Which would be the most effective method to determine if the mean diameter of the supplier’s products is not more than 5 centimeters. Regression analysis Confidence interval Hypothesis test Binomial distribution

Which would be the most effective method to determine if the mean diameter of the supplier’s products is not more than 5 centimeters. Regression analysis Confidence interval Hypothesis test Binomial distribution

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

How would you interpret this data?
7) Below is a multiple regression in which the dependent variable is market value of houses and the independent variables are the age of the house and square footage of the house. The regression was estimated for 42 houses. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total df 2 39 41 0.745495 0.555762 0.532981 7211.848 42 SS 2537650171 2028419591 4566069762 Coefficients Standard Error MS 1.27E+09 52010759 F 24.39544 Significance F 1.3443E-07 Upper 95% t Stat P-value Lower 95% Intercept 47331.38 13884.34664 3.408974 0.001528 19247.6673 House Age -825.161 607.3128421 -1.35871 0.182046 -2053.5662 Square Feet 40.91107 6.696523994 6.109299 3.65E-07 27.3660835 7A. What is the estimated regression equation for determining the market value of houses? 7B. Discuss tests of significance of the regression 7C. What percentage of the variation in the dependent variable, Market Value, is explained by the regression…
Percentage variance and turkey HSD
Dex Research Limited conducted a research to investigate consumer characteristics that can be used to predict the amount charged by credit card users. The following multiple regression output is based on a data collected by this research company on annual income, household size and annual credit card charges for a sample if 50 consumers. Regression Statistics Multiple R 0.9086 R Square A Adjusted R Square 0.8181 Standard Error 398.091 Observations B ANOVA df SS MS F Significance F Regression 2 C E G 1.50876E-18 Residual D 7448393 F Total 49 42699149 Coefficients Standard Error t Stat P-Value Intercept 1304.9048 197.6548 6.6019 3.28664E-08 Income ($1000s) 33.1330 3.9679 H 7.68206E-11 Household size 356.2959 33.2009 10.7315 3.12342E-14 a. Complete the missing entries from A to H in this outputb. Estimate the annual credit card charges…
21. Least-squares OK? Following is a residual plot produced by MINITAB. Was it appropriate to compute the least-squares regression line? Explain. Residuals Versus x -2 -3 5.0 5.5 6.0 6.5 7.0 7.5 8.0 Residual
Chapter 9, Section 2, Exercise 032 Use the following ANOVA table for regression to answer the questions. Response: Y Source DF Sum Sq Mean Sq F-value Pr(>F) Regression 1 355.21 355.21 14.76 0.000 Residual Error 359 8641.13 24.07 Total 360 8996.34 Give the F-statistic and p-value.Enter the exact answers.The F-statistic is=The p-value is=
Assuming variance > 1, which of the following must be true? The sample variance is calculated based on the sample size rather than the degrees of freedom The data are normally distributed Standard deviation < variance The model will explain more than 50% of the variance of the dependent variable
3.Which model do you think is the “best” reduced model? Discuss why you choose this model. Analysis of Variance Table (Step back model) Response: rent Df Sum Sq Mean Sq F value Pr(>F) age 1 21000 21000 17.1136 0.0003079 *** sqft 1 35364 35364 28.8196 1.134e-05 *** sd 1 5961 5961 4.8576 0.0362339 * unts 1 8678 8678 7.0722 0.0130049 * gar 1 33364 33364 27.1899 1.713e-05 *** cp 1 7641 7641 6.2269 0.0189934 * Residuals 27 33131 1227 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Step forward model: Response: rent Df Sum Sq Mean Sq F value Pr(>F) age 1 21000 21000 16.6255 0.000406 *** sqft 1 35364 35364 27.9976 1.757e-05 *** sd 1 5961 5961 4.7191 0.039517 * unts 1 8678 8678 6.8705 0.014697 * gar 1 33364 33364 26.4144 2.599e-05 *** cp 1 7641 7641 6.0493 0.021176 *…
1. If we choose the significance level α=0.05, is Gender a significant factor in explaining Salary? Explain. 2. Use Excel’s Data Analysis tool to conduct a multiple regression, using Salary as the dependent variable, and all the rest of variables as independent variables.(Choose confidence level at 95 %.) 3. Based on the multiple regression analysis output, write the estimated regression equation. (Keep 2 decimal places) Salary Gender Years Of Service Years Of Education 52,100 0 5 13 55,015 0 20 13 55,520 0 23 12 43,430 0 7 12 43,813 0 5 12 51,903 0 6 12 54,580 0 24 14 54,913 0 18 12 52,100 0 29 12 50,693 0 14 12 47,878 0 10 12 46,555 0 6 14 47,878 0 7 16 47,878 0 9 12 54,913 0 16 13 50,123 0 4 13 50,693 0 20 12 48,933 0 29 12 58,270 0 12 12 50,538 0 5 13 48,933 0 12 12 45,078 0 5 12 47,878 0 5 14 53,508 0 24 12 42,250 0 1 16 53,508 1 8 15 42,250 1 3 15 47,808 1 1 13 50,180 1 11 13 44,163 1 9 10 41,718 1 3 10 47,878…
It is claimed that the mean household size in the River Terrace neighbourhood is 3.5 persons. A random sample of 25 households is taken. What is the number of cases for this study 52 3.5 48 25 24
After performing an ANOVA analysis, which of the following tests are performed in order to determine whether the means of specific categories are significantly different from each other? Goodness-of-fit Linear regression Bonferonni Comparing proportions