BASIC STATISTICS STAT 220
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This 5 page Class Notes was uploaded by Providenci Mosciski Sr. on Wednesday September 9, 2015. The Class Notes belongs to STAT 220 at University of Washington taught by Staff in Fall. Since its upload, it has received 79 views. For similar materials see /class/192512/stat-220-university-of-washington in Statistics at University of Washington.
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Date Created: 09/09/15
LINEAR REGRESSION The Leaning Tower of Pisa is an architectural wonder Engineers concerned about the towers stability have done extensive studies of its increasing tilt Measurements of the lean of the tower over time provide much useful information The following table gives measurements for the years 1975 to 1987 The lean represents the difference between where a point on the tower would be if the tower were straight and where it actually is The lean is measured in meters Year 1975 1976 1977 1978 1979 1980 1981 Lean 29642 29644 29656 29667 29688 29696 Year 1982 1983 1984 1985 1986 1987 Lean 29698 29713 29717 29725 29742 29757 AverageYear 1981 AverageLean 2969 SDYear 3742 SDLean 00035 7 0994 a What does the correlation coef cient 7quot tell us about the relationship be tween time as measured by year and lean as measured in meters for the Tower of Pisa 77mm omd feom om S tronaiy M50C QQJ MA FoSp hmY 50 145 time hCV GMQSI 50 Joes a n b Predict the amount of lean we would expect to see in 2009 Y can x 4dr 1 00035 2 Y ILQon V x 00 7 WW mW 37 A36 2739 3X QOOQIWYI ET m gt W 1995 02 50 590 39 300 Xqvemoe of X bx gal 31 o W 0m 25053 1127 000930 x pkb f39xj f 360 quot K 32 refer c What is a potential problem With making a prediction for 2009 100 01 5 we Dan65 ng the V mse 04C years in our 56 Lil 2 5 ngur 039 43er N 0l TAL rePMJ ole Jaa39 a comJ til3994 Slahhcl cmntf acrom I a 300 d What is the probability that the lean Will be more than 3 meters in 2009 w almi C w em 0 Le 61 Mefeyj From 77w s ed wt39tma Um Vera n t 200 is 3 MA by M VV0V th OLWS l Tquot x5065 WuODQBS g 0000 T G Lemx m got J 7 K I 43015 3 O M l Sogqooon 1315 Ems A 000033quot 339 55 7 f 3001 TLbfPJLaAr39ty W 42 e 0 will Le mzro Tame QQW tam ama c 6 200g F aFkdkim4ey amp439 e Answer part q gain but now for n measured 1n centimeters If 0 wquot what okraou fak 391 antee55 SJ CL hjC WD ies Owl M k tfrmquot Ad39s AU am 19 Ag CGV VG IL am Zoe Idemf 3 The director of admissions of a small college administered a newly designed en trance test to 20 students selected at random from the new freshman class in a study to determine whether a students grade point average GPA at the end of the freshman year can be predicted from the entrance test score The results of the study follow AverageGPA 25 AverageTest 5 SDGPA 0701 SDTest 0675 7 0809 a Predict the GPA for a randomly selected freshman We Lowe no informwem 0490 15996 S 0 S 6 Our bes gkacs is the Net03 b For your answer to part a what would you predict the student s test score to be What does this tell us about the regression line X GPA vilarch 1 s lt15st 1 In 25 y eST Score 1 r 5 2 S s 75 gt N 0 0675 WC VOWZJ yV aficf lxe Simeth 56 Score a 4e 5 7135 ixS us M14 e foil1 a whang I S Ola Ate V Q r ESS39bll quotquotv c What is the RMS error for predicting GPA from entrance test score 3 5 95 SCore error ma 39 50 if H OJOCia 39 0 70113999 d For a student with a GPA of 30 What is the probability that his or her entrance test score was under 5 7C which 5 jinn to 19 39625 6 SCOT398
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