il.CENGAGE MINDTAPapter 13 Assignment3.4.5.6.7.9.8.Ebay0.OOOOFP-See What's HotA factorial experiment involving two levels of factor A and three levels of factor B resulted in the following data.Source ofVariationFactor AFactor BInteractionErrorTotalSum ofSquares1976.312482818.63530Test for any significant main effects and any interaction. Use a = 0.05. Round Sum of Squares to the whole number, F value, Mean Square to twodecimals, if necessary, and p-value to four decimals.9573FF Geres 9/O€3Degrees ofFreedom122611Factor A311976.3Mean Square624Pokemon Eestis..1409.3Level 1588.33Level 2Level 111514513595F value3.361.06Factor BLevel 2100762.4117125p-value0.1165Level 355830.40330.1719100156ConclusionNot significantNot significantQ Search this courseNot significantOct 21X6:46?

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Answered: A factorial experiment involving two…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

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ch 11 end. 7: In a bumper test, three test vehicles of each of three types of autos were crashed into a barrier at 5 mph, and the resulting damage was estimated. Crashes were from three angles: head-on, slanted, and rear-end. The results are shown below. Research questions: Is the mean repair cost affected by crash type and/or vehicle type? Are the observed effects (if any) large enough to be of practical importance (as opposed to statistical significance)?
2. Researchers wanted to study physical activity in children, so they gave 74 randomly chosen children a "FitBit" to record how many steps they took each day. Additionally, the scientists recorded each child's Body Mass Index (BMI) and grade in school. Grade was coded as middle or high school. The results of their analysis are below: Table 1 - Factors Contributing to Daily Steps Taken Intercept BMI Grade_middle Estimate 6,350.2 -137.5 1,302.4 SE 316.1 54.9 588.3 a. Calculate the test statistics for each predictor in the model and determine which are significant (you don't have to write full conclusion for each as long as you indicate which are significant). Given: critical value = 1.99 b. Interpret the estimate of Grade_middle in context. c. Suppose a middle-school student with a BMI of 20 took 6,000 steps in a day. Calculate this student's residual.
Section 3.1, question 3
A factorial experiment involving two levels of factor A and three levels of factor B resulted in the following data. Factor B Level 1 Level 2 Level 3 135 86 79 Level 1 165 62 97 Factor A 125 131 116 Level 2 95 109 132 Test for any significant main effects and any interaction. Use a = 0.05. Find the value of the test statistic for factor A. (Round your answer to two decimal places.) Find the p-value for factor A. (Round your answer to three decimal places.) p-value = State your conclusion about factor A. O Because the p-value > a = 0.05, factor A is not significant. O Because the p-value s a = 0.05, factor A is significant. Because the p-value > a = 0.05, factor A is significant. O Because the p-value a = 0.05, factor B is significant. O Because the p-value s a = 0.05, factor B is not significant. Because the p-value a = 0.05, factor B is not significant. Find the value of the test statistic for the interaction between factors A and B. (Round your answer to two decimal places.) Find…
A factorial experiment involving two levels of factor A and three levels of factor B resulted in the following data. Factor B Level 1 Level 2 Level 3 139 86 75 Level 1 169 62 93 Factor A 121 131 120 Level 2 91 109 136 Test for any significant main effects and any interaction. Use a = 0.05. Find the value of the test statistic for factor A. (Round your answer to two decimal places.) Find the p-value for factor A. (Round your answer to three decimal places.) p-value State your conclusion about factor A. Because the p-value > a = 0.05, factor A is not significant. Because the p-value > a = 0.05, factor A is significant. Because the p-value a = 0.05, factor B is not significant. Because the p-value a = 0.05, factor B is significant. O O O O O O O O
c. Which of the following is the correct graph of the given data? -ОА. 10 1012 12 10 O C. 12- 81012 1012 Using the graph, explain the dramatic difference between the answers to parts (a) and (b). Choose the correct answer below. OA. The point (10,10) is not an outier, but it does have a strong effect on the least squares line and the correlation coefficient. OB. The point (10,10) does not have any effect on the least squares line and the correlation coefficient. OC. The point (10,10) is an outler that has a weak effect on the least squares line and the correlation coefficient. OD. The point (10,10) is an outlier that has a strong effect on the least squares line and the correlation coefficient.
pauieidxa aJe Pien aun 2. Consider the following data on the hours of burnout for a sample of 59 lightbulbs 68 70 86 88 62 61 79 92 116 103 68 63 88 81 62 74 62 94 71 70 58 98 98 65 73 71 70 97 94 59 57 90 71 101 78 43 59 67 61 71 96 75 64 76 72 77 74 65 82 86 66 86 96 107 57 97 86 59 83 Describe the shape of the data using coefficient measures based on the moments 3. Ten competitors in a beauty contest are ranked by three judges as follows: Competitors Judges 6. 7 8 9. 10 1|Page
1.) The Test Statistic for this data. (Round answer to 3 decimal places). 2.) The p-value for this sample. (Round answer to 4 decimal places).
QUESTION 2 The following sample of 50 was selected randomly from a large population. Match the following questions with their answers: 3 16 55 75 91 5 16 58 78 92 9 19 60 81 93 9 20 62 84 93 10 20 67 86 93 13 22 72 86 94 15 34 73 86 94 15 37 74 94 16 49 74 94 16 51 75 94 56.72 32.92 Approximately what percent of data is more than the 90th mean st dev 8888 87 87 89 A. 48%
Section 3.1, question 15
5. An article in Agricultural Engineering (December 1964, pp. 672-673) described an experiment in which the daily weight gain of swine is evaluated at different levels of housing temperature. The mean weight of each group of swine at the start of the experiment is considered to be a nuisance factor. The data from this experiment are as follows: Mean Weight (lbs) Housing Air Temperatures (°F) 100 50 60 70 80 90 1.37 1.58 2.00 1.97 1.40 100 0.39 150 1.47 1.75 2.16 1.82 1.14 -0.19 200 1.19 1.91 2.22 1.67 0.88 -0.77 Does housing air temperature affect mean weight gain at a = 0.05?

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