Question 2: The Journal of the American Medical Association reported in 2002 on a study of 1,100 airline passengers who flew from San Francisco to Denver. 515 of these passengers traveled on planes where air was re-circulated, the remaining 585 traveled on planes that did not recirculate air. Of those that did travel on planes where the air was recirculated, 110 reported post-flight respiratory problems. Of those on planes that did not recirculate the air, 108 reported post-flight respiratory problems.

1. (a) Is there a difference in the proportion of passengers who experience post-flight respiratory problems between planes who re-circulate air and planes that do not? State the statistical hypotheses.

2. (b) Carry out the statistical test at a level of significance of 5%.

3. (c) What can you conclude?

4. (d) Interpret the meaning of the P -value you computed, in the context of the data.
   Should you reject the null hypothesis in part (a), compute the 95% confidence interval for the difference in the proportion of passengers experiencing post-flight respiratory problems in planes that recirculate air and planes that do not, pReCirculate − pNoRecirculate.

In January 2004, Mr. Pandit decided to buy a residential property and rent to various tenants. On 1st January 2004, he borrowed Rs. 30 Lakhs from a housing bank on a condition of repaying the loan in 10 annual installments with an interest @10% per annum. He put in his own savings of Rs. 15 Lakhs and bought a property having 5 flats in a fast developing locality. The cost of the property was Rs. 30 Lakhs comprising land valued at Rs. 15 lakhs and building values at Rs. 15 lakhs.

The entire year of 2004 was spent in repairing and repainting the property. The cost of one-time repairs was Rs. 5 lakhs and that of repainting, which was completed on 31st December 2004, was Rs. 1.2 lakh. Mr. Pandit expected that this paint would last for 3 years before it was repainted. The life of the property after repairs was expected to be 20 years. Mr. Pandit was informed that cost of repairs and first year's interest on the bank loan had to be added to the cost of building as it were incurred in bringing asset to a position of generating revenue.On December 31st of 2004, Mr. Pandit paid the first installment of loan together with interest @10%.

The flats were ready to let out on 1st January 2005. 5 tenants signed the agreement and paid interest free deposit equivalent to 10 months rent. The monthly rent of each flat was Rs. 8000. The three tenants paid their rent regularly on the last day of the month during 2005. One tenant Mr. Khanna, had indicated that he would vacate the flat on 31st december 2005 and had not paid his rent for November and december, requesting Mr. Pandit to adjust the same against his deposit. Though Mr. Khanna vacated the flat on the decided date, Mr. Pandit had yet to pay his balance deposit amount. Another tenant, Mr. Khan went abroad in December 2005 but had promised to pay the rent on return. Mr. Pandit had already found a tenant for the flat vacated by Mr. Khanna and the new tenant paid a deposit of Rs. 80000 on 31st December 2005. Mr. Pandit paid the second installment of loan together with interest on 31st December 2005. Mr. Pandit had made the following payments during 2005:

Taxes - Rs 20000

Electricity - Rs 10000

Telephone - Rs 10000

Fire Insurance was taken on January 1, 2005 for 4 years - premium Rs 60000

The closing cash/bank balance was Rs. 546000 on 31st December 2005.

******

Prepare the income statement and balance sheet of Samavya Building as on 31st December 2005 and show each step in detail.

In this quiz, use the following touchdown data for Tom Brady:

2 (a) Find the correlation coefficient, accurate to four significant figures, between the number of touchdowns, t, and the number of passing yards, y.

(b) Find the equation of the regression line, y = n*t + k, giving the line of best fit for the number of passing yards, y, as a function of the number of touchdowns, t. What is the slope, n, of this line, accurate to two decimal places?

(c) Find the equation of the regression line, y = n*t + k, giving the line of best fit for the number of passing yards, y, as a function of the number of touchdowns, t. What is the value of k for this line, accurate to two decimal places?

(d)  Use the regression line you found in 2 (b) and 2 (c) to find the number of touchdowns expected if Brady passes for 4000 yards.Use the values stored in your calculator or spreadsheet, without rounding them, and give an answer with four significant figures.

(e) Use the regression line you found in 2 (b) and 2 (c) to find the number of passing yards expected if Brady throws 45 touchdowns.Use the values stored in your calculator or spreadsheet, without rounding them, and give an answer with two decimal places.

In this quiz, use the following touchdown data for Tom Brady:

2 (a) Find the correlation coefficient, accurate to four significant figures, between the number of touchdowns, t, and the number of passing yards, y.

(b) Find the equation of the regression line, y = n*t + k, giving the line of best fit for the number of passing yards, y, as a function of the number of touchdowns, t. What is the slope, n, of this line, accurate to two decimal places?

(c) Find the equation of the regression line, y = n*t + k, giving the line of best fit for the number of passing yards, y, as a function of the number of touchdowns, t. What is the value of k for this line, accurate to two decimal places?

(d)  Use the regression line you found in 2 (b) and 2 (c) to find the number of touchdowns expected if Brady passes for 4000 yards.Use the values stored in your calculator or spreadsheet, without rounding them, and give an answer with four significant figures.

(e) Use the regression line you found in 2 (b) and 2 (c) to find the number of passing yards expected if Brady throws 45 touchdowns.Use the values stored in your calculator or spreadsheet, without rounding them, and give an answer with two decimal places.

Use the data and Excel to answer this question. It contains the United States Census Bureau’s estimates for World Population from 1950 to 2014. You will find a column of dates and a column of data on the World Population for these years. Generate the time variable t. Then run a regression with the Population data as a dependent variable and time as the dependent variable. Have Excel report the residuals.

(a) Based on the ANOVA table and t-statistics, does the regression appear significant?

(b) Calculate the Durbin-Watson Test statistic. Is there a serial correlation problem with the data? Explain.

(d) What affect might your answer in part (b) have on your conclusions in part (a)?

Can you please give detailed steps to do on excel?

Program Requirements:

Write a C++ program according to the following requirements:

1.   Open the data file Electricity.txt and read each column into an array (8 arrays total).

2.   Also create 2 arrays for the following:

• Total Fossil Fuel Energy (sum of all fossil fuels)
• Total Renewable Energy (sum of all renewable sources)

Electricity.txt:

Net generation United States all sectors monthly
https://www.eia.gov/electricity/data/browser/
Source: U.S. Energy Information Administration
All values in thousands of megawatthours
Year   all fuels   coal       natural gas   nuclear       hydroelectric   wind       solar
2018   347576.0   95496.8       122393.9   67257.0       24377.0       22720.8       7780.4
2017   336189.2   100486.3   108034.6   67079.1       25027.8       21191.9       6439.7
2016   339722.9   103262.4   114858.9   67141.2       22317.7       18916.0       4572.2
2015   339800.1   112699.8   111123.5   66431.5       20756.7       15893.2       3252.7
2014   341133.8   131809.2   93884.1       66430.5       21613.9       15137.9       2410.3
2013   338830.3   131759.6   93736.3       65751.4       22380.4       13986.6  
2012   337313.8   126170.2   102157.8   64110.9       23020.0       11735.1  
2011   341678.4   144452.5   84474.1       65850.4       26612.9       10014.7  
2010   343755.0   153940.9   82308.1       67247.4       21683.6       7887.7  
2009   329194.2   146325.4   76748.2       66571.2       22787.1       6157.2  
2008   343282.3   165483.4   73581.7       67184.0       21235.9       4613.6  
2007   346395.4   168038.0   74715.8       67202.1       20625.8       2870.8  
2006   338725.2   165875.9   68036.7       65601.6       24103.9       2215.8  
2005   337951.9   167739.4   63413.4       65165.5       22526.8       1484.2  
2004   330879.6   164858.4   59175.0       65710.7       22368.1       1178.6  
2003   323598.8   164478.1   54159.0       63644.4       22983.9       932.3  
2002   321537.7   161094.2   57583.8       65005.3       22027.4       862.9  
2001   311387.0   158663.0   53260.8       64068.9       18080.1       561.4

Williams Act of 1968

Sarbanes - Oxley Act of 2002

Why was the regulation brought into existence?

• What were the main provisions of the regulation? •

Was the regulation successful? •

Provide real-world examples related to this regulation (e.g.: Corporations or Executives found adhering/flouting these regulations)

1. Why does many companies entering international business ignore the element (cost) of doing business overseas?

2. What were some of the reasons interest dropped on freight derivatives in 2002? Had this occurred to a lesser extent at any time previously?

The following are the years that the big market crashes happened since 1900 in US stock market .

1929-1932

1987

2000-2002

2007-2009

2020

What are the economic and political background, triggers, and fundamental reasons of each market crash.

no word limit