Satyam Acharya BSPHH010409

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Percentage of music sales by genre of music Type 1996 1997 1998 1999 2000 Rock 32.6 32.5 25.7 25.2 24.8 Country 12.1 11.2 12.8 10.8 10.7 R&B 12.1 11.2 12.8 10.5 9.7 Pop 9.3 9.4 10 10.3 11 Rap 8.9 10.1 9.7 10.8 12.9 Gospel 4.3 4.5 6.3 5.1 4.8 Classica 3.4 2.8 3.3 3.5 2.7 Jazz 3.3 2.8 1.9 3 2.9 Other 14 15.5 17.5 20.8 20.5 line diagrams Rock Cou 0 5 10 15 20 25 30 35 1 2 3 9 10 11 12 13 Country 1 2 3 4 5 0 5 10 15 R&B 1 2 3 4 5 8 9 10 11 12 Pop 1 2 3 0 5 10 15 Rap

Transcript of Satyam Acharya BSPHH010409

Sheet1Percentage of music sales by genre of musicType19961997199819992000Rock32.632.525.725.224.8Country12.111.212.810.810.7R&B12.111.212.810.59.7Pop9.39.41010.311Rap8.910.19.710.812.9Gospel4.34.56.35.14.8Classical3.42.83.33.52.7Jazz3.32.81.932.9Other1415.517.520.820.5

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Sheet2Travel & Living conducts an annual survey of subscribers in order to determine the best places to stay. Table below shows a sample of 9 European hotels from one of their surveys. The overall score includes subscriber's evaluation of each hotel's rooms, service, resturants, location / atmosphere and public arteas (a high score indicates high level of satisfaction). The price of the room varies from $ (lowest) to $$$$ (highest). Name of PropertyCountryRoom Rate Number of RoomsOverall ScoreGraveteye ManorEngland$$1883.6Villa d'EsteItaly$$$$16686.3Hotel PremGermany$5477.8Hotel d'EuropeFrance$$4776.8Palace LuzernSwitzerland$$32680.9Royal Crescent HotelEngland$$$4573.7Hotel SacherAustria$$$12085.5Duc de BourgogneBelgium$1076.9Villa GalliciFrance$$2290.6

Sheet3A C Neilson's home technology report provided information about technology and its usage by persons aged 12 years & above. The following data are the hours of personal computer usage during one week for a sample of 50 persons.S.No.Hours14.123.134.1410.857.261.574.884.192.8106.11110.4122138.8149.5155.7165.91714.8185.61912.9205.9213.4225.4234.32412.1254.7265.7274.2283.3290.7303.9311.6323.9337.1344353.7366.1374.13810.3399.2403.14134211.1436.2444.4456.1463.7473.5487.6495.7503.1

Sheet4Table below presents a company's data on revenue generated through each of its customers. The table also provides information about the type of customer and the region and the industry each customer belongs to. The variable description is provided below:id : customer identification numberCustomer : 1 - Regular, 2 - Preferredrevenue : Revenue generatedregion : 1 - North, 2 - South, 3 - East, 4 - Westindustryt : 1. Government, 2 - Commercial, 3 - Academics(arranged/ sorted data)idcustomerrevenueregionindustry11$3,7874121$1,7342231$2,1264141$2,2594251$1,5871161$04371$1,8382181$1,8474191$1,71433101$1,71823111$4,38841121$3,15512131$3,83441142$2,29112152$4,14022162$2,19423172$2,93821182$3,31332192$3,32733202$1,44931212$2,69613222$3,27222232$4,09613242$4,34023252$2,46241262$3,63032272$46543282$1,87112292$1,37743302$3,79721312$4,25313322$3,05721332$3,39541342$1,38741352$2,14812362$2,20542372$2,02223382$2,73831

Sheet5The table below provides financial information for a sample of 36 companies whose stocks trade on NYSE. The data on sales / margins / ROE are a composite rating based on a company's sales growth rate, its profit margins and its return on equity (ROE). EPS rating is a measure of growth in earnings per share of the company. CompanyEPS RatingRelative Price StrengthIndustry Group Relative StrengthSales/Margins/ROEPE RatioMcDermott66AC7Bowater PLC1446CD51NYMAGIC1745DD15Mattel1820ED29Atmos Engy219CE25Goodyear219ED19York Intl.2814DB7Reebok3172CE15Callaway Golf4662BE20Teco Energy4948DB12Hanson PLC5732BB12AlaskaAirGp5817CB6Nordstrom5857BC21Office Depot5840BB14US West6065BA22Praxair6232CB15Wachovia6936EB14Dole Food7054EC17Elec. Data Sys7269AB36Central Parking7618BC19ICN Pharm.7656AD18Payless Shoes7659BB12Fed. Dept. Stor.7921DB11Jefferson plt8038DC16Murphy Oil8062BB26Texaco8031DC23Advo8174BA14Gateway8268AA42Winnebago8349DA8Alliant Tech8422BB10Dean Foods847BC9Kroger8424DA17Bnk of Am.8738CA11Safeway9161DA24Monaco9721DA8United Rental9812CA9

Sheet6Table below shows employee data for a BPO firm for the annual appraisal of its employees. The data is collected von 6 variables - Name, Gender, DOB, Present Salary, Beginning Salary & the previous experiewnce.

NameGenderDate ofPresentBeginningExperienceBirthSalarySalaryin monthsAkramM3-Feb-52$57,000$27,000144RahmanM23-May-58$40,200$18,75036TineF26-Jul-29$21,450$12,000240NeelamF15-Apr-47$21,900$13,200190ArdenM9-Feb-55$45,000$21,000138AdolfM22-Aug-58$32,100$13,50067JackM26-Apr-56$36,000$18,750114JillF6-May-66$21,900$9,7500JoeyF23-Jan-46$27,900$12,750115RamayaF13-Feb-46$24,000$13,500244RamanaF7-Feb-50$30,300$16,500143SureshM11-Jan-66$28,350$12,00026KadirM17-Jul-60$27,750$14,25034KusumF26-Feb-49$35,100$16,800137VeerM29-Aug-62$27,300$13,50066BoscoM17-Nov-64$40,800$15,00024DanM18-Jul-62$46,000$14,25048DanyM20-Mar-56$103,750$27,51070RoneyM19-Aug-62$42,300$14,250103RosyF23-Jan-40$26,250$11,55048LeelaF19-Feb-63$38,850$15,00017MathewM24-Sep-40$21,750$12,750315KarunaF15-Mar-65$24,000$11,10075SabrinaF27-Mar-33$16,950$9,000124

Sheet7A study of job satisfaction was conducted for 4 occupations. The satisfaction was measured using an 18 item questionnaire with each question receiving a response score of 1 to 5 (high score indicating higher satisfaction). The sum of the 18 scores provided an overall satisfaction score for each individual in the sample (total 49 in number).ObservationOccupationSatisfaction Score1Cabinetmaker792Cabinetmaker653Cabinetmaker694Cabinetmaker645Cabinetmaker596Cabinetmaker547Cabinetmaker788Cabinetmaker799Cabinetmaker8410Cabinetmaker6011Lawyer4212Lawyer4213Lawyer3814Lawyer4415Lawyer5316Lawyer7417Lawyer5018Lawyer4819Lawyer4520Lawyer6421Physical Therapist8622Physical Therapist5523Physical Therapist5224Physical Therapist7825Physical Therapist8026Physical Therapist5527Physical Therapist5928Physical Therapist6029Physical Therapist5030Physical Therapist6231Systems Analyst5532Systems Analyst4133Systems Analyst6634Systems Analyst4435Systems Analyst7136Systems Analyst6437Systems Analyst7638Systems Analyst6039Systems Analyst6240Systems Analyst73

Sheet9Demograpic data for 46 Asian countries, 2006-07Country nameTot. Pop.Tot. Male Pop.Tot. Fem. Pop.Pop. in 0-14 yrsPop. in 15-64 yrsPop.>65 yrsMale Pop. in 0-14 yrsMale Pop. in 15-64 yrsMale Pop.>65 yrsFem. Pop. in 0-14 yrsFem. Pop. in 15-64 yrsFem. Pop.>65 yrs

geonametotpoptotmpoptotfpoppop0_14pop15_64pop65pmal0_14mal15_64mal65pfml0_14fml15_64fml65pBahrain520,653301,659218,994164,849344,11711,68784,620210,7756,26480,229133,3425,423Bangladesh109,291,00056,381,00052,910,00047,854,00061,437,000024,366,00032,015,000023,488,00029,422,0000Bhutan1,596,00000000000000Brunei Darussalam267,800141,300126,50092,300168,1007,40047,60089,9003,80044,70078,2003,600Cambodia5,816,4692,909,1382,907,3312,637,0783,031,984147,4071,332,5651,504,90371,6701,304,5131,527,08175,737China1,130,510,638581,820,407548,690,231313,001,854754,515,39262,993,392162,863,598390,295,69228,661,117150,138,256364,219,70034,332,275Georgia5,400,8412,562,0402,838,8011,338,4743,584,418477,949682,3271,721,616158,097656,1471,862,802319,852Hong Kong5,919,0003,015,8002,903,2001,184,4004,192,900541,700615,1002,159,000241,700569,3002,033,900300,000India849,638,000440,455,000409,183,000305,868,000509,041,00034,729,000157,952,000265,082,00017,421,000147,916,000243,959,00017,308,000Indonesia179,247,78389,375,67789,872,10665,690,343106,801,9196,751,10633,733,08152,497,7173,142,67431,957,26254,304,2023,608,432Iran55,837,16328,768,45027,068,71324,723,87429,164,7311,890,19312,669,89814,996,6421,065,75312,053,97614,168,089824,440Iraq17,250,2678,864,1638,386,1047,678,0748,984,018588,1753,942,8084,639,396281,9593,735,2664,344,622306,216Israel5,123,5002,543,0002,580,5001,550,2003,094,800478,600795,4001,537,300210,000754,9001,556,900268,400Japan124,451,93861,095,66763,356,27121,364,03186,845,46016,242,44710,954,26143,547,2656,594,14110,409,77043,298,1959,648,306Jordan4,012,0002,054,0001,958,0001,713,1002,198,600100,300883,2001,116,80054,000829,9001,081,80046,300Kazakhstan16,721,1138,115,8578,605,2565,247,90610,474,265998,9422,659,5865,158,149298,1222,588,3205,316,116700,820Korea Dem. People's Rep.23,048,00000000000000Korea, Republic of43,663,40521,978,67721,684,72810,832,38630,547,6172,283,4025,653,64715,473,943851,0875,178,73915,073,6741,432,315Kuwait2,142,6001,210,575932,025784,2141,332,57525,811395,767801,69313,115388,447530,88212,696Kyrgyzstan4,451,8242,183,0792,268,7451,673,6542,550,132228,038847,3841,258,92276,773826,2701,291,210151,265Lebanon2,126,3251,080,0151,046,310906,4501,112,010107,865463,410562,63553,970443,040549,37553,895Malaysia18,180,8539,164,1139,016,7406,658,26610,808,849713,7383,425,9415,408,738329,4343,232,3255,400,111384,304Maldives238,363122,045116,318111,571119,7377,05557,05860,7594,22854,51358,9782,827Mongolia2,043,40000855,0001,105,40083,000000000Myanmar38,541,11919,107,65019,433,46914,380,35522,669,7551,491,0097,178,12611,207,019722,5057,202,22911,462,736768,504Nepal17,143,5038,819,6888,323,8157,243,8989,384,548515,0573,775,4884,774,006270,1943,468,4104,610,542244,863Oman2,017,59100000000000Pakistan84,253,64444,232,67740,020,96737,516,63443,175,8903,561,12019,392,17422,794,1852,046,31818,124,46020,381,7051,514,802Papua New Guinea3,727,2501,928,1201,799,1301,504,5602,131,51091,180770,2601,110,78047,080734,3001,020,73044,100Philippines62,868,21231,585,39031,282,82224,036,28736,642,2212,189,70412,285,90918,296,3951,003,08611,750,37818,345,8261,186,618Qatar369,079247,852121,227102,452262,7643,77052,610192,9802,18949,84269,7841,581Russian Federation148,310,17469,562,47478,747,70033,314,75398,913,41616,082,00516,960,59948,099,9154,501,96016,354,15450,813,50111,580,045Saudi Arabia17,119,00000000000000Singapore2,873,8001,449,9001,423,900663,0002,024,700186,100343,3001,022,80083,800319,7001,001,900102,300Sri Lanka17,619,0008,981,0008,638,0006,203,00010,655,000761,0003,160,0005,419,000402,0003,043,0005,236,000359,000Syrian Arab Rep.13,393,0006,842,0006,551,0006,590,0006,217,000586,0003,411,0003,136,000295,0003,179,0003,081,000291,000Taiwan20,878,00000000000000Tajikistan5,092,6032,530,2452,562,3582,186,5852,712,536191,9081,107,4181,347,73474,1771,079,1671,364,802117,731Thailand57,760,00028,948,00028,812,00018,069,00037,340,0002,351,0009,179,00018,717,0001,052,0008,890,00018,623,0001,299,000Turkmenistan3,522,7171,735,1791,787,5381,428,4051,962,581131,731721,422967,91245,845706,983994,66985,886United Arab Emirates862,000613,700248,300227,100621,40013,500119,100486,9007,700108,000134,5005,800Uzbekistan19,810,0779,784,15610,025,9218,083,20210,922,650803,8644,088,2115,412,404283,3703,994,9915,510,246520,494Yemen12,301,9706,104,9406,197,0306,377,2305,551,700373,0403,264,6002,662,340178,0003,112,6302,889,360195,040Afghanistan15,513,2677,962,3977,550,8707,146,5757,791,404575,2883,610,6304,014,894336,8733,535,9453,776,510238,415Vietnam64,375,76231,230,73733,145,02525,222,59836,112,5083,034,30312,914,42717,109,5461,203,21212,308,17119,002,9621,831,091Laos2,962,0001,499,0001,463,0001,236,0001,649,00077,000625,000836,00038,000611,000813,00039,000

geonametotpoptotmpoptotfpoppop0_14pop15_64pop65pmal0_14mal15_64mal65pfml0_14fml15_64fml65pCountry nameTot. Pop.Tot. Male Pop.Tot. Fem. Pop.Pop. in 0-14 yrsPop. in 15-64 yrsPop.>65 yrsMale Pop. in 0-14 yrsMale Pop. in 15-64 yrsMale Pop.>65 yrsFem. Pop. in 0-14 yrsFem. Pop. in 15-64 yrsFem. Pop.>65 yrs