11. To test whether the mean time to mix a batch of adhesive is the same for machines produced by four manufacturers, TiteBondMax obtained Manufacturer A B C D 25 23 25 26 23 21 25 27 21 23 25 26 23 24 21 24 the time (minutes) needed to mix the materials. Test whether the machines have equal mean mixing time at = 0.01.

A. None of the answers are correct. B. The data provide strong evidence against H0: Equal means at pvalue 0.013. The mixing machines are not all equal. C. The data provide extreme evidence against H0: Equal means at pvalue 0.001. The mixing machines are not all equal. D. The data provide insignificant evidence against H0: Equal means at pvalue 0.514. The machine are considered equal. E. The pvalue 0.0001 is extreme evidence that the machines are not all the same. F. The data provide weak evidence against H0: Equal means at pvalue 0.072. Equality of means remains plausible.

hint for Question We state that the evidence against H0 is

Extreme when p value < 0.001 Overwhelming when 0.001 p value < 0.01 Strong when 0.01 p value < 0.05 Weak when 0.05 p value < 0.10 Insignificant when 0.10 p value

12. Given the following contingency table with category labels A, B, C, X, Y, and Z, what is the expected count with 1 decimal place in the joint category of C and X?

X Y Z A 17 10 1 B 15 6 2 C 13 1 5

13. What is the critical value for level of significance and table parameters in

Level of Significance 0.025 Number of Rows 3 Number of Columns 3

A. 5.991 B. None of the answers are correct. C. 11.143 D. 22.307 E. 18.475

hint for Question DF depends on the number of rows and columns of a contingency table

14. Part Quality Supplier Good Minor Defect Major Defect A 100 5 8 B 160 18 4 C 150 7 11

contains Part Quality data of three Suppliers. At = 0.05, does Part Quality depend on Supplier, or should the cheapest Supplier be chosen? A. Pvalue of 0.039 rejects the assumption of independence of Part Quality and Supplier. Further supplier evaluation is recommended. B. Pvalue of 0.008 rejects the assumption of independence of Part Quality and Supplier. Further supplier evaluation is recommended. C. The assumption of independence of Part Quality and Supplier cannot be rejected. Choose the cheapest Supplier. D. None of the answers fit the data. E. Pvalue of 0.0008 rejects the assumption of independence of Part Quality and Supplier. Further supplier evaluation is recommended.

hint for Question Test independence of Supplier and Part Quality.

15. A sales region is divided into five territories, each of which is believed to have equal sales volume. The actual Sales Volume for several sampled days is logged in

Territory A B C D E Sales Volume 110 130 100 106 110

At = 0.05, do the territories have equal Sales Volume?

A. H0: Territories have equal Sales Volume is rejected with pvalue 0.012. The counts are not consistent with the model of equal proportions. Territories have unequal Sales Volume. B. None of the answers are correct C. H0: Territories have equal Sales Volume is rejected with pvalue 0.041. The counts are not consistent with the model of equal proportions. Territories have unequal Sales Volume. D. H0: Territories have equal Sales Volume is not rejected with pvalue 0.334. The counts are consistent with the model of equal proportions. E. H0: Territories have equal Sales Volume is not rejected with pvalue 0.074. The counts are consistent with the model of equal proportions. hint for Question If the territories have equal volume, then they should share the total volume equally. Recall the formula for DF for a tabulation of one row or one column.

16. Scatter plots are used to discover relationships between variables. Using the corresponding measurements of variable1 and variable2 in variable1 variable2 -8.78162 18.34055 7.39749 2.85607 3.75278 6.23950 -3.91953 13.58786 -7.62142 18.08145 -4.59753 12.85170 -3.41580 13.45867 -0.28752 8.95585 -8.37001 18.84054 6.00523 3.95631 -3.85438 13.08315 -2.86084 13.53479 4.42861 4.86409 -1.24050 9.81458 -4.80313 15.31168 -5.14316 14.74720 -7.41768 17.07810 -5.39179 15.51509 2.34057 8.38950 -8.82911 19.72766 -1.77868 11.60777 -8.99293 18.44845 -7.83663 18.07113 1.56835 7.71226 plot variable1 vs. variable2 and describe the correlation between variable1 and variable2.

A. The strength of the relationship is strong, but it is not linear. B. There is no relationship, or the strength of the relationship is very weak C. The relationship is linear, positive, and strong. D. None of the answers accurately characterize the data. E. The strength of the relationship is moderate, linear, and positive. F. The strength of the relationship is moderate, linear, and negative. G. The relationship is linear, negative, and strong.

17. Correlation - Quantitative Evaluation Correlation is used to discover relationships between variables. Evaluate the correlation between the variables in variable1 variable2 -0.21582 0.89369 0.56997 -0.72620 -0.54850 -0.09185 -0.12385 0.50086 0.06975 -0.73607 0.16327 0.88498 -0.72595 -0.27512 0.22500 0.62647 -0.40463 0.92432 0.67652 0.56368 -0.82322 0.73005 0.06747 -0.74824 0.74055 0.79412 -0.71577 -0.04509 -0.82231 -0.70951 -0.47603 0.01573 0.58094 0.51169 -0.58573 0.10376 0.19003 -0.90089 -0.49528 0.04767 0.93083 -0.16886 0.61389 -0.65529 -0.91742 0.25296 -0.60957 -0.24747

What is the correlation?

A. -0.008 B. 0.984 C. -0.991 D. 0.310 E. None of the answers are correct.

18. You are required to setup a predictive equation involving variable 1 and variable 2. First, you plot the variable1 variable2 -0.21582 0.89369 0.56997 -0.726