3. Setup: The data set "Healthy Breakfast" contains, among other variables, the Consumer Reports ratings of 77 cereals and the number of grams of sugar contained in each serving. (Data source: Free publication available in many grocery stores. Data set available through the Statlib Data and Story.) Considering "Sugars" as the explanatory variable and "Rating" as the response variable generated the following regression line: Rating = 59.3-2.40 - Sugars. and the ANOVA table Source Regression Error Total SS df MS 8654.7 1 8654.7 102.35 6342.1 75 84.6 14996.8 76 F Questions: (a) Write down the simple linear regression model and its model assumption. (b) State the null and alternative hypotheses for the model. Based on the ANOVA table, draw conclusion based on the p-value for the test. (c) Obtain szz and the standard error se (3₁) to construct the 95% confidence interval for $₁.
3. Setup: The data set "Healthy Breakfast" contains, among other variables, the Consumer Reports ratings of 77 cereals and the number of grams of sugar contained in each serving. (Data source: Free publication available in many grocery stores. Data set available through the Statlib Data and Story.) Considering "Sugars" as the explanatory variable and "Rating" as the response variable generated the following regression line: Rating = 59.3-2.40 - Sugars. and the ANOVA table Source Regression Error Total SS df MS 8654.7 1 8654.7 102.35 6342.1 75 84.6 14996.8 76 F Questions: (a) Write down the simple linear regression model and its model assumption. (b) State the null and alternative hypotheses for the model. Based on the ANOVA table, draw conclusion based on the p-value for the test. (c) Obtain szz and the standard error se (3₁) to construct the 95% confidence interval for $₁.
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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VIEWStep 3: State the null and alternative hypotheses for the model and draw conclusions
VIEWStep 4: Obtain Sxx and the standard error se(β1^) to construct the 95% confidence interval for β1
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