1B.Write on the differences between the following terms

QUESTION PART A: Many investors and financial analysts believe the Dow Jones Industrial Average (DJIA) gives a good barometer of the overall stock market. On January 31, 2006, 9 of the 30 stocks making up the DJIA increased in price (The Wall Street Journal, February 1, 2006). On the basis of this fact, a financial analyst claims we can assume that 30% of the stocks traded on the New York Stock Exchange (NYSE) went up the same day.

A sample of 61 stocks traded on the NYSE that day showed that 6 went up.

You are conducting a study to see if the proportion of stocks that went up is is significantly less than 0.3. You use a significance level of α=0.01α=0.01.

What is the test statistic for this sample? (Report answer accurate to three decimal places.)
test statistic =

What is the p-value for this sample? (Report answer accurate to four decimal places.)
p-value =

The p-value is...

• less than (or equal to) αα
• greater than αα

This test statistic leads to a decision to...

• reject the null
• accept the null
• fail to reject the null

As such, the final conclusion is that...

• There is sufficient evidence to warrant rejection of the claim that the proportion of stocks that went up is is less than 0.3.
• There is not sufficient evidence to warrant rejection of the claim that the proportion of stocks that went up is is less than 0.3.
• The sample data support the claim that the proportion of stocks that went up is is less than 0.3.
• There is not sufficient sample evidence to support the claim that the proportion of stocks that went up is is less than 0.3.

QUESTION PART B: You want to obtain a sample to estimate a population proportion. At this point in time, you have no reasonable estimate for the population proportion. You would like to be 99.9% confident that you esimate is within 2.5% of the true population proportion. How large of a sample size is required?

n =



Do not round mid-calculation. However, use a critical value accurate to three decimal places.

(I have posted this three different times and it has been wrong, so please!! it will help me a lot)

In recent times, with mortgage rates at low levels, financial institutions have had to provide more customer convenience. One of the innovations offered by Coastal National Bank and Trust is online entry of mortgage applications. Listed below are the times, in minutes, for eight customers to complete the application process for a 15-year fixed-rate mortgage and the times for nine customers to complete an application for a 30-year fixed-rate mortgage.

State the decision rule. Use the 0.05 significance level. (Negative amounts should be indicated by a minus sign. Round your answer to 3 decimal places.)

H₀: The distributions are the same.
H₁: The 30-year distribution is smaller or to the left.

Complete the following table. (Round your answer to 1 decimal places.)

What is the Wilcoxon rank-sum test value, at the 0.05 significance level? (Round your answer to 2 decimal places.)

At the 0.05 significance level, is it reasonable to conclude that it takes less time for those customers applying for the 30-year fixed-rate mortgage?

A statistician employed by a consumer testing organization reports that at 95% confidence he has determined that the true average content of the Uncola soft drinks is between 11.7 to 12.3 ounces. He further reports that his sample revealed an average content of 12 ounces, but he forgot to report the size of the sample he had selected. Assuming the standard deviation of the population is 1.28, determine the size of the sample. #9b) About 28% of private companies are owned by women (Cincinnati Enquirer, January 26, 2006). Answer the following questions based on a sample of 240 private companies. #9bi). Show the sampling distribution of (), the sample proportion of companies that are owned by women. #9bii). What is the probability the sample proportion will be within ±.04 of the population proportion?

4. The following Treasury bond quote appeared in The Wall Street Journal on May 11, 2004:

9.125               May 09            100.09375       100.12500       …         ‐2.15

Why would anyone buy this Treasury bond with a negative yield to maturity? How is this possible?

What does article mean?

Revenue Recognition

Revenue recognition for multiple-element arrangements requires judgment to determine if multiple elements exist, whether elements can be accounted for as separate units of accounting, and if so, the fair value for each of the elements.

Judgment is also required to assess whether future releases of certain software represent new products or upgrades and enhancements to existing products. Certain volume licensing arrangements include a perpetual license for current products combined with rights to receive unspecified future versions of software products and are accounted for as subscriptions, with billings recorded as unearned revenue and recognized as revenue ratably over the coverage period.

Software updates are evaluated on a case-by-case basis to determine whether they meet the definition of an upgrade, which may require revenue to be deferred and recognized when the upgrade is delivered. If it is determined that implied post-contract customer support (“PCS”) is being provided, revenue from the arrangement is deferred and recognized over the implied PCS term. If updates are determined to not meet the definition of an upgrade, revenue is generally recognized as products are shipped or made available.

Microsoft enters into arrangements that can include various combinations of software, services, and hardware. Where elements are delivered over different periods of time, and when allowed under U.S. GAAP, revenue is allocated to the respective elements based on their relative selling prices at the inception of the arrangement, and revenue is recognized as each element is delivered. We use a hierarchy to determine the fair value to be used for allocating revenue to elements: (i) vendor-specific objective evidence of fair value (“VSOE”), (ii) third-party evidence, and (iii) best estimate of selling price (“ESP”). For software elements, we follow the industry-specific software guidance which only allows for the use of VSOE in establishing fair value. Generally, VSOE is the price charged when the deliverable is sold separately or the price established by management for a product that is not yet sold if it is probable that the price will not change before introduction into the marketplace. ESPs are established as best estimates of what the selling prices would be if the deliverables were sold regularly on a stand-alone basis. Our process for determining ESPs requires judgment and considers multiple factors that may vary over time depending upon the unique facts and circumstances related to each deliverable.

Customers purchasing a Windows 10 license will receive unspecified updates and upgrades over the life of their Windows 10 device at no additional cost. As these updates and upgrades will not be sold on a stand-alone basis, we are unable to establish VSOE. Accordingly, revenue from licenses of Windows 10 is recognized ratably over the estimated life of the related device, which ranges between two to four years.

The new standard related to revenue recognition will have a material impact on our consolidated financial statements. See Note 1 – Accounting Policies in the Notes to Financial Statements (Part II, Item 8 of this Form 10-K) for further discussion

Use the following information to work Problem1 a) and b).

Why the tepid response to higher gasoline prices?

Most studies report that when U.S. gas prices rise by 10 percent, the quantity purchased falls by 1 to 2 percent. In September 2005, the retail gasoline price was $2.90 a gallon, about $1.00 higher than in September 2004, but purchases of gasoline fell by only 3.5 percent.

Source: The New York Times, October 13, 2005

1.   (2 points) Calculate the price elasticity of demand for gasoline implied by what most studies have found.

2.   (2 points) Compare the elasticity implied by the data for the period from September 2004 to September 2005 with that implied by most studies. What might explain the difference?

A farmer's marketing cooperative recorded the volume of wheat harvested by its members from 1991-2004. The cooperative is interested in detecting the long-term trend of the amount of wheat harvested. The data collected is shown in the table.

                                     Wheat Harvested by Coop. Member

            Year      Time          (y, in thousands of bushels)    

            1991         1                               75

            1992         2                               78

            1993         3                               82

            1994         4                               82

            1995         5                               84

            1996         6                               85

            1997         7                               87

            1998         8                               91

            1999         9                               92

            2000        10                              92

            2001        11                              93

            2002        12                              96

            2003        13                            101

            2004        14                            102                       

Find the least squares prediction equation for the model. Use excel to conduct data analysis. Provide detailed interpretation of the results.

R code:

## 2. __Basic dplyr exercises__

## Install the package `fueleconomy` and load the dataset `vehicles`. Answer the following questions.
install.packages("fueleconomy")
library(fueleconomy)
library(dplyr)
library(tidyr)
data(vehicles)

e. Finally, for the years 1994, 1999, 2004, 2009, and 2014, find the average city mpg of midsize cars for each manufacturer for each year. Use tidyr to transform the resulting output so each manufacturer has one row, and five columns (a column for each year). I have included sample output for the first two rows.

Output should like :

# make 1994 1999 2004 2009 2014
# 1 Acura NA 16.50000 17.33333 17.00000 20.60000
# 2 Audi NA 15.25000 16.20000 15.83333 19.08333