100%Perfect work A++++ Tutorial
using this 3 data set compare the means between two groups. Make sure and identify the variables, state the hypotheses, use the pooled t-test, and then state your conclusions in the context of the variables. this are the 3 data set which i will send one after the other
Price Bedrooms Size Pool Distance Twnship Garage Baths
263.1 4 2300 0 17 5 1 2
182.4 4 2100 1 19 4 0 2
242.1 3 2300 1 12 3 0 2
213.6 2 2200 1 16 2 0 2.5
139.9 2 2100 1 28 1 0 1.5
245.4 2 2100 0 12 1 1 2
327.2 6 2500 1 15 3 1 2
271.8 2 2100 1 9 2 1 2.5
221.1 3 2300 0 18 1 0 1.5
266.6 4 2400 1 13 4 1 2
292.4 4 2100 1 14 3 1 2
209 2 1700 1 8 4 1 1.5
270.8 6 2500 1 7 4 1 2
246.1 4 2100 1 18 3 1 2
194.4 2 2300 1 11 3 0 2
281.3 3 2100 1 16 2 1 2
172.7 4 2200 0 16 3 0 2
207.5 5 2300 0 21 4 0 2.5
198.9 3 2200 0 10 4 1 2
209.3 6 1900 0 15 4 1 2
252.3 4 2600 1 8 4 1 2
192.9 4 1900 0 14 2 1 2.5
209.3 5 2100 1 20 5 0 1.5
345.3 8 2600 1 9 4 1 2
326.3 6 2100 1 11 5 1 3
173.1 2 2200 0 21 5 1 1.5
187 2 1900 1 26 4 0 2
257.2 2 2100 1 9 4 1 2
233 3 2200 1 14 3 1 1.5
180.4 2 2000 1 11 5 0 2
234 2 1700 1 19 3 1 2
207.1 2 2000 1 11 5 1 2
247.7 5 2400 1 16 2 1 2
166.2 3 2000 0 16 2 1 2
177.1 2 1900 1 10 5 1 2
182.7 4 2000 0 14 4 0 2.5
216 4 2300 1 19 2 0 2
312.1 6 2600 1 7 5 1 2.5
199.8 3 2100 1 19 3 1 2
273.2 5 2200 1 16 2 1 3
206 3 2100 0 9 3 0 1.5
232.2 3 1900 0 16 1 1 1.5
198.3 4 2100 0 19 1 1 1.5
205.1 3 2000 0 20 4 0 2
175.6 4 2300 0 24 4 1 2
307.8 3 2400 0 21 2 1 3
269.2 5 2200 1 8 5 1 3
224.8 3 2200 1 17 1 1 2.5
171.6 3 2000 0 16 4 0 2
216.8 3 2200 1 15 1 1 2
192.6 6 2200 0 14 1 0 2
236.4 5 2200 1 20 3 1 2
172.4 3 2200 1 23 3 0 2
251.4 3 1900 1 12 2 1 2
246 6 2300 1 7 3 1 3
147.4 6 1700 0 12 1 0 2
176 4 2200 1 15 1 1 2
228.4 3 2300 1 17 5 1 1.5
166.5 3 1600 0 19 3 0 2.5
189.4 4 2200 1 24 1 1 2
312.1 7 2400 1 13 3 1 3
289.8 6 2000 1 21 3 1 3
269.9 5 2200 0 11 4 1 2.5
154.3 2 2000 1 13 2 0 2
222.1 2 2100 1 9 5 1 2
209.7 5 2200 0 13 2 1 2
190.9 3 2200 0 18 3 1 2
254.3 4 2500 0 15 3 1 2
207.5 3 2100 0 10 2 0 2
209.7 4 2200 0 19 2 1 2
294 2 2100 1 13 2 1 2.5
176.3 2 2000 0 17 3 0 2
294.3 7 2400 1 8 4 1 2
224 3 1900 0 6 1 1 2
125 2 1900 1 18 4 0 1.5
236.8 4 2600 0 17 5 1 2
164.1 4 2300 1 19 4 0 2
217.8 3 2500 1 12 3 0 2
192.2 2 2400 1 16 2 0 2.5
125.9 2 2400 1 28 1 0 1.5
220.9 2 2300 0 12 1 1 2
294.5 6 2700 1 15 3 1 2
244.6 2 2300 1 9 2 1 2.5
199 3 2500 0 18 1 0 1.5
240 4 2600 1 13 4 1 2
263.2 4 2300 1 14 3 1 2
188.1 2 1900 1 8 4 1 1.5
243.7 6 2700 1 7 4 1 2
221.5 4 2300 1 18 3 1 2
175 2 2500 1 11 3 0 2
253.2 3 2300 1 16 2 1 2
155.4 4 2400 0 16 3 0 2
186.7 5 2500 0 21 4 0 2.5
179 3 2400 0 10 4 1 2
188.3 6 2100 0 15 4 1 2
227.1 4 2900 1 8 4 1 2
173.6 4 2100 0 14 2 1 2.5
188.3 5 2300 1 20 5 0 1.5
310.8 8 2900 1 9 4 1 2
293.7 6 2400 1 11 5 1 3
179 3 2400 1 8 4 1 2
188.3 6 2100 0 14 2 1 2.5
227.1 4 2900 1 20 5 0 1.5
173.6 4 2100 1 9 4 1 2
188.3 5 2300 1 11 5 1 3
ountryArea (KM)G-20PetroleumPop (1000's)65 & overLife ExpectancyAlgeria2,381,7400231,7364.0769.95Argentina2,766,8901137,38510.4275.26Australia7,686,8501119,35712.579.87Austria83,858008,15015.3877.84Belgium30,5100010,25916.9577.96Brazil8,511,96511174,4695.4563.24Canada9,976,1401131,59212.7779.56China9,596,960111,273,1117.1171.62Czech Republic790010,26413.9274.73Denmark43,094015,35214.8576.72Finland337,030005,17515.0377.58France547,0301059,55116.1378.9Germany357,0211083,02916.6177.61Greece131,9400110,62317.7278.59Hungary93,0300010,10614.7171.63Iceland103,0000027811.8179.52India3,287,590111,029,9914.6862.68Indonesia1,919,44012228,4374.6368.27Iran1,648,0000266,1294.6569.95Iraq437,0720223,3323.0866.95Ireland70,280003,84011.3576.99Italy301,2301057,68018.3579.14Japan377,83510126,77117.3580.8Kuwait17,820022,0412.4276.27Libya1,759,540025,2403.9575.65Luxembourg2,5860044314.0677.3Mexico1,972,55011101,8794.471.76Netherlands41,5260115,98113.7278.43New Zealand286,680003,86411.5377.99Nigeria923,76802126,6352.8251.07Norway324,220014,50315.178.79Poland312,6850038,63412.4473.42Portugal92,3910010,06615.6275.94Qatar11,437027692.4872.62Russia########11145,47012.8167.34Saudi Arabia1,960,5821222,7572.6868.09South Africa1,219,9121043,5864.8848.09South Korea98,4801047,9047.2774.65Spain504,7820040,03817.1878.93Sweden449,964008,87517.2879.71Switzerland41,290007,28315.379.73Turkey780,5801066,4946.1371.24United Arab Emirates82,880022,4072.474.29United Kingdom244,8201159,64815.777.82United States9,629,09111278,05912.6177.26Venezuela912,0500223,9174.7273.31
| Rank | Name | Age | Company | Title |
| 1 | Meg Whitman | 49 | eBay | CEO/Chairman |
| 2 | Anne Mulcahy | 52 | Xerox | CEO/Chairman |
| 3 | ***** ***** | 51 | ***** ***** | CEO/President |
| 4 | Oprah Winfrey | 51 | Harpo | Chairman |
| 5 | Andrea Jung | 47 | Avon | CEO/Chairman |
| 6 | Pat Woertz | 52 | Chevron | EVP |
| 7 | Sallie Krawcheck | 40 | Citigroup | CFO |
| 8 | Abigail Johnson | 43 | Fidelity | President |
| 9 | Karen Katen | 56 | Pfizer | Vice Chair |
| 10 | Judy McGrath | 52 | Viacom | CEO/Chairman |
| 11 | Indra Nooyi | 49 | PepsiCo | CFO/President |
| 12 | Christine Poon | 53 | Johnson & Johnson | Vice Chair |
| 13 | ***** ***** | 55 | Time Inc. | CEO/Chairman |
| 14 | Pat Russo | 53 | Lucent Technologies | CEO/Chairman |
| 15 | Ginni Rometty | 48 | IBM | SVP |
| 16 | Anne Sweeney | 47 | Walt Disney | President |
| 17 | Susan Arnold | 51 | Procter & Gamble | Vice Chair |
| 18 | ***** *****vermore | 47 | Hewlett-Packard | EVP |
| 19 | Zoe Cruz | 50 | Morgan Stanley | President |
| 20 | Charlene Begley | 39 | General Electric | CEO/President |
| 21 | ***** ***** | 64 | ***** ***** Living Omnimedi | Founder |
| 22 | Anne Stevens | 56 | Ford Motor | COO |
| 23 | Susan Desmond-Hellmann | 48 | Genentech | President |
| 24 | Susan Ivey | 46 | Reynolds American | CEO/President |
| 25 | ***** *****s Brinkley | 49 | Bank of America | CRO |
| 26 | Shelly Lazarus | 58 | WPP | CEO/Chairman |
| 27 | Irene Rosenfeld | 52 | PepsiCo | CEO/Chairman |
| 28 | Heidi Miller | 51 | J.P. Morgan Chase | CEO |
| 29 | Linda Dillman | 49 | Wal-Mart | CIO/EVP |
| 30 | Mary Minnick | 45 | Coca-Cola | EVP |
| 31 | Carol Bartz | 57 | Autodesk | CEO/Chairman |
| 32 | Doreen Toben | 55 | Verizon | CFO |
| 33 | Stacey Snider | 44 | GE | Chairman |
| 34 | Cathleen Black | 61 | Hearst Magazines | President |
| 35 | Lisa Weber | 42 | MetLife | President |
| 36 | Lois Quam | 44 | United Health Group | CEO |
| 37 | Carrie Cox | 48 | Schering-Plough | EVP |
| 38 | Nancy Peretsman | 51 | Allen & Co. | EVP |
| 39 | Mary Sammons | 59 | Rite Aid | CEO/President |
| 40 | Susan Decker | 42 | Yahoo | CFO/EVP |
| 41 | Dawn Hudson | 47 | PepsiCo | CEO/President |
| 42 | Amy Pascal | 47 | Sony | Vice Chair |
| 43 | Claire Watts | 45 | Wal-Mart | EVP |
| 44 | Vivian Banta | 55 | Prudential Financial | Vice Chair |
| 45 | Ellyn McColgan | 51 | Fidelity | President |
| 46 | Ellen Kullman | 49 | DuPont | Vice Chair |
| 47 | Barbara Desoer | 53 | Bank of America | Executive |
| 48 | Ursula Burns | 47 | Xerox | SVP |
| 49 | Safra Catz | 43 | Oracle | President |
| 50 | Kathy Cassidy | 51 | General Electric | Treasurer
pick three datasets and set up a difference of means tests - in other words, you are comparing the means between two groups. Make sure and identify the variables, state the hypotheses, use the pooled t-test, and then state your conclusions in the context of the variables
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11 years ago
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- solutions.docx
- data_sets.xlsx