Given the regression output below and a significance level of 99%, can we rejectthe null hypothesis that bl=0?call:Im(formula = Sales - spend, data = dataset)Residuals:Min1Q Median3Q258 1726мах-3385 -20973034coefficients:Estimate std. Error t value Pr(>|t|)(Intercept) 1383.4714 1255. 2404 1.102 0.2960.1625 65. 378 1.71e-14 ***Spend10. 6222signif. codes: 0 ****' 0.001 **' 0.01 **' 0.05 '.' 0.1 ''1Residual standard error: 2313 on 10 degrees of freedomMultiple R-squared: 0.9977, Adjusted R-squared: 0.9974F-statistic: 4274 on 1 and 10 DF, p-value: 1.707e-14YesCannot determine with the available dataNo

Given that p-value =0.000 Level of significance =0.01

Given the regression output below and a significance level of 99%, can we reject the null hypothesis that bl=0? call: Im(formula = Sales - spend, data - dataset) Residuals: Min -3385 -2097 1Q Median 258 30 мах 1726 3034 coefficients: Estimate std. Error t value Pr(>[t|) 0.296 (Intercept) 1383. 4714 1255.2404 1.102 Spend 10. 6222 0.1625 65. 378 1.71e-14 *** signif. codes: 0 ***** 0.001 ***' 0.01 **' 0.05 '.' 0.1 ·'1 Residual standard error: 2313 on 10 degrees of freedom Multiple R-squared: 0.9977, Adjusted R-squared: 0.9974 F-statistic: 4274 on 1 and 10 DF, p-value: 1.707e-14 Yes Cannot determine with the available data No

Given the regression output below and a significance level of 99%, can we reject the null hypothesis that bl=0? call: Im(formula = Sales - spend, data - dataset) Residuals: Min -3385 -2097 1Q Median 258 30 мах 1726 3034 coefficients: Estimate std. Error t value Pr(>[t|) 0.296 (Intercept) 1383. 4714 1255.2404 1.102 Spend 10. 6222 0.1625 65. 378 1.71e-14 * signif. codes: 0 * 0.001 *' 0.01 **' 0.05 '.' 0.1 ·'1 Residual standard error: 2313 on 10 degrees of freedom Multiple R-squared: 0.9977, Adjusted R-squared: 0.9974 F-statistic: 4274 on 1 and 10 DF, p-value: 1.707e-14 Yes Cannot determine with the available data No

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

Problem 4GP

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