E13.17 Contributions Received on Behalf of Others

The United Way receives contributions and distributes them to other NFP organizations. Some of its transactions for the current year are as follows:

1. Donors contribute $5 million, designated to specific unaffiliated NFP organizations. $3 million of this money is distributed according to donor wishes during the current year.

2. Donors contribute $2 million, to be distributed to unaffiliated NFP organizations selected by United Way. United Way distributes $1.8 million of these donations in the current year.

3. Donors contribute $1 million, to be distributed to a specific affiliated organization. United Way distributes $900,000 of these donations in the current year.

Required

Prepare journal entries to record the above activities. If the item affects net assets, identify the category affected.

sketch a graph about the relation between Number of states N(E) and Energy E .

and explain the different between the empty states and the full states

Make a list of all the possible sets of quantum numbers that an electron in an atom can have if n = 4. How many different states with n = 4 are there? Indicate on your list which states are degenerate (i.e. have the same energy as other n = 4 states). Assume that the electron is in a multi-electron atom (i.e. not the Hydrogen atom). Does the total number of states agree with the general rule that the number of states is equal to 2n^2.

Insurance companies know the risk of insurance is greatly reduced if the company insures not just one person, but many people. How does this work? Let x be a random variable representing the expectation of life in years for a 25-year-old male (i.e., number of years until death). Then the mean and standard deviation of x are μ = 48.7 years and σ = 10.3 years (Vital Statistics Section of the Statistical Abstract of the United States, 116th Edition).

Suppose Big Rock Insurance Company has sold life insurance policies to Joel and David. Both are 25 years old, unrelated, live in different states, and have about the same health record. Let x₁ and x₂be random variables representing Joel's and David's life expectancies. It is reasonable to assume x₁ and x₂ are independent.

Joel, x₁: 48.7; σ₁ = 10.3
David, x₂: 48.7; σ₁ = 10.3

If life expectancy can be predicted with more accuracy, Big Rock will have less risk in its insurance business. Risk in this case is measured by σ (larger σ means more risk).

(a) The average life expectancy for Joel and David is W = 0.5x₁ + 0.5x₂. Compute the mean, variance, and standard deviation of W. (Use 2 decimal places.)

(b) Compare the mean life expectancy for a single policy (x₁) with that for two policies (W).

The mean of W is larger.The means are the same.     The mean of W is smaller.

(c) Compare the standard deviation of the life expectancy for a single policy (x₁) with that for two policies (W).

The standard deviation of W is smaller.The standard deviation of W is larger.     The standard deviations are the same.

Insurance companies know the risk of insurance is greatly reduced if the company insures not just one person, but many people. How does this work? Let x be a random variable representing the expectation of life in years for a 25-year-old male (i.e., number of years until death). Then the mean and standard deviation of x are μ = 52.4 years and σ = 12.1 years (Vital Statistics Section of the Statistical Abstract of the United States, 116th Edition).

Suppose Big Rock Insurance Company has sold life insurance policies to Joel and David. Both are 25 years old, unrelated, live in different states, and have about the same health record. Let x1 and x2 be random variables representing Joel's and David's life expectancies. It is reasonable to assume x1 and x2 are independent.

Joel, x1: 52.4; σ1 = 12.1 David, x2: 52.4; σ2 = 12.1

If life expectancy can be predicted with more accuracy, Big Rock will have less risk in its insurance business. Risk in this case is measured by σ (larger σ means more risk). (a) The average life expectancy for Joel and David is W = 0.5x1 + 0.5x2. Compute the mean, variance, and standard deviation of W. (Use 2 decimal places.)

μ

σ2

σ

(b) Compare the mean life expectancy for a single policy (x1) with that for two policies (W).

The mean of W is larger.

The means are the same.

The mean of W is smaller.

(c) Compare the standard deviation of the life expectancy for a single policy (x1) with that for two policies (W).

The standard deviation of W is smaller.

The standard deviations are the same.

The standard deviation of W is larger.

Insurance companies know the risk of insurance is greatly reduced if the company insures not just one person, but many people. How does this work? Let x be a random variable representing the expectation of life in years for a 25-year-old male (i.e., number of years until death). Then the mean and standard deviation of x are μ = 52.5 years and σ = 10.1 years (Vital Statistics Section of the Statistical Abstract of the United States, 116th Edition). Suppose Big Rock Insurance Company has sold life insurance policies to Joel and David. Both are 25 years old, unrelated, live in different states, and have about the same health record. Let x1 and x2 be random variables representing Joel's and David's life expectancies. It is reasonable to assume x1 and x2 are independent.

Joel, x1: 52.5; σ1 = 10.1 David, x2: 52.5; σ1 = 10.1

If life expectancy can be predicted with more accuracy, Big Rock will have less risk in its insurance business. Risk in this case is measured by σ (larger σ means more risk).

(a) The average life expectancy for Joel and David is W = 0.5x1 + 0.5x2. Compute the mean, variance, and standard deviation of W. (Use 2 decimal places.) μ σ2 σ

(b) Compare the mean life expectancy for a single policy (x1) with that for two policies (W). The mean of W is smaller. The mean of W is larger. The means are the same.

(c) Compare the standard deviation of the life expectancy for a single policy (x1) with that for two policies (W). The standard deviation of W is larger. The standard deviation of W is smaller. The standard deviations are the same.

After reading the analysis of your peers, reply to at least to 1 peer by providing a theoretical proof (using your textbook and/or materials posted in Canvas) that would either (1) further cement their argument or (2) negate their argument.

Notably, by mid-May 2020, amid the COVID-19 Pandemic, gas prices fell to its lowest level since 2016, reaching as low as $1.85 per gallon on average in the United States. This reflects demand rather than supply in action. During the pandemic, the governments in different states focused on adopting restrictions affecting the people's movement from one location to another. Gas is for the movement of people. The lockdown rules and restrictions forced people to stay in their homes, thus, creating a historic plunge in demand. The decrease in the quantity demanded forced the prices to drop. Graphically, as the prices decline and quantity demanded decreases, the demand curve shifts to the left, showing such decreases in prices and the quantity demanded. In the stated period, most people in the world were not moving. Gas, of course, is for moving. Most economic analysts did project the demand for gasoline to decrease by about 30 percent, which would be the worst dive ever in humanity's history.

As depicted in the above discussion/illustration, prices affect the quantity demanded. When there is a change in the quantity demanded, suppliers respond by changing the prices. For example, a positive change in the quantity demanded increases the prices of the products or services at the consumers' disposal. On the other hand, a substantial dip in quantity demanded initiates a decrease in the price; thus, the demand curve's essence of shifting to the left. This is what happened to the price of the gas during the mid-May following the government's directives to restrict the movement of the people as a platform to minimize the spread of the virus.

1.As the use of gold as currency became more standardized, what happened to the gold trade?

a.)The dollar's convertibility was suspended.

b.)Banks printed paper money to represent a specific amount of gold in the vault.

c.)Americans lost faith in their currency and hoarded gold.

d.)Gold held little practical value other than as jewelry.

2.What is the central issue that causes bank runs and panics?

a.)Banks withhold deposits from creditors

b.)Banks fail to pay interest to their depositors

c.)Banks print more money than they have gold in their vaults

d.)Banks do not loan out enough funds to stimulate the economy

3.Before a Central Bank was established in the United States, people known as __________ were able to buy and sell the monies from individual states.

a.)federal funds traders

b.)currency traders

c.)the Board of Governors

d.)equity salesmen

4. Which of the following statements regarding central banks is true?

a.)Central banks require greater reliance on the gold standard.

b.)Central banks undermine international trade.

c.)A central bank controls the state and local bank locations and number of branches.

d.)A central bank has the sole authority with respect to the money supply.

5.Which statement below is true about the discount rate?

a.)It is the interest rate that the federal government pays to the public via the sale of Treasury securities.

b.)This is the rate used when banks borrow directly from the Fed.

c.)It is the same as the fed funds rate.

d.)It is the rate that banks charge other banks to loan money overnight.

1)The powers of Congress are enumerated in Article ____ of the Constitution. The founders established Congress in Article
I, Section 1, which states, “All legislative Powers herein granted shall be vested in a Congress of the United States, which shall consist of a Senate and House of Representatives.”

2)_________ refers to members of Congress benefiting on projects that are spent in their districts. Earmarks are legislative provisions that provide funding for pork barrel projects. Pork barrel projects include federally funded parks, community centers, theaters, military bases, and building projects that benefit particular areas.

Group of answer choices

Government waste

Franking privilege

3)The _____________ is at the top of the leadership hierarchy. The Speaker is second in succession to the presidency and is the only officer of the House mentioned specifically in the Constitution.

Majority Whip

Speaker of the House of Representatives

Minority Whip

Senate Pro Tempore

Pork barrel

Government corporations

4) The President of the U.S. Senate is ______________.

Majority Whip

Senate Pro Tempore

Speaker of the House of Representatives

Vice President

5) Congress members receive free postage. What is this called?

Group of answer choices

franklin privilege

franking privilege

Free Postage Act of 1891

congressional benefits

6)Presidents exercise only one power that cannot be limited by other branches: the _______.

pardon

voting

veto

approving treaties

The _____Amendment was enacted in the wake of the only president to serve more than two terms, the powerful Franklin D. Roosevelt. Currently, presidents can only serve 2 terms in office for a total of 8 years.

11

20

21

22

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Forecasting labour costs is a key aspect of hotel revenue management that enables hoteliers to appropriately allocate hotel resources and fix pricing strategies. Mary, the President of Hellenic Hoteliers Federation (HHF) is interested in investigating how labour costs (variable L_COST) relate to the number of rooms in a hotel (variable Total_Rooms). Suppose that HHF has hired you as a business analyst to develop a linear model to predict hotel labour costs based on the total number of rooms per hotel using the data provided. 3.1 Use the least squares method to estimate the regression coefficients b0 and b1 3.2 State the regression equation 3.3 Plot on the same graph, the scatter diagram and the regression line 3.4 Give the interpretation of the regression coefficients b0 and b1 as well as the result of the t-test on the individual variables (assume a significance level of 5%) 3.5 Determine the correlation coefficient of the two variables and provide an interpretation of its meaning in the context of this problem 3.6 Check statistically, at the 0.05 level of significance whether there is any evidence of a linear relationship between labour cost and total number of rooms per hotel

TR=TOTAL ROOMS, L COST =LABOUR COST

TR L_COST       Turnover_per_Room
412       2,165,000       21,519.42
313       2,214,985       21,755.04
265       1,393,550       17,937.91
204       2,460,634       37,400.05
172       1,151,600       31,824.30
133       801,469 19,444.46
127       1,072,000       22,551.18
322       1,608,013       18,205.04
241       793,009 8,793.00
172       1,383,854       25,114.16
121       494,566       14,095.35
70       437,684       22,231.59
65       83,000 5,953.85
93       626,000       18,150.99
75       37,735       3,871.67
69       256,658       11,071.70
66       230,000       8,030.30
54       200,000       10,185.19
68       199,000      
57       11,720       2,982.46
38       59,200       6,342.11
27       130,000       25,185.19
47       255,020       18,223.26
32       3,500 1,000.00
27       20,906 2,384.85
48       284,569       14,264.58
39       107,447       10,478.26
35       64,702       10,811.29
23       6,500 3,478.26
25       156,316       22,231.56
10       15,950       8,150.00
18       722,069       81,556.71
17       6,121 2,151.88
29       30,000       4,068.97
21       5,700 4,142.86
23       50,237       5,113.83
15       19,670       10,037.87
8       7,888 4,849.25
20 3,750.00
11 1,753.91
15       3,500 2,666.67
18       112,181       34,260.90
23              
10       30,000 12,000.00
26       3,575 3,001.81
306       2,074,000       19,803.92
240       1,312,601       15,823.58
330       434,237       4,361.65
139       495,000       17,050.36
353       1,511,457       15,370.22
324       1,800,000       15,432.10
276       2,050,000       22,101.45
221       623,117       9,199.82
200       796,026       18,158.06
117       360,000       11,649.57
170       538,848       10,294.08
122       568,536       17,510.12
57       300,000       15,614.04
62       249,205       9,623.61
98       150,000       6,326.53
75       220,000       6,666.67
62       50,302       2,058.19
50       517,729       20,000.00
27       51,000       16,666.67
44       75,704       7,118.52
33       271,724       40,499.76
25       118,049       9,664.80
42              
30       40,000       4,833.33
44 522.73
10       10,000       7,300.00
18       10,000       5,555.56
18 1,338.22
73       70,000       4,958.90
21       12,000       6,904.76
22       20,000       3,636.36
25       36,277       1,489.72
25       36,277       1,489.72
31       10,450       2,348.39
16       14,300       5,000.00
15       4,296       732.00
12 1,083.33
11 2,000.00
16       379,498      
22       1,520 673.36
12       45,000       58,333.33
34       96,619       18,817.53
37       270,000       21,621.62
25       60,000 10,000.00
10       12,500 9,000.00
270       1,934,820       27,977.57
261       3,000,000       36,781.61
219       1,675,995       17,559.77
280       903,000 15,907.14
378       2,429,367       16,666.67
181       1,143,850       22,352.93
166       900,000 20,180.72
119       600,000       31,932.77
174       2,500,000       32,628.43
124       1,103,939       17,559.77
112       363,825 8,054.72
227       1,538,000       16,173.81
161       1,370,968       23,161.53
216       1,339,903       12,503.53
102       173,481       6,795.40
96       210,000       15,833.33
97       441,737       11,759.43
56       96,000       8,000.00
72       177,833       7,501.82
62       252,390       25,266.45
78       377,182       17,409.35
74       111,000       9,891.89
33       238,000       23,848.48
30       45,000       5,919.30
39       50,000       3,846.15
32       40,000       6,250.00
25       61,766       4,237.28
41       166,903       25,266.46
24       116,056       17,409.33
49       41,000       5,102.04
43       195,821       11,759.42
9              
20       96,713       17,409.35
32       6,500       2,953.13
14       5,500       2,500.00
14       4,000       4,285.71
13       15,000       2,307.69
13       9,500       1,538.46
53       48,200       3,528.30
11       3,000       10,909.09
16       27,084       3,652.44
21       30,000       2,380.95
21       20,000       2,380.95
46       43,549       1,314.04
21       10,000       952.38