Name Date Three different makes of cars were tested for fuel efficiency. For each make of car fifteen automobiles were randomly selected and subjected to standard driving procedures. Using the data from the following results compute the between treatments estimate of o² and the within treatments estimate of o?. At the a=.05 level of significance, can the null hypothesis, that all fuel economies are the same, be rejected? Construct the ANOVA table for this data. (Use the formulas to compute the needed values by hand.) 1. Ford Chevrolet Chrysler Miles Per Gallon 32 29 34 Standard Deviation 4 APR 17 étv 4 3. w/

7. Consider the following ANOVA table for a multiple regression model: Source df SS MS F Regression 118.8475 59.42375 40.92168993 Residual 13.0692 1.452133333 Total 11 131.9167 a) Complete the remaining entries in the table. e) Test the significance of the overall regression model using a=0.05.

The data below pertain to the flourometric determination of the riboflavin content of dired collard leaves. Two factors were measured: 1) the size of the sample (.25 g vs 1.0 g) and 2) the effect of the inclusion of a clarification step in the determination process (with vs without). Do either of these factors have a significant effect on the apparent riboflavin concentration? Analyze these data used a nested ANOVA using the clarification step as the top level. Put your answers in standard format: hypotheses and conclusions relative to the hypotheses.      Size   Clarification Step 0.25g 1.00g Without 39.5 38.6   43.1 39.5   45.2 33 With 27.2 24.6   23.2 24.2   24.8 22.2

Consider the following measurements of blood hemoglobin concentrations (in g/dL) from three human populations at different geographic locations: population1 = [ 14.7 , 15.22, 15.28, 16.58, 15.10 ] population2 = [ 15.66, 15.91, 14.41, 14.73, 15.09] population3 = [ 17.12, 16.42, 16.43, 17.33] Perform ANOVA to check if any of these populations have different mean hemoglobin concentrations.  (Assume that all the ANOVA requirements such as normality, equal variances and random samples are met.)  After you perform ANOVA perform a Tukey-Kramer post-hoc test at a significance level of 0.05 to see which populations actually have different means.  As usual, round all answers to two digits after the decimal point.  (Make sure you round off to at least three digits any intermediate results in order to obtain the required precision of the final answers.) For any questions, which ask about differences in means or test statistics, which depend on differences in means provide absolute values.  In…