5. Altria is reexamining the costs of capital it uses to decide
on investments in its two
primary businessesó food and tobacco. The two divisions have about
the same market
value.
Altria has an equity beta of 0.95 and a debt/equity ratio of 25%.
The companyís debt is
priced to yield an expected return of 8%. The average equity beta
of publicly traded Örms
in the tobacco business is 1.2, the average debt beta is 0.3, and
the average debt/equity
ratio of such Örms is 20%. The average equity beta of publicly
traded Örms in the food
business is 0.9, the average debt beta is close to zero, and the
debt/equity ratio of such
Örms is 80%. The current interest rate is 7.1%.
Estimate the cost of capital for each of the two businesses
In: Finance
Explain how the below ratio could be affected if there was an increase in Publicly traded hospital costs or supply chain disruptions occurred for materials including equipment, medications and other supplies? And explain how these ratio can affect the Publicly traded hospital financial statement
Increase in costs
a. Debt service coverage ratio (Net Income/Debt Service)
b. Profit Margin Ratio (Net Income/Net Sales)
c. Return on Assets (Net Income/ total assets)
Supply chain disruptions
a. Current Ratio (Current Assets/Current Liabilities)
b. Inventory turnover (Net Sales/ Average Inventory)
c. Debt to total assets (debt/total assets)
d. Return on assets (Net Income/ total assets)
In: Economics
Refer to the Baseball 2016 data, which reports information on the 2016 Major League Baseball season. Let attendance be the dependent variable and total team salary be the independent variable. Determine the regression equation and answer the following questions.
Draw a scatter diagram. From the diagram, does there seem to be a direct relationship between the two variables?
What is the expected attendance for a team with a salary of $100.0 million?
If the owners pay an additional $30 million, how many more people could they expect to attend?
At the .05 significance level, can we conclude that the slope of the regression line is positive? Conduct the appropriate test of hypothesis.
What percentage of the variation in attendance is accounted for by salary?
Determine the correlation between attendance and team batting average and between attendance and team ERA. Which is stronger? Conduct an appropriate test of hypothesis for each set of variables.
Show all work in Excel
| Team | League | Year Opened | Team Salary | Attendance | Wins | ERA | BA | HR | Year | Average salary | ||
| Arizona | National | 1998 | 65.80 | 2080145 | 79 | 4.04 | 0.264 | 154 | 2000 | 1988034 | ||
| Atlanta | National | 1996 | 89.60 | 2001392 | 67 | 4.41 | 0.251 | 100 | 2001 | 2264403 | ||
| Baltimore | American | 1992 | 118.90 | 2281202 | 81 | 4.05 | 0.250 | 217 | 2002 | 2383235 | ||
| Boston | American | 1912 | 168.70 | 2880694 | 78 | 4.31 | 0.265 | 161 | 2003 | 2555476 | ||
| Chicago Cubs | National | 1914 | 117.20 | 2959812 | 97 | 3.36 | 0.244 | 171 | 2004 | 2486609 | ||
| Chicago Sox | American | 1991 | 110.70 | 1755810 | 76 | 3.98 | 0.250 | 136 | 2005 | 2632655 | ||
| Cincinnati | National | 2003 | 117.70 | 2419506 | 64 | 4.33 | 0.248 | 167 | 2006 | 2866544 | ||
| Cleveland | American | 1994 | 87.70 | 1388905 | 81 | 3.67 | 0.256 | 141 | 2007 | 2944556 | ||
| Colorado | National | 1995 | 98.30 | 2506789 | 68 | 5.04 | 0.265 | 186 | 2008 | 3154845 | ||
| Detroit | American | 2000 | 172.80 | 2726048 | 74 | 4.64 | 0.270 | 151 | 2009 | 3240206 | ||
| Houston | American | 2000 | 69.10 | 2153585 | 86 | 3.57 | 0.250 | 230 | 2010 | 3297828 | ||
| Kansas City | American | 1973 | 112.90 | 2708549 | 95 | 3.73 | 0.269 | 139 | 2011 | 3305393 | ||
| LA Angels | American | 1966 | 146.40 | 3012765 | 85 | 3.94 | 0.246 | 176 | 2012 | 3440000 | ||
| LA Dodgers | National | 1962 | 230.40 | 3764815 | 92 | 3.44 | 0.250 | 187 | 2013 | 3650000 | ||
| Miami | National | 2012 | 84.60 | 1752235 | 71 | 4.02 | 0.260 | 120 | 2014 | 3950000 | ||
| Milwaukee | National | 2001 | 98.70 | 2542558 | 68 | 4.28 | 0.251 | 145 | 2015 | 4250000 | ||
| Minnesota | American | 2010 | 108.30 | 2220054 | 83 | 4.07 | 0.247 | 156 | ||||
| NY Mets | National | 2009 | 100.10 | 2569753 | 90 | 3.43 | 0.244 | 177 | ||||
| NY Yankees | American | 2009 | 213.50 | 3193795 | 87 | 4.05 | 0.251 | 212 | ||||
| Oakland | American | 1966 | 80.80 | 1768175 | 68 | 4.14 | 0.251 | 146 | ||||
| Philadelphia | National | 2004 | 133.00 | 1831080 | 63 | 4.69 | 0.249 | 130 | ||||
| Pittsburgh | National | 2001 | 85.90 | 2498596 | 98 | 3.21 | 0.260 | 140 | ||||
| San Diego | National | 2004 | 126.60 | 2459742 | 74 | 4.09 | 0.243 | 148 | ||||
| San Francisco | National | 2000 | 166.50 | 3375882 | 84 | 3.72 | 0.267 | 136 | ||||
| Seattle | American | 1999 | 123.20 | 2193581 | 76 | 4.16 | 0.249 | 198 | ||||
| St. Louis | National | 2006 | 120.30 | 3520889 | 100 | 2.94 | 0.253 | 137 | ||||
| Tampa Bay | American | 1990 | 74.80 | 1287054 | 80 | 3.74 | 0.252 | 167 | ||||
| Texas | American | 1994 | 144.80 | 2491875 | 88 | 4.24 | 0.257 | 172 | ||||
| Toronto | American | 1989 | 116.40 | 2794891 | 93 | 3.8 | 0.269 | 232 | ||||
| Washington | National | 2008 | 174.50 | 2619843 | 83 | 3.62 | 0.251 | 177 |
In: Math
How does Zynga recognize revenue from virtual goods?
Zynga was founded in July 2007 and is headquartered in San
Francisco, California. Around 80% of Zynga’s revenue comes from
Facebook users. Facebook provides a social networking platform used
by over 1 billion people, and Zynga is a video game developer with
many products (e.g. FarmVille, MafiaWars) that interface with
social technology sites like Facebook. Zynga has been publicly
traded since December 16, 2011.
Zynga’s FarmVille players can use Facebook to purchase in-game
currency they can use to acquire resources, such as hay and
animals, in pursuit of a more productive virtual farm. Revenue from
conversion of real dollars into in-game currency is big business:
Zynga estimates that such sales, from FarmVille hay to Mafia Wars
guns, accounted for nearly all of Zynga’s $1.1 billion in 2011
revenues and 12% of revenue for Facebook.
Revenue recognition in firms that earn money through socially-based
use of virtual items is challenging. Zynga’s customers convert real
dollars into FarmVille currency in order to purchase virtual goods.
Customers’ real dollars become Farm Cash which the customers can
use in the future to purchase virtual items in the Farmville
application. When the customer uses Farm Cash to buy a tractor, for
example, Facebook reduces the player’s Farm Cash, keeps 30% of the
real dollar equivalent as a processing fee, and sends 70% to
Zynga.
Starting in 2009, Zynga classified the game items it sells to
players as either “consumable” or “durable” goods. The former
category is for goods that players can immediately use, like energy
in the game CityVille; the latter is for goods that players buy and
keep for the duration of the game, such as tractors in FarmVille.
Until 2010 Zynga estimated the average player life (the number of
months a player on average continues to play the game) to be 19
months. In early 2011 it changed that estimate to 15 months. The
shorter player life increased revenue for the six months by $27.3
million, turning a loss for the six months ended June 30, 2011 into
a net profit of $18.1 million.
Required:
Discuss the revenue recognition at Zynga.
In: Accounting
Concord Corporation, a publicly-traded company, agreed to loan
money to another company. On July 1, 2020, the company received a
five-year promissory note with a face value of $505,000, paying
interest at a face rate of 5% on July 1 each year. The note was
issued to yield an effective interest rate of 6%. Concord used the
effective interest method of amortization for discounts or
premiums, and the company’s year-end is September 30.
1. Use 1. PV.1 Tables, 2. a financial calculator, or 3. Excel functions to arrive at the amount to record the note receivable.
2. Prepare a schedule of note premium / discount amortization schedule
3. Prepare the journal entries to record the issue of the note on July 1, 2020, and any required accrual entries at the company’s year-end on September 30, 2020. Finally, prepare the journal entry to record the first cash collection received on July 1, 2021 for Concord Corporation.
In: Accounting
Part 2: Transforming data and computing descriptive statistics
Create a quarterly real GDP series by dividing nominal GDP by the GDP deflator. Also, create a money velocity series as PY/M where P is the price level, Y is real GDP, and M is the M3 money supply measure.
a. Plot the velocity of money (produce a graph similar to Figure 8.2 on page 212 of the textbook). Has velocity risen or fallen over the sample period? b. What is the mean and standard deviation of M3 velocity?
picture from textbook: https://media.cheggcdn.com/media%2Fb3d%2Fb3d56712-5053-405f-83e0-88009e1d6240%2FphpGAezM0.png
data to be used:
| observation_date | MABMM301CAQ189S | observation_date | CANGDPDEFQISMEI | Quarterly | v62295562 - Gross domestic product at market prices (x 1,000,000) | ||
| 1981-01-01 | 2.04311E+11 | 1981-01-01 | 42.69811116 | Q1 1981 | 354,784 | ||
| 1981-04-01 | 2.07984E+11 | 1981-04-01 | 43.66104146 | Q2 1981 | 366,788 | ||
| 1981-07-01 | 2.16848E+11 | 1981-07-01 | 44.62899825 | Q3 1981 | 371,560 | ||
| 1981-10-01 | 2.18082E+11 | 1981-10-01 | 45.29084386 | Q4 1981 | 375,352 | ||
| 1982-01-01 | 2.17479E+11 | 1982-01-01 | 46.60831697 | Q1 1982 | 381,676 | ||
| 1982-04-01 | 2.19886E+11 | 1982-04-01 | 47.57980057 | Q2 1982 | 385,140 | ||
| 1982-07-01 | 2.2233E+11 | 1982-07-01 | 48.37395895 | Q3 1982 | 388,116 | ||
| 1982-10-01 | 2.24304E+11 | 1982-10-01 | 49.3332838 | Q4 1982 | 392,160 | ||
| 1983-01-01 | 2.2614E+11 | 1983-01-01 | 49.71327644 | Q1 1983 | 401,680 | ||
| 1983-04-01 | 2.24478E+11 | 1983-04-01 | 50.26292877 | Q2 1983 | 414,192 | ||
| 1983-07-01 | 2.25279E+11 | 1983-07-01 | 51.27358864 | Q3 1983 | 427,308 | ||
| 1983-10-01 | 2.27179E+11 | 1983-10-01 | 51.61005878 | Q4 1983 | 435,584 | ||
| 1984-01-01 | 2.283E+11 | 1984-01-01 | 51.97043324 | Q1 1984 | 446,148 | ||
| 1984-04-01 | 2.32617E+11 | 1984-04-01 | 52.30782428 | Q2 1984 | 457,828 | ||
| 1984-07-01 | 2.37141E+11 | 1984-07-01 | 52.72343939 | Q3 1984 | 463,424 | ||
| 1984-10-01 | 2.40677E+11 | 1984-10-01 | 53.04197052 | Q4 1984 | 473,572 | ||
| 1985-01-01 | 2.44981E+11 | 1985-01-01 | 53.42486468 | Q1 1985 | 484,236 | ||
| 1985-04-01 | 2.48915E+11 | 1985-04-01 | 54.26513634 | Q2 1985 | 493,432 | ||
| 1985-07-01 | 2.5245E+11 | 1985-07-01 | 54.50504061 | Q3 1985 | 501,888 | ||
| 1985-10-01 | 2.5701E+11 | 1985-10-01 | 54.84025435 | Q4 1985 | 512,744 | ||
| 1986-01-01 | 2.64237E+11 | 1986-01-01 | 55.25634718 | Q1 1986 | 516,520 | ||
| 1986-04-01 | 2.68411E+11 | 1986-04-01 | 55.49059389 | Q2 1986 | 521,696 | ||
| 1986-07-01 | 2.71948E+11 | 1986-07-01 | 56.09128688 | Q3 1986 | 528,016 | ||
| 1986-10-01 | 2.8153E+11 | 1986-10-01 | 56.87836721 | Q4 1986 | 531,568 | ||
| 1987-01-01 | 2.91177E+11 | 1987-01-01 | 57.53317263 | Q1 1987 | 550,140 | ||
| 1987-04-01 | 2.99965E+11 | 1987-04-01 | 58.33295861 | Q2 1987 | 565,020 | ||
| 1987-07-01 | 3.05585E+11 | 1987-07-01 | 58.89916591 | Q3 1987 | 579,244 | ||
| 1987-10-01 | 3.08066E+11 | 1987-10-01 | 59.55513344 | Q4 1987 | 593,300 | ||
| 1988-01-01 | 3.12459E+11 | 1988-01-01 | 60.19836959 | Q1 1988 | 608,480 | ||
| 1988-04-01 | 3.22487E+11 | 1988-04-01 | 60.66882712 | Q2 1988 | 618,684 | ||
| 1988-07-01 | 3.34801E+11 | 1988-07-01 | 61.66399317 | Q3 1988 | 628,884 | ||
| 1988-10-01 | 3.42958E+11 | 1988-10-01 | 62.46758329 | Q4 1988 | 641,556 | ||
| 1989-01-01 | 3.51835E+11 | 1989-01-01 | 62.92301878 | Q1 1989 | 653,604 | ||
| 1989-04-01 | 3.62677E+11 | 1989-04-01 | 63.98918575 | Q2 1989 | 667,232 | ||
| 1989-07-01 | 3.73418E+11 | 1989-07-01 | 64.65157352 | Q3 1989 | 676,572 | ||
| 1989-10-01 | 3.85482E+11 | 1989-10-01 | 64.99380354 | Q4 1989 | 678,696 | ||
| 1990-01-01 | 3.95554E+11 | 1990-01-01 | 65.40531748 | Q1 1990 | 689,404 | ||
| 1990-04-01 | 4.0366E+11 | 1990-04-01 | 66.03354097 | Q2 1990 | 693,132 | ||
| 1990-07-01 | 4.10993E+11 | 1990-07-01 | 66.70745429 | Q3 1990 | 695,180 | ||
| 1990-10-01 | 4.1872E+11 | 1990-10-01 | 67.22290923 | Q4 1990 | 694,272 | ||
| 1991-01-01 | 4.27352E+11 | 1991-01-01 | 67.93588676 | Q1 1991 | 691,484 | ||
| 1991-04-01 | 4.32806E+11 | 1991-04-01 | 68.36517541 | Q2 1991 | 699,036 | ||
| 1991-07-01 | 4.33277E+11 | 1991-07-01 | 68.59406171 | Q3 1991 | 702,272 | ||
| 1991-10-01 | 4.39453E+11 | 1991-10-01 | 68.66059067 | Q4 1991 | 704,220 | ||
| 1992-01-01 | 4.45823E+11 | 1992-01-01 | 68.94091388 | Q1 1992 | 707,560 | ||
| 1992-04-01 | 4.50337E+11 | 1992-04-01 | 69.32202186 | Q2 1992 | 712,328 | ||
| 1992-07-01 | 4.57429E+11 | 1992-07-01 | 69.62116203 | Q3 1992 | 719,252 | ||
| 1992-10-01 | 4.64677E+11 | 1992-10-01 | 69.77651809 | Q4 1992 | 724,936 | ||
| 1993-01-01 | 4.70009E+11 | 1993-01-01 | 69.96565871 | Q1 1993 | 731,528 | ||
| 1993-04-01 | 4.72942E+11 | 1993-04-01 | 70.41575784 | Q2 1993 | 742,932 | ||
| 1993-07-01 | 4.75799E+11 | 1993-07-01 | 70.19167988 | Q3 1993 | 747,640 | ||
| 1993-10-01 | 4.79652E+11 | 1993-10-01 | 70.70364286 | Q4 1993 | 756,332 | ||
| 1994-01-01 | 4.8357E+11 | 1994-01-01 | 70.95633662 | Q1 1994 | 770,204 | ||
| 1994-04-01 | 4.89883E+11 | 1994-04-01 | 70.93029423 | Q2 1994 | 781,204 | ||
| 1994-07-01 | 5.00109E+11 | 1994-07-01 | 71.5711307 | Q3 1994 | 798,332 | ||
| 1994-10-01 | 5.03525E+11 | 1994-10-01 | 71.94169718 | Q4 1994 | 808,288 | ||
| 1995-01-01 | 5.07562E+11 | 1995-01-01 | 72.43909165 | Q1 1995 | 821,384 | ||
| 1995-04-01 | 5.15417E+11 | 1995-04-01 | 72.8401001 | Q2 1995 | 826,212 | ||
| 1995-07-01 | 5.24551E+11 | 1995-07-01 | 73.10778253 | Q3 1995 | 830,332 | ||
| 1995-10-01 | 5.29711E+11 | 1995-10-01 | 73.48182065 | Q4 1995 | 837,964 | ||
| 1996-01-01 | 5.39297E+11 | 1996-01-01 | 73.73975025 | Q1 1996 | 841,428 | ||
| 1996-04-01 | 5.45922E+11 | 1996-04-01 | 73.98403847 | Q2 1996 | 850,092 | ||
| 1996-07-01 | 5.50767E+11 | 1996-07-01 | 74.34930978 | Q3 1996 | 861,784 | ||
| 1996-10-01 | 5.55781E+11 | 1996-10-01 | 74.87572976 | Q4 1996 | 874,788 | ||
| 1997-01-01 | 5.65662E+11 | 1997-01-01 | 75.08368347 | Q1 1997 | 888,792 | ||
| 1997-04-01 | 5.70634E+11 | 1997-04-01 | 74.88081067 | Q2 1997 | 896,372 | ||
| 1997-07-01 | 5.75825E+11 | 1997-07-01 | 75.08607625 | Q3 1997 | 909,568 | ||
| 1997-10-01 | 5.85016E+11 | 1997-10-01 | 75.29788696 | Q4 1997 | 920,876 | ||
| 1998-01-01 | 5.88563E+11 | 1998-01-01 | 75.10463509 | Q1 1998 | 931,392 | ||
| 1998-04-01 | 5.92121E+11 | 1998-04-01 | 75.11357127 | Q2 1998 | 931,908 | ||
| 1998-07-01 | 5.97459E+11 | 1998-07-01 | 74.72571561 | Q3 1998 | 935,696 | ||
| 1998-10-01 | 6.02599E+11 | 1998-10-01 | 74.87131258 | Q4 1998 | 950,184 | ||
| 1999-01-01 | 6.02129E+11 | 1999-01-01 | 75.21325796 | Q1 1999 | 971,824 | ||
| 1999-04-01 | 6.13187E+11 | 1999-04-01 | 76.03927032 | Q2 1999 | 990,748 | ||
| 1999-07-01 | 6.21062E+11 | 1999-07-01 | 76.91249304 | Q3 1999 | 1,017,736 | ||
| 1999-10-01 | 6.32911E+11 | 1999-10-01 | 77.30843557 | Q4 1999 | 1,037,516 | ||
| 2000-01-01 | 6.48037E+11 | 2000-01-01 | 78.22530767 | Q1 2000 | 1,066,576 | ||
| 2000-04-01 | 6.58564E+11 | 2000-04-01 | 79.42312702 | Q2 2000 | 1,095,808 | ||
| 2000-07-01 | 6.74681E+11 | 2000-07-01 | 80.21978873 | Q3 2000 | 1,117,980 | ||
| 2000-10-01 | 6.83844E+11 | 2000-10-01 | 80.87774982 | Q4 2000 | 1,129,156 | ||
| 2001-01-01 | 6.93689E+11 | 2001-01-01 | 81.65841791 | Q1 2001 | 1,145,988 | ||
| 2001-04-01 | 6.96378E+11 | 2001-04-01 | 81.65117527 | Q2 2001 | 1,148,844 | ||
| 2001-07-01 | 7.0454E+11 | 2001-07-01 | 80.70759895 | Q3 2001 | 1,134,708 | ||
| 2001-10-01 | 7.1682E+11 | 2001-10-01 | 80.0583262 | Q4 2001 | 1,132,480 | ||
| 2002-01-01 | 7.29263E+11 | 2002-01-01 | 80.41861287 | Q1 2002 | 1,154,524 | ||
| 2002-04-01 | 7.34895E+11 | 2002-04-01 | 81.83423125 | Q2 2002 | 1,181,544 | ||
| 2002-07-01 | 7.50367E+11 | 2002-07-01 | 82.38631683 | Q3 2002 | 1,199,908 | ||
| 2002-10-01 | 7.58437E+11 | 2002-10-01 | 83.42950962 | Q4 2002 | 1,221,832 | ||
| 2003-01-01 | 7.61874E+11 | 2003-01-01 | 84.59159619 | Q1 2003 | 1,245,676 | ||
| 2003-04-01 | 7.82063E+11 | 2003-04-01 | 83.87561141 | Q2 2003 | 1,233,300 | ||
| 2003-07-01 | 7.96029E+11 | 2003-07-01 | 84.95635352 | Q3 2003 | 1,253,900 | ||
| 2003-10-01 | 8.07003E+11 | 2003-10-01 | 85.3524376 | Q4 2003 | 1,268,384 | ||
| 2004-01-01 | 8.30867E+11 | 2004-01-01 | 86.29841734 | Q1 2004 | 1,291,688 | ||
| 2004-04-01 | 8.50393E+11 | 2004-04-01 | 87.39335372 | Q2 2004 | 1,323,544 | ||
| 2004-07-01 | 8.63961E+11 | 2004-07-01 | 87.89404677 | Q3 2004 | 1,346,952 | ||
| 2004-10-01 | 8.85819E+11 | 2004-10-01 | 88.27669893 | Q4 2004 | 1,362,528 | ||
| 2005-01-01 | 9.14545E+11 | 2005-01-01 | 88.82847112 | Q1 2005 | 1,375,720 | ||
| 2005-04-01 | 9.38963E+11 | 2005-04-01 | 89.42817592 | Q2 2005 | 1,394,868 | ||
| 2005-07-01 | 9.54247E+11 | 2005-07-01 | 90.72483988 | Q3 2005 | 1,432,508 | ||
| 2005-10-01 | 9.62155E+11 | 2005-10-01 | 91.87374486 | Q4 2005 | 1,465,016 | ||
| 2006-01-01 | 9.81505E+11 | 2006-01-01 | 91.54859597 | Q1 2006 | 1,471,532 | ||
| 2006-04-01 | 9.99682E+11 | 2006-04-01 | 92.42400195 | Q2 2006 | 1,486,320 | ||
| 2006-07-01 | 1.02234E+12 | 2006-07-01 | 93.05784619 | Q3 2006 | 1,500,672 | ||
| 2006-10-01 | 1.04904E+12 | 2006-10-01 | 93.3031751 | Q4 2006 | 1,510,304 | ||
| 2007-01-01 | 1.07602E+12 | 2007-01-01 | 94.71213816 | Q1 2007 | 1,543,024 | ||
| 2007-04-01 | 1.10249E+12 | 2007-04-01 | 95.59095835 | Q2 2007 | 1,572,372 | ||
| 2007-07-01 | 1.14279E+12 | 2007-07-01 | 95.53638302 | Q3 2007 | 1,578,004 | ||
| 2007-10-01 | 1.17806E+12 | 2007-10-01 | 96.77660407 | Q4 2007 | 1,600,728 | ||
| 2008-01-01 | 1.21117E+12 | 2008-01-01 | 98.67959821 | Q1 2008 | 1,633,172 | ||
| 2008-04-01 | 1.25192E+12 | 2008-04-01 | 100.7423479 | Q2 2008 | 1,673,096 | ||
| 2008-07-01 | 1.28028E+12 | 2008-07-01 | 100.9439217 | Q3 2008 | 1,690,428 | ||
| 2008-10-01 | 1.30447E+12 | 2008-10-01 | 97.56793201 | Q4 2008 | 1,614,996 | ||
| 2009-01-01 | 1.29867E+12 | 2009-01-01 | 96.02749385 | Q1 2009 | 1,553,180 | ||
| 2009-04-01 | 1.29828E+12 | 2009-04-01 | 96.54850348 | Q2 2009 | 1,544,376 | ||
| 2009-07-01 | 1.3059E+12 | 2009-07-01 | 97.33262931 | Q3 2009 | 1,563,964 | ||
| 2009-10-01 | 1.31498E+12 | 2009-10-01 | 98.90114935 | Q4 2009 | 1,607,940 | ||
| 2010-01-01 | 1.32874E+12 | 2010-01-01 | 99.68889426 | Q1 2010 | 1,640,056 | ||
| 2010-04-01 | 1.36292E+12 | 2010-04-01 | 99.73092225 | Q2 2010 | 1,649,184 | ||
| 2010-07-01 | 1.39202E+12 | 2010-07-01 | 99.76256572 | Q3 2010 | 1,661,488 | ||
| 2010-10-01 | 1.40577E+12 | 2010-10-01 | 100.8028477 | Q4 2010 | 1,697,792 | ||
| 2011-01-01 | 1.43135E+12 | 2011-01-01 | 102.1875932 | Q1 2011 | 1,733,840 | ||
| 2011-04-01 | 1.45784E+12 | 2011-04-01 | 103.2762484 | Q2 2011 | 1,755,640 | ||
| 2011-07-01 | 1.48928E+12 | 2011-07-01 | 103.3687047 | Q3 2011 | 1,781,600 | ||
| 2011-10-01 | 1.52151E+12 | 2011-10-01 | 104.1128451 | Q4 2011 | 1,808,604 | ||
| 2012-01-01 | 1.55116E+12 | 2012-01-01 | 104.2014187 | Q1 2012 | 1,810,720 | ||
| 2012-04-01 | 1.57589E+12 | 2012-04-01 | 104.0827415 | Q2 2012 | 1,814,628 | ||
| 2012-07-01 | 1.59536E+12 | 2012-07-01 | 104.5453546 | Q3 2012 | 1,826,288 | ||
| 2012-10-01 | 1.61098E+12 | 2012-10-01 | 105.1788905 | Q4 2012 | 1,839,596 | ||
| 2013-01-01 | 1.63607E+12 | 2013-01-01 | 105.9475736 | Q1 2013 | 1,872,136 | ||
| 2013-04-01 | 1.67053E+12 | 2013-04-01 | 105.8155098 | Q2 2013 | 1,881,924 | ||
| 2013-07-01 | 1.69833E+12 | 2013-07-01 | 106.3926058 | Q3 2013 | 1,907,692 | ||
| 2013-10-01 | 1.75066E+12 | 2013-10-01 | 106.4727711 | Q4 2013 | 1,928,372 | ||
| 2014-01-01 | 1.78916E+12 | 2014-01-01 | 108.0058207 | Q1 2014 | 1,958,572 | ||
| 2014-04-01 | 1.81251E+12 | 2014-04-01 | 108.0948485 | Q2 2014 | 1,983,684 | ||
| 2014-07-01 | 1.85501E+12 | 2014-07-01 | 108.6916969 | Q3 2014 | 2,009,164 | ||
| 2014-10-01 | 1.89181E+12 | 2014-10-01 | 108.2081793 | Q4 2014 | 2,009,312 | ||
| 2015-01-01 | 1.92827E+12 | 2015-01-01 | 107.1608189 | Q1 2015 | 1,985,880 | ||
| 2015-04-01 | 1.95461E+12 | 2015-04-01 | 107.4289334 | Q2 2015 | 1,987,968 | ||
| 2015-07-01 | 2.01857E+12 | 2015-07-01 | 107.7699516 | Q3 2015 | 2,005,556 | ||
| 2015-10-01 | 2.05577E+12 | 2015-10-01 | 107.3727069 | Q4 2015 | 2,000,240 | ||
| 2016-01-01 | 2.09906E+12 | 2016-01-01 | 107.1804261 | Q1 2016 | 2,008,964 | ||
| 2016-04-01 | 2.14464E+12 | 2016-04-01 | 107.4862374 | Q2 2016 | 2,009,416 | ||
| 2016-07-01 | 2.19735E+12 | 2016-07-01 | 108.2285573 | Q3 2016 | 2,044,564 | ||
| 2016-10-01 | 2.2347E+12 | 2016-10-01 | 109.4481763 | Q4 2016 | 2,079,080 | ||
| 2017-01-01 | 2.25137E+12 | 2017-01-01 | 110.2520312 | Q1 2017 | 2,115,064 | ||
| 2017-04-01 | 2.30112E+12 | 2017-04-01 | 110.1958834 | Q2 2017 | 2,136,712 | ||
| 2017-07-01 | 2.29036E+12 | 2017-07-01 | 110.2431625 | Q3 2017 |
In: Economics
1. Two researcher want to find out whether there is a difference among graduation rates (these are in percentages) of five colleges over a 10-year period. Using the Data set below, determine if there a difference between colleges? Do this manually and show all eight steps in computing. (HINT: There is one variable being examined (i.e. graduation rates) for more than two groups (i.e. college 1, 2, 3, 4, 5) that are tested only once).
|
College 1 |
College 2 |
College 3 |
College 4 |
College 5 |
|
|
2005 |
67 |
82 |
94 |
65 |
88 |
|
2006 |
68 |
87 |
78 |
65 |
87 |
|
2007 |
65 |
83 |
81 |
45 |
86 |
|
2008 |
68 |
73 |
76 |
57 |
88 |
|
2009 |
67 |
77 |
75 |
68 |
89 |
|
2010 |
71 |
74 |
81 |
76 |
87 |
|
2011 |
78 |
76 |
79 |
77 |
81 |
|
2012 |
76 |
78 |
89 |
72 |
78 |
|
2013 |
72 |
76 |
76 |
69 |
89 |
|
2014 |
77 |
86 |
77 |
58 |
87 |
2. How do you interpret = 18.9, p < .05?
3. If the correlation between variable X and variable Y is perfect, what do you know about the prediction?
In: Statistics and Probability
1. Two researcher want to find out whether there is a difference among graduation rates (these are in percentages) of five colleges over a 10-year period. Using the Data set below, determine if there a difference between colleges? Do this manually and show all eight steps in computing. (HINT: There is one variable being examined (i.e. graduation rates) for more than two groups (i.e. college 1, 2, 3, 4, 5) that are tested only once).
|
College 1 |
College 2 |
College 3 |
College 4 |
College 5 |
|
|
2005 |
67 |
82 |
94 |
65 |
88 |
|
2006 |
68 |
87 |
78 |
65 |
87 |
|
2007 |
65 |
83 |
81 |
45 |
86 |
|
2008 |
68 |
73 |
76 |
57 |
88 |
|
2009 |
67 |
77 |
75 |
68 |
89 |
|
2010 |
71 |
74 |
81 |
76 |
87 |
|
2011 |
78 |
76 |
79 |
77 |
81 |
|
2012 |
76 |
78 |
89 |
72 |
78 |
|
2013 |
72 |
76 |
76 |
69 |
89 |
|
2014 |
77 |
86 |
77 |
58 |
87 |
2. How do you interpret = 18.9, p < .05?
3. If the correlation between variable X and variable Y is perfect, what do you know about the prediction?
In: Statistics and Probability
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 62 stocks traded on the NYSE that day showed that 27
went up.
You are conducting a study to see if the proportion of stocks that
went up is is significantly more than 0.3. You use a significance
level of α=0.10α=0.10.
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...
This test statistic leads to a decision to...
As such, the final conclusion is that...
In: Math
A cyclist won a bicycle race for seven consecutive years. His "winning" times and "victory" margins (time difference of the second place finisher) are given in the figure below.
| Year | Time (h:m:s) |
Margin (m:s) |
|---|---|---|
| 1999 | 91:32:19 | 7:35 |
| 2000 | 92:33:07 | 6:07 |
| 2001 | 86:17:27 | 6:41 |
| 2002 | 82:05:12 | 7:18 |
| 2003 | 83:41:12 | 1:05 |
| 2004 | 83:36:05 | 6:13 |
| 2005 | 86:15:05 | 4:20 |
(a) Find the mean, median and mode of the cyclist's times. (If an answer does not exist, enter DNE.)
| mean | : : h:m:s |
| median | : : h:m:s |
| mode | : : h:m:s |
(b) Find the mean, median and mode of the cyclist's margins. (If an
answer does not exist, enter DNE.)
| mean | : m:s |
| median | : m:s |
| mode | : m:s |
In: Statistics and Probability