Answer Happy

If you plan to do this optional HW, your HW must be hand written on unlined white A4 (9*11, that is the same type of paper we use for print or copy in most cases) paper with all steps shown including but are not limited to graphs, and statements. Otherwise, students will lose points accordingly. Please treat each question in your homework as a problem solving (or essay) question, which means you need to show detailed steps. To make it clear, you must explain the process how you obtain any number that appears in your submission but is not given by the question. Any printed (typed) homework is graded as zero. In each homework, students are requested to put their answers in the same order as the original questions, or you lose 10 points for that assignment. No late submission is accepted, no email submission is accepted. Please keep at least 4 decimals for your answer. You are NOT allowed to use Excel (statistical software or package) to get the answer. You can only use the tables provided by this class. 1 In a completely randomized experimental design, we want to test whether all populations have the same mean. 10 experimental units were used for each of the 5 treatments. Part of the ANOVA table is shown below. Please fill in the blanks for the following ANOVA table Dr SS MS F Between treatment 160 Error Total 1000 Based on the result of your ANOVA, use the p-value approach to test whether all populations have the same mean at the 0.05 significance level and explain your results? 2 Three different models of automobiles (A, B, and C) were compared for gasoline consumption For each model of car, ten cars were randomly selected and subjected to standard driving procedures. The average miles/gallon obtained for each model of car and sample standard deviations are shown below. Average Mile Gallon Sample Standard Deviation Car A 40 3 Car B 48 4 Car C 44 3
Use the above data and test to see if the mean gasoline consumption for all three models of cars is the same. Let a -0.05. Show the complete ANOVA table. 3 Multiple regression analysis was used to study the relationship between a dependent variable Y, and three independent variables X., Xand, X.. The following is a partial result of the regression analysis involving 20 observations Coefficients Standard Error Intercept 20.00 5.00 X -12.00 X 9.00 6,00 X -18.00 10.00 3.00 500 ANOVA DF SS MS Regression 100 Residual 1. Compute the coefficient of determination. b. Using both P-value and critical value to perform at test and determine whether or not $3 is significantly different from zero (c 0,05). c. Ata -0.1. Using both P-value and critical value to determine whether or not the regression model is significant 4 Part of an Excel output relating X (independent variable) and Y (dependent variable) is shown below. Fill in all the blanks marked with " Summary Output Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA 0.12 ? ? 4.2 SS 8 2 Regression Residual MS 2 10 F ? 2
Total 15 Intercept Coefficients Standard Error Stat 2.245 -1.2 0.525 1 SS 24 66 5 Shown below is a portion of a computer output for regression analysis relating Y (dependent variable) and X (independent variable) ANOVA df Regression Residual Coefficients Standard Error Intercept -10 5.24 -0.5 0.208 What has been the sample size for the above? Perform at test and determine whether or not X and Y are related. Leta -0.05. Perform an F test and determine whether or not X and Y are related. Let a -0.01. d. Interpret the meaning of the value of -10 and -0.5 in the table above. X c.