Topic1 - Example: Price Analysis for Diamond Rings in...

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Example: Price Analysis for Diamond Rings in Singapore Variables Response Variable: Price in Singapore dollars (Y) Explanatory Variable: Weight of diamond in carats (X) Goals Create a scatterplot Fit a regression line
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diamond.sas (input) data diamonds; input weight price @@; cards; .17 355 .16 328 .17 350 .18 325 .25 642 .16 342 .15 322 .19 485 .21 483 .15 323 .18 462 .28 823 .16 336 .20 498 .23 595 .29 860 .12 223 .26 663 .25 750 .27 720 .18 468 .16 345 .17 352 .16 332
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diamonds.sas (print out) proc print data=diamonds; run; Obs weight price 1 0.17 355 2 0.16 328 3 0.17 350 47 0.26 693 48 0.15 316
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diamonds.sas (scatterplot) proc sort data=diamonds1; by weight; symbol1 v=circle i=sm70; title1 'Diamond Ring Price Study'; title2 'Scatter plot of Price vs. Weight with Smoothing Curve'; axis1 label=('Weight (Carats)'); axis2 label=(angle=90 'Price (Singapore $$)'); proc gplot data=diamonds1; plot price*weight / haxis=axis1 vaxis=axis2; run;
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diamonds.sas (scatterplot, cont)
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diamonds.sas (linear regression line) symbol1 v=circle i=rl; title2 'Scatter plot of Price vs. Weight with Regression Line'; proc gplot data=diamonds1; plot price*weight / haxis=axis1 vaxis=axis2; run;
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diamonds.sas (linear regression) proc reg data=diamonds; model price=weight/clb p r; output out=diag p=pred r=resid; id weight; run;
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diamonds.sas (linear regression, cont) Analysis of Variance
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diamonds.sas (linear regression, cont) proc print data=diag; run; Output Statistics Dependent Predicted Std Error Std Error Obs weight Variable Value Mean Predict Residual Residual 1 0.17 355.0000 372.9483 5.3786 -17.9483 31.383 2 0.16 328.0000 335.7381 5.8454 -7.7381 31.299
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diamond.sas (Residual plot) symbol1 v=circle i=NONE;
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Topic1 - Example: Price Analysis for Diamond Rings in...

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