QUESTION 2 Do various financial indicators differ significantly according to type of company? Using the "Excel Databases.xls" file on Blackboard, locate the tab for the Financial Database. Let Type of Company be the independent variable with seven levels (Apparel, Chemical, Electric Power, Grocery, Healthcare Products, Insurance, and Petroleum for Types 1 - 7, respectively. Perform a one-way ANOVA using Excel with Earnings Per Share as the dependent variable to test if there is a significant difference in earnings per share between the 7 types of companies. (hint: you will have to organize the data appropriately to perform the one- way ANOVA in Excel). Assume a 5% level of significance. How many degrees of freedom are the Within (Error) Group Variation? Write your answer as a number.

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Company Type Total Revenues Total Assets Return on Equity Earnings per Share Average Yield Dividends per Share Average P/E Ratio
AFLAC 6 7251 29454 17.1 2.08 0.9 0.22 11.5
Albertson's 4 14690 5219 21.4 2.08 1.6 0.63 19
Allstate 6 20106 80918 20.1 3.56 1 0.36 10.6
Amerada Hess 7 8340 7935 0.2 0.08 1.1 0.6 698.3
American General 6 3362 80620 7.1 2.19 3 1.4 21.2
American Stores 4 19139 8536 12.2 1.01 1.4 0.34 23.5
Amoco 7 36287 32489 16.7 2.76 3.1 1.4 16.1
Arco Chemical 2 3995 4116 6.2 1.14 6.1 2.8 40.4
Ashland 7 14319 7777 9.5 3.8 2.3 1.1 12.4
Atlantic Richfield 7 19272 25322 21.8 5.41 3.8 2.83 3.8
Bausch & Lomb 5 1916 2773 6 0.89 2.6 1.04 2.6
Baxter International 5 6138 8707 11.5 1.06 2.3 1.13 47.2
Bristol-Myers Squibb 5 16701 14977 44.4 3.14 2 1.52 24.1
Burlington Coat 1 1777 775 12.3 1.18 0.1 0.02 12.9
Central Maine Power 3 954 2299 2.4 0.16 7.8 0.9 79.6
Chevron 7 41950 35473 18.6 4.95 3 2.28 15.2
CIGNA 6 14935 108199 13.7 4.88 2 1.1 11.4
Cinergy 3 4353 8858 13.3 1.59 5.1 1.8 22.4
Dayton Hudson 1 27757 14191 18 1.7 1.2 0.33 16.2
Dillard's 1 6817 5592 9.2 2.31 0.4 0.16 15.7
Dominion Resources 3 7678 20193 7.9 2.15 6.8 2.58 17.7
Dow Chemical 2 20018 24040 23.6 7.7 3.6 3.24 11.6
DPL 3 1356 3585 13.9 1.2 5.3 0.91 14.3
E. I. DuPont DeNemours 2 46653 42942 21.3 2.08 2.1 1.23 27.9
Eastman Chemical 2 4678 5778 16.3 3.63 3 1.76 16
Edison International 3 9235 25101 12.3 1.73 4.2 1 13.6
Engelhard 2 3631 2586 6.1 0.33 1.9 0.38 61.8
Entergy 3 9562 27001 4.2 1.03 6.9 1.8 25.4
Equitable 6 9666 151438 12.3 2.86 0.5 0.2 13.4
Ethyl 7 1064 1067 53.6 0.71 5.6 0.5 12.6
Exxon 7 137242 96064 19.4 3.37 2.8 1.63 17.1
FPL Group 3 6369 12449 12.2 3.57 3.7 1.92 14.4
The GAP 1 6508 3338 33.7 1.3 0.7 0.2 22
Georgia Gulf 2 966 613 228 2.39 1.1 0.32 11.8
GIANT Food 4 4231 1522 7.9 1.18 2.4 0.78 26.9
A & P 4 10262 2995 6.9 1.66 1.2 0.35 17.8
Great Lakes Chemicals 2 1311 2270 5.5 1.19 1.3 0.62 40.5
Green Mountain Power Company 3 179 326 8.3 1.57 7.3 1.61 14
Hannaford Bros. 4 3226 1227 9.9 1.4 1.5 0.54 26.6
Hercules 2 1866 2411 47 3.18 2.2 1 14.5
Houston Industries 3 6873 18415 8 1.66 6.6 1.5 13.7
Jefferson-Pilot 6 2578 23131 14.5 3.47 2.3 1.04 13.3
Johnson & Johnson 5 22629 21453 26.7 2.41 1.5 0.85 24.1
Liberty 6 660 3185 11.1 3.34 1.8 0.77 12.7
The Limited 1 9189 4301 10.6 0.79 2.3 0.48 26.7
Lincoln National 6 4899 77175 0.4 0.21 3.1 1.96 300.2
Lubrizol 2 1674 1462 19 2.66 2.6 1.01 14.5
Lyondell Petrochemical 7 3010 1559 46.2 3.58 3.9 0.9 6.4
Mallinkrodt 5 1868 2988 14.8 2.47 1.7 0.66 16
May Department Stores 1 12685 9930 20.5 3.11 2.4 1.2 16.2
McKesson 5 20857 5608 11 1.59 1.2 0.5 26
Mercantile Stores 1 3144 2178 7.9 3.53 2.1 1.19 16.3
Merck 5 23637 25812 36.6 3.74 1.7 1.69 26.6
Millennium Chemicals 2 3048 4326 12.6 2.47 2.9 0.6 8.3
Mobil 7 65906 43559 16.8 4.01 3.1 2.12 17.2
Monsanto 2 7514 10774 7.2 0.48 1.1 0.5 90.7
Morton 2 2388 2805 12.3 1.48 1 0.36 25.2
Murphy Oil 7 2138 2238 12.3 2.94 2.6 1.35 18
Mylan Laboratories 5 555 848 13.5 0.82 0.9 0.16 22.4
NALCO Chemical 2 1434 1441 25 2.1 2.6 1 18.3
Nevada Power 3 799 2339 10.1 1.65 6.8 1.6 14.2
NIPSCO 3 2587 4937 14.1 1.53 4.1 0.9 14.4
Olin 2 2410 1946 17.4 3 2.8 1.2 14.5
Orion Capital 6 1591 3884 16 4.15 1.5 0.6 9.8
Owens & Minor 5 3117 713 9.4 0.6 1.4 0.18 21.7
Pacific Corporation 3 6278 13880 5.2 0.68 4.6 1.08 34.2
J. C. Penney 1 30546 23493 7.7 2.1 3.8 2.13 26.9
Pennzoil 7 2654 4406 15.8 3.76 1.6 1 17.1
Pfizer 5 12504 15336 27.9 1.7 1.1 0.68 35.4
Pharmacia & Upjohn 5 6710 10380 5.8 0.61 3.1 1.08 56.2
Phillips Petroleum 7 15424 13860 19.9 3.61 3 1.34 12.4
Poe & Brown 6 129 194 25.1 1.48 1.5 0.35 16.3
PPG 2 7379 6868 28.5 3.94 2.3 1.33 14.7
PP&L Resources 3 3049 9485 11.4 1.8 7.7 1.67 12
Progressive 6 4190 7560 18.7 5.31 0.3 0.24 17
Rohm & Haas 2 3999 3900 19.8 2.13 2.2 0.63 13.4
Ruddick 4 2300 885 12.5 1.02 1.8 0.32 17
Schering-Plough 5 6778 6507 51.2 1.95 1.5 0.74 24.6
Sears, Roebuck 1 41296 38700 20.3 2.99 1.8 0.92 17.4
Stryker 5 980 985 20.5 1.28 0.3 0.11 27.2
Sun 7 10531 4667 18 2.7 2.8 1 13
Sunamerica 6 2114 35637 14.7 1.8 0.9 0.3 19.5
Texaco 7 46667 29600 20.9 4.87 3.1 1.75 11.5
The TJX Companies 1 7389 2610 26.3 1.75 0.6 0.09 8.2
Torchmark 6 2283 10967 17.5 2.39 1.7 0.59 14.2
Tosco 7 13282 5975 10.9 1.37 0.8 0.24 23
Travelers 6 37609 386555 14.9 2.54 0.9 0.4 17
Ultramar Diamond Shamrock 7 10882 5595 9.5 1.94 3.5 1.1 16.1
Union Carbide 2 6502 6964 28.8 4.53 1.6 0.79 10.7
United States Surgical Corporation 5 1172 1726 7.5 1.21 0.5 0.16 29
UNOCAL 7 6064 7530 28.9 2.65 2 0.8 15.5
UNUM 6 4077 13200 15.2 2.59 1.3 0.56 17
USX-Marathon 7 15754 10565 12.6 1.58 2.4 0.76 19.8
Valero Energy 7 5756 2493 9.6 2.03 1.2 0.42 17.2
Warner-Lambert 5 8180 8031 30.7 1.04 1.4 0.51 35.7
WEIS Markets 4 1819 972 9.2 1.87 3 0.94 16.9
Wellman 2 1083 1319 4.8 0.97 1.8 0.35 20.5
Winn-Dixie Stores 4 13219 2921 15.3 1.36 2.7 0.98 27.2
WITCO 2 2187 2298 14 1.55 2.9 1.12 24.9
Zenith Nation Insurance 6 601 1252 7.8 1.57 3.7 1 17
QUESTION 2
Do various financial indicators differ significantly according to type of company? Using the "Excel Databases.xls" file on Blackboard, locate the tab for the
Financial Database. Let Type of Company be the independent variable with seven levels (Apparel, Chemical, Electric Power, Grocery, Healthcare Products,
Insurance, and Petroleum for Types 1 - 7, respectively. Perform a one-way ANOVA using Excel with Earnings Per Share as the dependent variable to test if there
is a significant difference in earnings per share between the 7 types of companies. (hint: you will have to organize the data appropriately to perform the one-
way ANOVA in Excel). Assume a 5% level of significance. How many degrees of freedom are the Within (Error) Group Variation? Write your answer as a
number.
Transcribed Image Text:QUESTION 2 Do various financial indicators differ significantly according to type of company? Using the "Excel Databases.xls" file on Blackboard, locate the tab for the Financial Database. Let Type of Company be the independent variable with seven levels (Apparel, Chemical, Electric Power, Grocery, Healthcare Products, Insurance, and Petroleum for Types 1 - 7, respectively. Perform a one-way ANOVA using Excel with Earnings Per Share as the dependent variable to test if there is a significant difference in earnings per share between the 7 types of companies. (hint: you will have to organize the data appropriately to perform the one- way ANOVA in Excel). Assume a 5% level of significance. How many degrees of freedom are the Within (Error) Group Variation? Write your answer as a number.
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