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The CEO of the company thinks that this statistical analysis strongly suggests that increasing the number of baths by 1 will increase, on average, the house sale price by at least 3 thousands of dollars. To assess the plausibility of his claim, a hypothesis testing procedure was performed. (i) Write down the hypotheses, (ii) carry out the test to assess the CEO's claim at level a = .1, and (iii) state your conclusion in a sentence form.

The CEO of the company thinks that this statistical analysis strongly suggests that increasing the number of baths by 1 will increase, on average, the house sale price by at least 3 thousands of dollars. To assess the plausibility of his claim, a hypothesis testing procedure was performed. (i) Write down the hypotheses, (ii) carry out the test to assess the CEO's claim at level a = .1, and (iii) state your conclusion in a sentence form.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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A large house building company is interested in the relation between sale prices of houses y (in thousands of dollars) to taxes x1 (in thousands of dollars), number of baths x2, and age of home x8 (in years). To this end, the measurements of these four variables were taken from a sample of properties and a linear model was run. A fragment of the R output of the regression is shown below. Coefficients: Estimate Std. Error t value Pr(>|t|) Secollant x1 (Intercept) 7.4226 0.1964 -4.5571 0.5429 4.1630 1.783 0.0863. 0.3703 0.530 0.6004 2.5464 -1.790 0.0852 0.7188 0.755 0.4568 x2 x8 Signif. codes: 0*** 0.001 ** 0.01 0.05. 0.11 Jade alun-Residual standard error: 3.323 on 26 degrees of freedom Multiple R-squared: 0.1597, Adjusted R-squared: 0.06276 donda alowe F-statistic: 1.647 on 3 and 26 DF, p-value: 0.2028
Transcribed Image Text:A large house building company is interested in the relation between sale prices of houses y (in thousands of dollars) to taxes x1 (in thousands of dollars), number of baths x2, and age of home x8 (in years). To this end, the measurements of these four variables were taken from a sample of properties and a linear model was run. A fragment of the R output of the regression is shown below. Coefficients: Estimate Std. Error t value Pr(>|t|) Secollant x1 (Intercept) 7.4226 0.1964 -4.5571 0.5429 4.1630 1.783 0.0863. 0.3703 0.530 0.6004 2.5464 -1.790 0.0852 0.7188 0.755 0.4568 x2 x8 Signif. codes: 0*** 0.001 ** 0.01 0.05. 0.11 Jade alun-Residual standard error: 3.323 on 26 degrees of freedom Multiple R-squared: 0.1597, Adjusted R-squared: 0.06276 donda alowe F-statistic: 1.647 on 3 and 26 DF, p-value: 0.2028
The CEO of the company thinks that this statistical analysis strongly suggests that increasing the number of baths by 1 will increase, on average, the house sale price by at least 3 thousands of dollars. To assess the plausibility of his claim, a hypothesis testing procedure was performed. (i) Write down the hypotheses, (ii) carry out the test to assess the CEO's claim at level a = .1, and (iii) state your conclusion in a sentence form. to 2000
Transcribed Image Text:The CEO of the company thinks that this statistical analysis strongly suggests that increasing the number of baths by 1 will increase, on average, the house sale price by at least 3 thousands of dollars. To assess the plausibility of his claim, a hypothesis testing procedure was performed. (i) Write down the hypotheses, (ii) carry out the test to assess the CEO's claim at level a = .1, and (iii) state your conclusion in a sentence form. to 2000
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