Questions
A company produces six products in the following manner. Each unit of raw material purchased yields...

A company produces six products in the following manner. Each unit of raw material purchased yields 4 units of product 1, 2 units of product 2, and 1 unit of product 3. Up to 1200 units of product 1 can be sold and up to 300 units of product 2 can be sold. Demand for products 3 and 4 is unlimited. Each unit of product 1 produced from raw material can be sold or processed further. Each unit of product 1 that is processed further yields 1 unit of product 4. Each unit of product 2 can be sold or processed further. Each unit of product 2 that is processed further yields 0.8 unit of product 5 and 0.3 unit of product 6.

For products 3 through 6, the production cost is additional to the costs already incurred.

Up to 1000 units of product 5 can be sold, and up to 800 units of product 6 can be sold. Up to 3000 units of raw material can be purchased at $6 per unit. Leftover units of products 5 and 6 must be destroyed. It costs $4 to destroy each leftover unit of product 5 and $3 to destroy each leftover unit of product 6. The selling price and production cost per unit of each product is provided in the table. The cost of raw material is irrelevant to solving this problem and is ignored in the costs provided.

Determine a profit-maximizing production schedule.

MICROSOFT EXCEL SOLVER SOLUTION PLEASE!!!!!!! The other solutions listed for this problem are incorrect.

Product Units produced per unit of raw material used Units produced per unit of Product 1 processed further Units produced per unit of Product 2 processed further Max Dem Selling price Production cost
1 4 1200 7 4
2 2 300 6 4
3 1 No limit 4 2
4 1 No limit 3 1
5 0.8 1000 20 5
6 0.3 800 35 5
3000 Units of raw material available to purchase
$6 Cost per unit of raw material
$4 Cost to destroy excess Product 5
$3 Cost to destroy excess Product 6

In: Statistics and Probability

4.In dancing bears, short fur is dominant to long fur, and curly hair is dominant to...

4.In dancing bears, short fur is dominant to long fur, and curly hair is dominant to straight. The genes for these traits are located on separate autosomes.

You have a large population of dancing bears with the following allele frequencies

Short fur (S) p = 0.5, Long fur (s) q = 0.5

Curly hair (C) p = 0.3, Straight hair (c) q = 0.7

You allow the population to randomly breed for several generations. You have a population of 1000 dancing bears and count 510 with curly hair.

Is this population in Hardy-Weinberg equilibrium for this trait based on the starting allele frequencies?

Multiple Choice

a.No, that is not enough with curly hair.

b.No, that is too many with curly hair.

c.Yes.

5.In dancing bears, short fur is dominant to long fur, and curly hair is dominant to straight. The genes for these traits are located on separate autosomes.

You have a large population of dancing bears with the following allele frequencies

Short fur (S) p = 0.5, Long fur (s) q = 0.5

Curly hair (C) p = 0.3, Straight hair (c) q = 0.7

You allow the population to randomly breed for several generations. You have a population of 1000 dancing bears and count 255 with short, curly fur.

Is this population in Hardy-Weinberg equilibrium for these traits based on the starting allele frequencies?

Multiple Choice

a.No, that is not enough with short, curly hair.

b.Yes.

c.No, that is too many with short, curly fur.

6.A species of plant that grows on rock outcrops produces a chemical on its stigmas that prevents pollen germination. After collecting pollen over the course of a day, the chemical wears off and all the pollen grains germinate at once with the fastest growing male fertilizing all or most of the eggs in the ovary.

You conduct an experiment where you mix equal amounts of pollen from three different plants and place it on the stigmas of three separate flowers on six different plants. You count the number of seeds produced by each flower and use genetic tests to determine paternity of the seeds.

You think that the same male plant will fertilize the most seeds on all of the female plants. If so, this is an example of disruptive selection.

Multiple Choice

a.True.

b.False.

In: Biology

Five years ago, a company was considering the purchase of 74 new diesel trucks that were...

Five years ago, a company was considering the purchase of 74 new diesel trucks that were 15.13% more fuel-efficient than the ones the firm is now using. The company uses an average of 10 million gallons of diesel fuel per year at a price of $1.25 per gallon. If the company manages to save on fuel costs, it will save $1.875 million per year (1.5 million gallons at $1.25 per gallon). On this basis, fuel efficiency would save more money as the price of diesel fuel rises (at $1.35 per gallon, the firm would save $2.025 million in total if he buys the new trucks).

Consider two possible forecasts, each of which has an equal chance of being realized. Under assumption #1, diesel prices will stay relatively low; under assumption #2, diesel prices will rise considerably. The 74 new trucks will cost the firm $5 million. Depreciation will be 25.35% in year 1, 38.81% in year 2, and 36.55% in year 3. The firm is in a 39% income tax bracket and uses a 10% cost of capital for cash flow valuation purposes. Interest on debt is ignored. In addition, consider the following forecasts:

Forecast for assumption #1 (low fuel prices):

Price of Diesel Fuel per Gallon

Prob. (same for each year)

Year 1

Year 2

Year 3

0.1

$0.83

$0.93

$1.02

0.2

$1.01

$1.11

$1.13

0.3

$1.12

$1.21

$1.3

0.2

$1.31

$1.45

$1.47

0.2

$1.4

$1.57

$1.62

Forecast for assumption #2 (high fuel prices):

Price of Diesel Fuel per Gallon

Prob. (same for each year)

Year 1

Year 2

Year 3

0.1

$1.21

$1.49

$1.72

0.3

$1.31

$1.7

$2.01

0.4

$1.82

$2.32

$2.53

0.2

$2.19

$2.49

$2.79

Required: Calculate the percentage change on the basis that an increase would take place from the NPV under assumption #1 to the probability-weighted (expected) NPV.

Answer% Do not round intermediate calculations. Input your answer as a percent rounded to 2 decimal places (for example: 28.31%).

In: Finance

Background: Anorexia is well known to be difficult to treat. The data set provided below contains...

Background: Anorexia is well known to be difficult to treat. The data set provided below contains data on the weight gain for three groups of young female anorexia patients. These groups include a control group, a group receiving cognitive behavioral therapy and a group receiving family therapy. Source: Hand, D. J., Daly, F., McConway, K., Lunn, D. and Ostrowski, E. eds (1993) A Handbook of Small Data Sets. Chapman & Hall, Data set 285 (p. 229).

Directions: Click on the Data button below to display the data. Copy the data into a statistical software package and click the Data button a second time to hide it. Then perform an analysis of variance (ANOVA) to determine whether or not the differences in weight gain between the treatment groups is statistically significant.

Data

Control CBT Family
-0.5 1.7 11.4
-9.3 0.7 11
-5.4 -0.1 5.5
12.3 -0.7 9.4
-2 -3.5 13.6
-10.2 14.9 -2.9
-12.2 3.5 -0.1
11.6 17.1 7.4
-7.1 -7.6 21.5
6.2 1.6 -5.3
-0.2 11.7 -3.8
-9.2 6.1 13.4
8.3 1.1 13.1
3.3 -4 9
11.3 20.9 3.9
0 -9.1 5.7
-1 2.1 10.7
-10.6 -1.4
-4.6 1.4
-6.7 -0.3
2.8 -3.7
0.3 -0.8
1.8 2.4
3.7 12.6
15.9 1.9
-10.2 3.9
0.1
15.4
-0.7
  1. State the null and alternative hypotheses.


  2. Compute the test statistic. Document how SSTr and SSE were computed. Use 4 decimal places for the sample means, sample standard deviations and the grand mean and round your answers for SSTr and SSE to 2 decimal places.

    Use the values for SSTr and SSE to complete the following ANOVA table. Round each of your answers to 2 decimal places.
    Source S.S. df M.S. F
    Treatment
    Error
    Total
  3. Compute the p-value. Provide the name of the distribution and the parameters used to compute the p-value. Then enter your answer rounded to 4 decimal places.


  4. Interpret the results of the significance test. Is this result statistically significant? Is this result important from a practical perspective?

In: Statistics and Probability

Background: Anorexia is well known to be difficult to treat. The data set provided below contains...

Background: Anorexia is well known to be difficult to treat. The data set provided below contains data on the weight gain for three groups of young female anorexia patients. These groups include a control group, a group receiving cognitive behavioral therapy and a group receiving family therapy. Source: Hand, D. J., Daly, F., McConway, K., Lunn, D. and Ostrowski, E. eds (1993) A Handbook of Small Data Sets. Chapman & Hall, Data set 285 (p. 229).

Directions: Click on the Data button below to display the data. Copy the data into a statistical software package and click the Data button a second time to hide it. Then perform an analysis of variance (ANOVA) to determine whether or not the differences in weight gain between the treatment groups is statistically significant.

Data

Control CBT Family
-0.5 1.7 11.4
-9.3 0.7 11
-5.4 -0.1 5.5
12.3 -0.7 9.4
-2 -3.5 13.6
-10.2 14.9 -2.9
-12.2 3.5 -0.1
11.6 17.1 7.4
-7.1 -7.6 21.5
6.2 1.6 -5.3
-0.2 11.7 -3.8
-9.2 6.1 13.4
8.3 1.1 13.1
3.3 -4 9
11.3 20.9 3.9
0 -9.1 5.7
-1 2.1 10.7
-10.6 -1.4
-4.6 1.4
-6.7 -0.3
2.8 -3.7
0.3 -0.8
1.8 2.4
3.7 12.6
15.9 1.9
-10.2 3.9
0.1
15.4
-0.7
  1. State the null and alternative hypotheses.


  2. Compute the test statistic. Document how SSTr and SSE were computed. Use 4 decimal places for the sample means, sample standard deviations and the grand mean and round your answers for SSTr and SSE to 2 decimal places

    Use the values for SSTr and SSE to complete the following ANOVA table. Round each of your answers to 2 decimal places.

    Source S.S. df M.S. F
    Treatment
    Error
    Total
  3. Compute the p-value. Provide the name of the distribution and the parameters used to compute the p-value. Then enter your answer rounded to 4 decimal places.


  4. Interpret the results of the significance test. Is this result statistically significant? Is this result important from a practical perspective?

In: Statistics and Probability

Problem 8-12 (Algorithmic) Many forecasting models use parameters that are estimated using nonlinear optimization. The basic...

Problem 8-12 (Algorithmic)

Many forecasting models use parameters that are estimated using nonlinear optimization. The basic exponential smoothing model for forecasting sales is

Ft + 1 = αYt + (1 – α)Ft

where

Ft + 1   =   forecast of sales for period t + 1
Yt   =   actual value of sales for period t
Ft   =   forecast of sales for period t
α   =   smoothing constant 0 ≤ α ≤ 1

This model is used recursively; the forecast for time period t + 1 is based on the forecast for period t, Ft; the observed value of sales in period t, Yt and the smoothing parameter α. The use of this model to forecast sales for 12 months is illustrated in the table below with the smoothing constant α = 0.3. The forecast errors, Yt - Ft, are calculated in the fourth column. The value of α is often chosen by minimizing the sum of squared forecast errors, commonly referred to as the mean squared error (MSE). The last column of Table shows the square of the forecast error and the sum of squared forecast errors.

EXPONENTAL SMOOTHING MODEL FOR α=0.3
Week
()		 Observed Value
()		 Forecast Forecast Error
()		 Squared Forecast Error
1 16 16.00 0.00 0.00
2 20 16.00 4.00 16.00
3 18 17.20 0.80 0.64
4 24 17.44 6.56 43.03
5 21 19.41 1.59 2.53
6 16 19.89 -3.89 15.13
7 19 18.72 0.28 0.08
8 21 18.80 2.20 4.84
9 24 19.46 4.54 20.61
10 22 20.82 1.18 1.39
11 12 21.17 -9.17 84.09
12 19 18.42 0.58 0.34
SUM=188.68

In using exponential smoothing models, we try to choose the value of α that provides the best forecasts. Build an Excel Solver or LINGO optimization model that will find the smoothing parameter, α, that minimizes the sum of squared forecast errors. You may find it easiest to put table into an Excel spreadsheet and then use Solver to find the optimal value of α. If required, round your answer for α to three decimal places and the answer for the resulting sum of squared errors to two decimal places.

The optimal value of α is  and the resulting sum of squared errors is .

In: Math

Use the following to answer the next six questions MADONNA, INC. Unadjusted Trial Balance December 31,...

Use the following to answer the next six questions
MADONNA, INC.
Unadjusted Trial Balance
December 31, 2012
DR CR
Cash $ 51,000   
Equipment 38,000   
Retained Earnings $ 4,000
Accounts Payable 6,000
Unearned Fee Revenue 8,000
Accumulated Depreciation-Equipment 1,800
Accounts Receivable 1,500   
Supplies 950   
Salaries Expense 6,700   
Common StockInsurance Expense 500 61,050
Fee RevenueRent Expense 4,200 30,000
Notes Receivable 8,000   
$ 110,850 $ 110,850
1. On July 1, 2012, Madonna paid the landlord $4,200 for 10 months rent in advance. The adjusting entry at December 31, 2012 would include:
A. debit to Prepaid Rent for $2,520
B. credit to Rent Expense for $1,680
C. credit to Rent Expense for $2,520
D. debit to Rent Expense for $2,520
E. none of the above
2. On October 1, 2012, Madonna received $8,000 in advance for fees to be earned evenly over five months beginning on that date. The required adjusting journal entry at December 31, 2012 would include a:
A. debit to Fee Revenue for $3,200
B. credit to Unearned Fee Revenue for $4,800
C. credit to Fee Revenue for $3,200
D. credit to Fee Revenue for $4,800
E. none of the above
3. The Notes Receivable represent a loan given to a supplier for $8,000 on December 1, 2012. The loan carries a 12 percent interest rate and has a term of 180 days. The adjusting entry on December 31, 2012 will include:
A. A debit to Interest Expense for $80
B. A debit to Interest Receivable for $80
C. A credit to Interest Payable for $480
D. A debit to Notes Receivable for $480
E. none of the above
4. At December 31, 2012 there was $320 of supplies on hand. The adjusting entry would include a:
A. credit to Supplies Expense of $630
B. debit to Supplies of $320
C. debit to Supplies Expense of $630
D. debit to Supplies Expense of $320
E. None of the above
5. The Equipment was purchased on July 1, 2011. It has a useful life of ten years and an estimated salvage value of $2,000. The adjusting entry at December 31, 2012 would include a:
A. credit to Equipment for $3,600
B. debit to Depreciation Expense –Equipment for $3,800
C. credit to Accumulated Depreciation –Equipment for $3,600
D. debit to Depreciation Expense –Equipment for 5,400
E. none of the above
6. Refer to the previous question. The book value of the Equipment on the December 31, 2012 balance sheet (after adjusting depreciation expense for 2012) is:
A. $ 36,000
B. $ 32,600
C. $ 32,400
D. $ 30,600
E. none of the above

7. The accountant for the Mobe Company made an adjusting entry to record depreciation for the current year twice by mistake. The effect of this error would be:
A. An overstatement of assets offset by an understatement of owner’s equity.
B. An understatement of assets, net income, and owner’s equity.
C. An overstatement of assets and of net income, and an understatement of owner’s equity.
D. An overstatement of net income and an understatement of assets.
E. None of the above.
8. The Sweeney Theater offered books of theater tickets to its patrons at $30 per book. Each book contained a certain number of tickets to future performances. During the current period 1,000 books were sold for $30,000, and this amount was credited to a temporary account. At the end of the period it was determined that $17,000 worth of book tickets had been used by customers attending performances. The appropriate adjusting entry at the end of the period would be:
A. Debit Ticket Revenue $17,000 and credit Unearned Ticket Revenue $17,000.
B. Debit Unearned Ticket Revenue $13,000 and credit Ticket Revenue $13,000.
C. Debit Unearned Ticket Revenue $17,000 and credit Ticket Revenue $17,000.
D. Debit Ticket Revenue $13,000 and credit Unearned Ticket Revenue $13,000.
E. None of the above.

In: Accounting

For this assignment, you will (1) Find a chart showing the economic growth of an economy...

For this assignment, you will

(1) Find a chart showing the economic growth of an economy in long run.

(2) Briefly discuss the history of economic growth of that economy.

(3) Finally talk about the factors driving economic growth.

Please find below the sample assignment.

Hong Kong GDP per capita (1961 - 2018)

In general, we observed the rising trend of GDP per capita of Hong Kong from 1961 to 2018. Modern history of economic growth of Hong Kong can be broadly divided into 3 phases.

1940s to early 1990s - Rapid industrialization

industrialization accelerated after 1945 with the inflow of money from Mainland China. Immigrants from Mainland China developed textile industry of Hong Kong. Hong Kong’s industry was founded in the textile sector in the 1950s and gradually diversified to clothing, electronics, plastics and other labor-intensive production mainly for exports.

Textile sector was the prominent industry of Hong Kong in 1950s

Early 1990s to early 2000s – Surge in service sector and reintegration into Mainland China

Manufacturing moved out of Hong Kong during the 1980s and 1990s, there was a surge in the service sector. Hong Kong’s economy transformed from manufacturing to services. Furthermore, Hong Kong’s integration with the mainland accelerated and Hong Kong became the main provider of commercial and financial services. From 1978 to 1997, trades between Hong Kong and the PRC grew at an average rate of 28% per annum.

Handover of Hong Kong from UK to China in 1997. This highlights the integration of the economy of Hong Kong with Mainland China.

Early 2000s to 2010s - Deepened reliance on China

Over the recent 20 years, Hong Kong economy has transformed from enhanced integration with China to deepened reliance on China. The four key industries, including financial services, tourism, trading and logistics heavily depend on the businesses with Mainland China. Hong Kong can maintain its economic growth during the global financial crisis primarily due to the help from Mainland China.

Is the economy of Hong Kong nowadays too reliant on the help from Mainland China?

Key factors driving economic growth:

Institutions: Low taxes, lax employment laws, absence of government debt, and free trade are all pillars of the Hong Kong experience of economic development.

Education: The government also pursued an ambitious public education program. By 1966, 99.8% of school-age children were attending primary school, and free universal primary school was provided after 1971. Secondary school provision was expanded in the 1970s, and from 1978 the government offered compulsory free education for all children up to the age of 15.

In: Economics

In the probability distribution to the​ right, the random variable X represents the number of hits...

In the probability distribution to the​ right, the random variable X represents the number of hits a baseball player obtained in a game over the course of a season. Complete parts​ (a) through​ (f) below. x ​P(x) 0 0.1685 1 0.3358 2 0.2828 3 0.1501 4 0.0374 5 0.0254 ​

(a) Verify that this is a discrete probability distribution. This is a discrete probability distribution because all of the probabilities are at least one of the probabilities is all of the probabilities are between 0 and 1​, ​inclusive, and the sum mean sum product of the probabilities is 1. ​(Type whole numbers. Use ascending​ order.)

​(b) Draw a graph of the probability distribution. Describe the shape of the distribution. Graph the probability distribution. Choose the correct graph below. A. 0 1 2 3 4 5 0 0.1 0.2 0.3 0.4 Number of Hits Probability The graph of a probability distribution has a horizontal x-axis labeled "Number of Hits" from 0 to 5 in intervals of 1 and a vertical y-axis labeled "Probability" from 0 to 0.4 in intervals of 0.05. Vertical line segments are centered on each of the horizontal axis tick marks. The approximate heights of the vertical line segments are as follows, with the horizontal coordinate listed first and the line height listed second: 0, 0.15; 1, 0.04; 2, 0.03; 3, 0.17; 4, 0.34; 5, 0.28. B. 0 1 2 3 4 5 0 0.1 0.2 0.3 0.4 Number of Hits Probability The graph of a probability distribution has a horizontal x-axis labeled "Number of Hits" from 0 to 5 in intervals of 1 and a vertical y-axis labeled "Probability" from 0 to 0.4 in intervals of 0.05. Vertical line segments are centered on each of the horizontal axis tick marks. The approximate heights of the vertical line segments are as follows, with the horizontal coordinate listed first and the line height listed second: 0, 0.34; 1, 0.15; 2, 0.03; 3, 0.17; 4, 0.28; 5, 0.04. C. 0 1 2 3 4 5 0 0.1 0.2 0.3 0.4 Number of Hits Probability The graph of a probability distribution has a horizontal x-axis labeled "Number of Hits" from 0 to 5 in intervals of 1 and a vertical y-axis labeled "Probability" from 0 to 0.4 in intervals of 0.05. Vertical line segments are centered on each of the horizontal axis tick marks. The approximate heights of the vertical line segments are as follows, with the horizontal coordinate listed first and the line height listed second: 0, 0.03; 1, 0.04; 2, 0.15; 3, 0.28; 4, 0.34; 5, 0.17. D. 0 1 2 3 4 5 0 0.1 0.2 0.3 0.4 Number of Hits Probability The graph of a probability distribution has a horizontal x-axis labeled "Number of Hits" from 0 to 5 in intervals of 1 and a vertical y-axis labeled "Probability" from 0 to 0.4 in intervals of 0.05. Vertical line segments are centered on each of the horizontal axis tick marks. The approximate heights of the vertical line segments are as follows, with the horizontal coordinate listed first and the line height listed second: 0, 0.17; 1, 0.34; 2, 0.28; 3, 0.15; 4, 0.04; 5, 0.03. Describe the shape of the distribution. The distribution has one mode has one mode is multimodal is uniform is bimodal and is skewed right. roughly symmetric. skewed right. skewed left.

​(c) Compute and interpret the mean of the random variable X. mu Subscript xequals 0.1666 hits ​(Type an integer or a decimal. Do not​ round.) Which of the following interpretations of the mean is​ correct? A. In any number of​ games, one would expect the mean number of hits per game to be the mean of the random variable. B. Over the course of many​ games, one would expect the mean number of hits per game to be the mean of the random variable. C. The observed number of hits per game will be less than the mean number of hits per game for most games. D. The observed number of hits per game will be equal to the mean number of hits per game for most games. ​

Need help with (c) through (f) please!

(d) Compute the standard deviation of the random variable X. sigma Subscript xequals nothing hits ​(Round to three decimal places as​ needed.)

​(e) What is the probability that in a randomly selected​ game, the player got 2​ hits? nothing ​(Type an integer or a decimal. Do not​ round.)

​(f) What is the probability that in a randomly selected​ game, the player got more than 1​ hit? nothing ​(Type an integer or a decimal. Do not​ round.)

In: Statistics and Probability

In an article in the Journal of Marketing, Bayus studied the differences between "early replacement buyers”...

In an article in the Journal of Marketing, Bayus studied the differences between "early replacement buyers” and "late replacement buyers” in making consumer durable good replacement purchases. Early replacement buyers are consumers who replace a product during the early part of its lifetime, while late replacement buyers make replacement purchases late in the product’s lifetime. In particular, Bayus studied automobile replacement purchases. Consumers who traded in cars with ages of zero to three years and mileages of no more than 35,000 miles were classified as early replacement buyers. Consumers who traded in cars with ages of seven or more years and mileages of more than 73,000 miles were classified as late replacement buyers. Bayus compared the two groups of buyers with respect to demographic variables such as income, education, age, and so forth. He also compared the two groups with respect to the amount of search activity in the replacement purchase process. Variables compared included the number of dealers visited, the time spent gathering information, and the time spent visiting dealers.

(a) Suppose that a random sample of 807 early replacement buyers yields a mean number of dealers visited of x⎯⎯x¯ = 3.3, and assume that σ equals .79. Calculate a 99 percent confidence interval for the population mean number of dealers visited by early replacement buyers. (Round your answers to 3 decimal places.)

The 99 percent confidence interval is            [ , ].

(b) Suppose that a random sample of 493 late replacement buyers yields a mean number of dealers visited of x⎯⎯x¯ = 4.2, and assume that σ equals .66. Calculate a 99 percent confidence interval for the population mean number of dealers visited by late replacement buyers. (Round your answers to 3 decimal places.)

The 99 percent confidence interval is            [ , ].

(c) Use the confidence intervals you computed in parts a and b to compare the mean number of dealers visited by early replacement buyers with the mean number of dealers visited by late replacement buyers. How do the means compare?

Mean number of dealers visited by late replacement buyers appears to be ( lower or higher?)

In: Advanced Math