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Introductory Applied Statistics for Engineers

by: Mrs. Triston Collier

Introductory Applied Statistics for Engineers STAT 324

Marketplace > University of Wisconsin - Madison > Statistics > STAT 324 > Introductory Applied Statistics for Engineers
Mrs. Triston Collier
GPA 3.57


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This 2 page Class Notes was uploaded by Mrs. Triston Collier on Thursday September 17, 2015. The Class Notes belongs to STAT 324 at University of Wisconsin - Madison taught by Staff in Fall. Since its upload, it has received 19 views. For similar materials see /class/205089/stat-324-university-of-wisconsin-madison in Statistics at University of Wisconsin - Madison.


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Date Created: 09/17/15
STAT 324 Discussion 10 TA Jiale Xu Webpage wwwstatwisceduxujialestat324 1 Examples 11 Example 1 Analyze the 77lung77 data in 77lSwR77 package a Consider a two way ANOVA What does the intercept coef cient correspond to b Whats the predicted lung volume for subject 77477 under method 77B c Perform multiple comparisons using TukeyHSD to see which types of methods result in signi cantly different lung volume codes and output str lung lm0lmvolume subj ectmethod lung summary lmlm0 v v v w Coefficients Estimate Std Error t value Prgtt Intercept 317222 019232 16494 14e08 subject2 083333 023555 3538 000538 subject3 010000 023555 0425 068016 subject4 006667 023555 0283 078293 subject5 003333 023555 0142 089027 subject6 060000 023555 2547 002900 methodB 028333 016656 1701 011975 methodC 060000 016656 3602 000483 Residual standard error 02885 on 10 degrees of freedom Multiple R squared 07968 Adjusted R squared 06546 F statistic 5603 on 7 and 10 DF p value 000768 gt predictlm0dataframesubjectquot4quotmethodquotBquot 1 3388889 gt 317222 006667 028333 compute the prediction 1 338888 gt lm00aov vo lume subj ectmethod lung gt TukeyHSDlmOOwhichquotmethodquot Tukey multiple comparisons of means 95 family wise confidence level Fit aovformula volume subject method data lung method diff lwr upr p adj BA 02833333 01732445 07399112 02520218 CA 06000000 01434222 10565778 00122174 CB 03166667 01399112 07732445 01885516 12 Example 2 Analyze 77tlc data in 77lSwR77 package a Take a look at the data7 what7s needed before analysis b Draw a scatter plot matrix of the data ls the logarithm transformation necessary c Fit a model using all the predictors available7 check the result Try to nd a best model codes and output strtlc tlcsexwithtlcfactorsex strtlc v v v w splom tlc 2typecquotgquotquotpquotquotsmoothquot tlcOtlc tlcOwithtlcOdataframelagelogageseXseXlheightlogheightltlclogtlc strtlcO dataframe 32 obs of 4 variables lage num 356 240 248 277 347 sex Factor w 2 levels quot1quotquot2quot 1 1 2 1 1 1 1 2 1 1 lheight num 500 493 500 505 502 ltlc num 122 123 134 136 139 VVVVV splom tlcO 2typecquotgquotquotpquotquotsmoothquot lm1lmltlc tlcO summarylm1 lm2lmltlc sexlheighttlcO summarylm2 lm3steplm1trace0 summarylm3


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