Project K requires an initial investment of $450,000, is expected to last for 7 years, and is expected to produce after-tax net cash flows of $92,000 per year. Project L requires $3000 initial investment and produces a net cash flow of $800 per year. The discount rate for both projects is 8%.

a) What is the NPV of each project?

b) What is the Profitability Index of each project?

c) Which one will you choose?

The table below is for questions 1-3.

In one day, one unit of labor can produce the following in two different countries;

                                      Fredonia                                      Sylvania

                          TVs           2                                                  1

                          Radios      10                                                 8

1. The country of ___________ has the absolute advantage in the production of radios.

2. The country of ___________ has the comparative advantage in the production of radios.

3. If the two countries trade at a price of 6 radios for 1 TV, with trade, for one day’s work, a worker in Fredonia can have 1 TV or _________ radios, while a worker in Sylvania can have 8 radios or _______________ TVs.

16. A developer of video game software has seven proposals for new games. Unfortunately,
the company cannot develop all the proposals because its budget for new projects
is limited to $950,000, and it has only 20 programmers to assign to new projects.
The financial requirements, returns, and the number of programmers required by each project are summarized in the following table. Projects 2 and 6 require specialized
programming knowledge that only one of the programmers has. Both of these
projects cannot be selected because the programmer with the necessary skills can be
assigned to only one of the projects. (Note: All dollar amounts represent thousands.)
Project Programmers Required Capital Required Estimated NPV
1 7 $250 $650
2 6 $175 $550
3 9 $300 $600
4 5 $150 $450
5 6 $145 $375
6 4 $160 $525
7 8 $325 $750
a. Formulate an ILP model for this problem.
b. Create a spreadsheet model for this problem and solve it.
c. What is the optimal solution?

Hadoopis one of the feasible and affordable solutions for big data analytics. Its success is on the numerous add-on products in its 4 functional areas. Describe what the following add-onproducts are and how it can help in big data analytics with around 50 to 100 words each.

1) Pig

2) Spark

3) Storm

4) Atlas

5) Flume

6) Solr

7) HBase

8) Oozie

Verizon Wireless records as a measure of productivity the number of weekly cell phone activations each of its retail employees achieves. The data below show a sample of 25 employees, for each employee giving the number of activations in the sampled week, the number of years of experience on the job, the gender (0-Male; 1-Female), the employee performance rating on a scale of 1-100, and the employee's age.

(Please help me solve this with MS EXCEL)

a. Estimate the mean number of activations in a week for a 30 year old male employee who has 5 years of experience and a performance rating of 90.

b. interpret the coefficient for the Gender variable:

c. What are the null and alternate hypotheses that would be used to test if the model is significant overall. (Express symbolically if possible)

d. What is the p-value that would be used for the hypothesis test corresponding to the hypotheses in part c?

e. What are the null and alternate hypotheses that would be used to determine if age is significantly related to the number of activations? (Express symbolically if possible)

f. Determine if age is significantly related to number of activations. Use α = 0.05. Give complete conclusions.

Tumor counts: A cancer laboratory is estimating the rate of tumorigenesis in two strains of mice, A and B. They have tumor count data for 10 mice in strain A and 13 mice in strain B. Type A mice have been well studied, and information from other laboratories suggest that Type A mice have tumor counts that are approximately Poisson-distributed with a mean of 12. Tumor count rates for Type B mice are unknown, but type B mice are related to type A mice. The observed tumor counts are yA = (12, 9, 12, 14, 13, 13, 15, 8, 15, 6) yB = (11, 11, 10, 9, 9, 8, 7, 10, 6, 8, 8, 9, 7). 1). (b) Compute and plot the posterior expectation of θB under the prior distribution θB ∼ gamma(12 × n0, n0) for each value of n0 = 1, 2, . . . , 50. Describe what sort of prior beliefs about θB would be necessary in order for the posterior expectation of θB to be close to that of θA. (c) Should knowledge about population A tell us anything about population B? Discuss whether or not it makes senes to have independent priors p(θA, θB) = p(θA) × p(θB).

1.Charter Company, which uses the perpetual inventory method, purchases different letters for resale. Charter had a beginning inventory comprised of ten units at $3 per unit. The company purchased four units at $5 per unit in February, sold seven units in October, and purchased four units at $6 per unit in December. If Charter Company uses the LIFO method, what is the cost of its ending inventory?

2. Delta Diamonds uses a periodic inventory system. The company had five one-carat diamonds available for sale this year: one was purchased on June 1 for $700, two were purchased on July 9 for $800 each, and two were purchased on September 23 for $850 each. On December 24, it sold one of the diamonds that was purchased on July 9. Using the specific identification method, its ending inventory (after the December 24 sale) equals:

3. Alphabet Company, which uses the periodic inventory method, purchases different letters for resale. Alphabet had no beginning inventory. It purchased A thru G in January at $8.00 per letter. In February, it purchased H thru L at $10.00 per letter. It purchased M thru R in March at $11.00 per letter. It sold A, D, E, H, J and N in October. There were no additional purchases or sales during the remainder of the year. If Alphabet Company uses the weighted average method, what is the cost of its ending inventory?

4. Sugar, Inc. sells $569,300 of goods during the year that have a cost of $448,600. Inventory was $30,283 at the beginning of the year and $34,538 at the end of the year. How long on average does it take to sell something from inventory after it is purchased?

5.King Costume uses a periodic inventory system. The company started the month with 8 masks in its beginning inventory that cost $11 each. During the month, King Costume purchased 50 additional masks for $13 each. At the end of the month, King counted its inventory and found that 4 masks remained unsold. Using the LIFO method, its cost of goods sold for the month is:

Find the mean, median, and mode of the following set of data. (Enter solutions for mode from smallest to largest. If there are any unused answer boxes, enter NONE in the last boxes.) (a) 6 6 7 8 9 12 Mean Median Mode Mode (b) 6 6 7 8 9 108 Mean Median Mode Mode

1. At the 5% level of significance, is there a relationship in the population between the three predictors taken as a group and the annual salary for teachers?

Select one:

a. Yes

b.Cannot be determined from the data

c.No

d.50/50 chance that there is.

Which predictor(s), if any, would you remove because it does not contribute to the regression models, using the 90% confidence level, α = .10?

Select one:

a.Sex and Experience

b. None

c. Education

d. Experience

Using R Language

The code provided below uses a for loop to simulate conducting 10,000 polls of 8 people in which each person has 58% probability of being a supporter of the Democratic candidate and a 42% probability of being a supporter of the Republican. The way the loop works is it runs through the code inside the loop 10,000 times, but changing the value of i with each iteration (i is 1 in the first iteration, 10,000 in the last).

# Define a vector of integers that has 10,000 elements. poll_sims = vector(length = 10000, mode = "integer") # for loop to simulate 10,000 polls for (i in 1:10000) { # Do a poll of 8 people in which each person has a 58% chance of supporting the # Democratic candidate and 42% chance of supporting the Republican. poll = sample(c("Democrat", "Republican"), size = 8, replace = T, prob = c(.58, .42)) # Count the number of people who support the Democrat and store the result in the # poll_sims vector as the ith result. poll_sims[i] = sum(poll == "Democrat") } 2 # Visualise the poll_sims vector using basic R plot(factor(poll_sims)) # Visualise the poll_sims vector using tidyverse library(tidyverse) qplot(factor(poll_sims)) + geom_bar()

1. Run this code on your own and find the fraction of the simulations in which less than half the people (3 or fewer) support the Democratic candidate. Compare this result to your answer in Question 5 of the previous section.

2. Change the code to simulate 10,000 polls of 100 people (rather than 10,000 polls of 8). Find the fraction of simulations in which less than half the people support the Democratic candidate. In other words, use the simulations to approximate the likelihood that a poll of 100 people will incorrectly guess the winner of the election.

3. Graph the simulations so you can visualize the distribution.

4. Change the code again to simulate 10,000 polls of 1,000 people. Find the fraction of simulations in which between 55% and 61% of the people support the Democratic candidate. In other words, use the simulations to approximate the likelihood that a poll of 1,000 people will be off from the true probability by 3% or less.