QUESTION FOUR(a) Three suppliers provide the following data on defective spare parts.SupplierPart QualityMinor Defect3186ABсGood90170135Major Defect779use α=0.05 and test for independence between supplier and spare part quality.What does the result of your analysis tell the purchasing department?

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Answered: QUESTION FOUR (a) Three suppliers…

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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2. The x values and standardized residuals for the chlorine flow/etch rate data of Exercise 52 (Section 12.4) are displayed in the accompanying table. Construct a stan- dardized residual plot and comment on its appearance. 1.50 2.00 2.50 x e* x e* 1.50 .31 3.00 .73 1.02 3.50 -1.36 -1.15 3.50 1.53 -1.23 4.00 .07 2.50 .23
(3-B is needed to answer it I am only asking for question 4.) 3) You go out and collect the following estimates of earthworms / acre:54,276 57,378 51,108 66,190 66,232 59,018 57,159These data yield the following: ̄y = 59,765.86, and s = 5,689.606a) Construct a 90% CI for these data.b) Construct a 99% CI for these data.c) Darwin once estimated that an acre of soil had about 50,000 worms in it. Is his estimateconsistent with the data above? (Historical note: His estimate was considered way too high inhis day). 4) Consider the results of 3(b). Notice that all the data fit within the 99% confidence interval. Is thisusually the case (in other words, will a 99% CI contain most of the observations)?Caution: a lot of people get this wrong! Here's a hint: suppose you had measured the worms in6000 acres (instead of just 7). What happens to the confidence interval? If you're not sure,substitute 6,000 for 7 in your calculation for (b) to see what happens.
1. (30 Points) Consider the following table where the production quantity of a welding process is presented for different pressure levels (low, medium, and high). By using 5% significance level, test whether the pressure level has an impact on the average production amount. Explicitly show all of your computations and clearly demonstrate how you reach your conclusion. Low Medium High 31 35 25 25 32 34 33 33 35 41 30 33 32 37 39
6. In a field experiment, the earth worm densities observed in different sites with varying soil moisture regimes are given below. Is there any relationship between the soil moisture and earth worm densities: Moisture % 6 25 12 8 16 20 30 22 27 31 Earth worm density (No./m2) 0 5 3 14 10 12 14 6
5. The following results were obtained from a multiple regression analysis . Conclusion of the test of significance of the model at 5% level is A. the model is insignificant . B. not enough information to make conclusion . C. model is significant . D. None
26. Earlier in this chapter we described a study by Bartholow and Anderson (2002) examining how the experience of violence in video games influenced ag- gressive behavior for males and females. Their results suggest that increased violence increase aggressive behavior for males but has little or no effect for fe- males. The following data are measures of aggressive behavior similar to the results obtained in the study. Nonviolent Game Violent Game Female Male 3 6 2 2 4 7 9 9 4 8 10 8 9 4 5 8 4 6 12 16 13 17 13 13 a. Use an ANOVA with a = .05 to evaluate the data. Describe the effect of the violent game compared with a nonviolent game on the aggressive behavior for males and for females. b. Calculate the effect size (n²) for each main effect and for the interaction.
12. DETAILS ASWSBE14 14.E.021. MY NOTES ASK YOUR TEACHER PRACTICE ANOTHER An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume Total Cost (units) ($) 400 4,100 450 5,000 550 5,500 600 5,900 700 6,500 750 7,000 (a) Use these data to develop an estimated regression equation that could be used to predict the total cost for a given production volume. (Round your numerical values to two decimal places.) (b) What is the variable cost (in dollars) per unit produced? (c) Compute the coefficient of determination. (Round your answer to three decimal places.) What percentage of the variation in total cost can be…
You conducted additional studies with these men and found the following: The RR for those who drank one drink per day was 1.50 (95% CI:1.32-1.67) in comparison to the abstainers. For those men who drank three or more drinks per day the RR compared to the abstainers was 4.20 (95% CI 2.68-5.85). Which one of Hill’s criteria does this illustrate? Explain.
I want the results of understanding these tables ?
4. A psychologist noted that people have more difficulty sleeping in a bright room than in a dark room. She measured whether the intensity of the light could predict the time it took a sample of four participants to fall asleep. The data for this hypothetical study are listed in the following table. Intensity of Light (X) Time it Took to sleep (Y) 5. 10 10 18 20 30 40 25 M = 18.75 M = 20.75 S= 15.48 S = 8.69 r= .68 Create a scatter plot of the data b. Calculater and r2 c. Report results in APA style. d. What do results mean? a.
1. A study of the relation between the waistline and percent body fat in men yielded the data shown (waistline measurement in inches). waistline (x) 34.7 46.5 32.8 41.3 29.8 39.3 35.7 29.0 percent fat (y) 21.8 33.6 13.4 27.1 13.7 30.2 18.5 11.2 x = 36.1375 y = 21.1875 SSxx = 248.53875 SSay = 332.67375 SSyy = 494.30875 (a) Find the proportion of the variability in percent body fat that is accounted for by the size of the waistline. Explain fully. (b) Find the regression line for predicting y from x. (c) Construct a 95% confidence interval for the average percent body fat of all men whose waistline size is 34.0 inches. (d) test HO: Beta1 is 0 vs. Ha : Beta1 is not 0, compute the appropriate test statistic and p-value, then make your decision at a = 0.05. (e) Construct a 90% confidence interval for beta1. (f) Compute a 90% confidence interval for the average percent fat when waistline is 35.
A survey collects demographic, socioeconomic, dietary, and health-related information on an annual basis. Here is a sample of 20 observations on HDL cholesterol level (mg/dl) obtained from the survey (HDL is "good" cholesterol; the higher its value, the lower the risk for heart disease). 36 46 38 48 51 53 66 50 50 85 37 45 32 38 44 62 94 34 29 47 (a) Calculate a point estimate (in mg/dl) of the population mean HDL cholesterol level. 49.5 mg/dl (b) Making no assumptions about the shape of the population distribution, calculate a point estimate (in mg/dl) of the value that separates the largest 50% of HDL levels from the smallest 50%. 44 X mg/dl (c) Calculate a point estimate (in mg/dl) of the population standard deviation. (Round your answer to three decimal places.) 18.46 X mg/dl (d) An HDL level of at least 60 is considered desirable as it corresponds to a significantly lower risk of heart disease. Making no assumptions about the shape of the population distribution, estimate the…

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