategy?   

Sending thank you cards to your customers thanking them for their loyalty
B. Improving the customer service
C. Offering a one-year money back guarantee   
D. All of the above

44. Why do local governments like to tax inelastic goods such as liquor and cigarettes?

A. Inelastic goods tend to be price insensitive.
B. Consumers can’t easily stop using inelastic goods
C. The government has an easier time collecting more tax revenue
D. A, B and C are all correct responses.

45. A product or service will become more elastic over time because:

A. This is a false statement. Over time products become more inelastic
B. With more time consumers can look for substitute goods or services
C. The inflection point of the demand curve will point up
D. All of the statement above are false
46. When Coca-Cola put real cocaine in their drink in the early 1900s, then what did they create?

A. A more inelastic demand curve
B. A more elastic demand curve
C. A new equilibrium point on the total revenue curve
D. A new equilibrium point on the Production Possibilities Curve
49. The source of all economic problems comes from what?

   A. Greedy people
   B. Scarcity
   C. The fact that people don’t have enough money to buy what they need
   D. The fact that government charges too much in taxes

In: Economics

CASE STUDY USING EXCEL SPREADSHEET You work for Theo Walcott Tours Ltd which provide tourists and...

CASE STUDY USING EXCEL SPREADSHEET You work for Theo Walcott Tours Ltd which provide tourists and visitors with ‘experiences’ of Perth and its surrounds. Your manager is currently investigating introducing another product, which are ‘Luxury’ helicopter rides over beautiful bushland. Each trip would be 50km in total. Your manager wants you to use cost-volume-profit analysis in order to help assess the plan’s feasibility. She provides you with the following estimated data: Selling price per trip: $600 (total for 3 customers – trips only run with 3 customers) Costs: Fuel: $50 per trip Walcott ‘goodie bag’ per customer: $40 Helicopter rental per month: $20,000 Insurance per month (unlimited trips): $1,000 Pilot costs: $5,000 per month plus $100 per trip Maintenance costs are difficult to estimate but data from a similar company in a different location shows that these monthly costs were $11,000 when 5,000 kms were flown and $5000 when 1,500 kms were flown. ACCM 4100 Management Accounting 1 Trimester 2, 2020: Individual Excel Assignment REQUIRED: Calculate the following: 1) The Break-even point in trips per month 2) The Break-even point in dollars of revenue per month 3) Assuming a profit after tax requirement from the Helicopter trip business of $120,000 per year and a tax rate of 30%, calculate: a) Trips required per month to obtain target profit b) Revenue required per month to obtain target profit Your manager has requested that the spreadsheet is easy to use for ‘What-if’ analysis – so she would like to be able to change some of the inputs to see the impact on the calculations above – for example, if the Helicopter were able to be rented more cheaply or the selling price was increased.

In: Accounting

Solve as an anova two-way model (the second factor is in the rows and has levels...

Solve as an anova two-way model (the second factor is in the rows and has levels A and B))

The null hypothesES are:

H0: μa = μb = μc (all Factor means for the column-wise factor are equal)

H0: μAmy = μBert (all Factor means for the row-wise factor are equal)

H0: the column-wise Factor and the row-wise Factor do not interact

Can we reject them at the alpha = 0.05 level?

Use the Excel data below:

A B C
Amy 23 21 20
25 21 22
Bert 27 24 26
28 27 27

In: Statistics and Probability

Let’s define a new number system, where we represent a number by the remainder we get...

Let’s define a new number system, where we represent a number by the remainder we get on
dividing by successive primes, i.e., by 2, 3, 5, 7, 11, 13, 17, etc. Thus, 15 might be represented as
[1,0,0], and 27 might be [1,0,2].

1.) What numbers do [1, 1, 1, 1] and [1, 2, 3, 4] represent? Are the representations unique? What
other numbers might these lists represent?

2.) We know that 15 + 27 = 42. What is the representation of 42? Can you see how to get this from
the representations for 15 and 27?

In: Computer Science

1. Consider the first and second exam scores of the 10 students listed below. Calculate the...

1. Consider the first and second exam scores of the 10 students listed below. Calculate the Pearson's correlation coefficient for the dataset below and interpret what that means.

exam 1 exam 2
24 37
22 35
21 42
22 40
21 41
23 37
23 30
23 37
21 48
25 30

A)The correlation is -0.774 . There is a strong negative linear association between Exam 1 and Exam 2

B) The correlation is -0.774 . There is a weak negative linear association between Exam 1 and Exam 2 .

C)The correlation is 0.774 . There is a strong positive linear association between Exam 1 and Exam 2 .

D)The correlation is -0.774 . There is a strong positive linear association between Exam 1 and Exam 2 .

E)The correlation is 0.774 . There is a strong negative linear association between Exam 1 and Exam 2 .

2. Consider the first and second exam scores of the 10 students listed below. Calculate the Pearson's correlation coefficient for the data set below and interpret what that means.

exam 1 exam 2
23 29
29 24
19 19
17 27
24 22
10 20
29 28
20 18
25 18
16

29

A)The correlation is 0.147 . There is a weak negative linear association between Exam 1 and Exam 2 .

B)The correlation is -0.147 . There is a weak positive linear association between Exam 1 and Exam 2

C)The correlation is 0.147 . There is a strong positive linear association between Exam 1 and Exam 2

D)The correlation is -0.147 . There is a weak negative linear association between Exam 1 and Exam 2

E)

The correlation is 0.147 . There is a weak positive linear association between Exam 1 and Exam 2 .

In: Math

PYTHON - You are given a data.csv file in the /root/customers/ directory containing information about your...

PYTHON - You are given a data.csv file in the /root/customers/ directory containing information about your customers. It has the following columns: ID,NAME,CITY,COUNTRY,CPERSON,EMPLCNT,CONTRCNT,CONTRCOST where ID: Unique id of the customer NAME: Official customer company name CITY: Location city name COUNTRY: Location country name CPERSON: Email of the customer company contact person EMPLCNT: Customer company employees number CONTRCNT: Number of contracts signed with the customer CONTRCOST: Total amount of money paid by customer (float in format dollars.cents) Read and analyze the data.csv file, and output the answers to these questions: How many total customers are in this data set? How many customers are in each city? How many customers are in each country? Which country has the largest number of customers' contracts signed in it? How many contracts does it have? How many unique cities have at least one customer in them? The answers should be formatted as: Total customers: Customers by city: : : ... Customers by country: : : ... Country with most customers' contracts: USA ( contracts) Unique cities with at least one customer: The answers for Customers by city and Customers by country must be sorted by CITY and COUNTRY respectively, in ascending order. If there are several cities that are tied for having the most customers' contracts, print the lexicographically bigger one.

In: Computer Science

A shipping company handles containers in three different sizes.

A shipping company handles containers in three different sizes. 

1. 27 ft3 (3 x 3 x 3) 

2. 125 ft3

3. 512 ft3 


Let Xi (i = 1, 2, 3) denote the number of type i containers shipped during a given week. With μi = E(X;) and σi2 = V(Xi), suppose that the mean values and standard deviations are as follows. 

μ1 = 500 μ2 = 450 μ3 = 50

σ1 = 8    σ2 = 12    σ3 = 10  


Suppose that the Xi's are independent with each one having a normal distribution. What is the probability that the total volume shipped is at most 100,000 ft3 (Round your answer to four decimal places.)

In: Math

The number of hours worked by 24 employees of a company is given below: 40 43...

The number of hours worked by 24 employees of a company is given below:
40 43 40 39 36 44 40 39 39 52 27 50
41 47 40 48 38 36 25 41 35 36 16 40
(a) (6 points) Calculate the mean, variance and standard derivation for the given data
(b) (6 points) Calculate the three quartiles (Q1, Q2, and Q3) and the Interquartile range
(IQR)
(c) (4 points) Calculate the values of the lower fence and the upper fence for a boxplot.
(d) (5 points) Construct a box-and-whisker plot. Comment on the shape of the distri-
bution of the data. List any potential outliers, if any

In: Advanced Math

To study the effect of temperature on yield in a chemical process, five batches were produced...

To study the effect of temperature on yield in a chemical process, five batches were produced at each of three temperature levels. The results follow.

Temperature

50°C 60°C 70°C
32 34 29
22 35 34
34 38 34
37 27 36
30 31 37

a. Construct an analysis of variance table (to 2 decimals but p-value to 4 decimals, if necessary).

Source of Variation Sum of Squares Degrees of Freedom Mean Square F p-value
Treatments
Error
Total

b. Use a  level of significance to test whether the temperature level has an effect on the mean yield of the process.

Calculate the value of the test statistic (to 2 decimals).

In: Statistics and Probability