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Multiple choice: Select the best answer for Exercises 21 to 26.What is the correlation between selling price and appraised value?(a) 0.1126 (c) -0.861 (e) -0.928(b) 0.861 (d) 0.928
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In statistics, this correlation is often represented by the letter 'r', also known as the correlation coefficient. Show more…
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Multiple choice: Select the best answer for Exercises 21 to 26. Is there significant evidence that selling price increases as appraised value increases? To answer this question, test the hypotheses (a) $H_{0} : \beta=0$ versus $H_{a} : \beta > 0$ (b) $H_{0} : \beta=0$ versus $H_{a} : \beta < 0$ (c) $H_{0} : \beta=0$ versus $H_{a} : \beta \neq 0$ (d) $H_{0} : \beta>0$ versus $H_{a} : \beta=0$ (e) $H_{0} : \beta=1$ versus $H_{a} : \beta > 1$
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Inference for Linear Regression
Multiple choice: Select the best answer for Exercises, which are based on the following information. To determine property taxes, Florida reappraises real estate every year, and the county appraiser's Web site lists the current "fair market value" of each piece of property. Property usually sells for somewhat more than the appraised market value. We collected data on the appraised market values $x$ and actual selling prices $y$ (in thousands of dollars) of a random sample of 16 condominium units in Florida. We checked that the conditions for inference about the slope of the population regression line are met. Here is part of the Minitab output from a least-squares regression analysis using these data. ${ }^{13}$ $$ \begin{array}{lllll} \text { Predictor } & \text { Coef } & \text { SE Coef } & \text { T } & \text { P } \\ \text { Constant } & 127.27 & 79.49 & 1.60 & 0.132 \\ \text { Appraisal } & 1.0466 & 0.1126 & 9.29 & 0.000 \\ \mathrm{~S}=69.7299 & \mathrm{R}-\mathrm{Sq}=86.1 \% & \mathrm{R}-\mathrm{Sq}(\mathrm{adj}) & =85.1 \% \end{array} $$ The equation of the least-squares regression line for predicting selling price from appraised value is (a) price $=79.49+0.1126$ (appraised value). (b) price $=0.1126+1.0466$ (appraised value). (c) price $=127.27+1.0466$ (appraised value). (d) price $=1.0466+127.27$ (appraised value). (e) price $=1.0466+69.7299$ (appraised value).
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