12.7.2Truck Unloading TimesConsider the data set of the times taken to unload a truck at a warehouse given inDS12.2.2. Plot theresiduals against the temperature. Are there any points that might be considered to be outliers? Doesthe residual plot have any patterns that suggest that the fitted regression model is not appropriate?Construct and interpret a normal probability plot.457 25700 124567891012130415Unloading Time (minute)645358594954384868635847Temperature (degrees526864888075596385747166

From the plot, we conclude that the two points , marked as red, can be considered as outliers: These…

Answered: 12.7.2Truck Unloading Times Consider…

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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Absenteeism: Absenteeism can be a serious employment problem. It is estimated that absenteeism reduces potential output by more than 10%. Two economists launched a research project to learn more about the problem. They randomly selected 100 organizations to participate in a 1-year study. For each organization, they recorded the average number of days absent per employee and several variables thought to affect absenteeism. Question: Use the t-tests and the slope coefficient for U/M Rel to describe how the relationship between the union and the management affects absenteeism. (both MLR and t-test are provided below) Data: Wage Pct PT Pct U Av Shift U/M Rel Absent 22477 8.5 57.1 1 1 5.4 29939 1.9 41.5 0 1 4.1 22957 12.2 52.6 1 0 11.5 18888 30.8 65.1 0 1 2.1 15078 6.8 68.8 0 1 5.9 15481 5.1 46.4 0 0 12.9 21481 25.3 38.9 0 1 3.5 29687 9.2 17.2 0 0 2.6 13603 8.4 12.9 0 0 8.6 18303 4.9 18.1 0 1 2.7 20832 23.8 64.4 1 1 6.6 22325 24.1 63.7 1 1 2.1 19964 8.6…
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Answer it correctly and explain well.Typed answer only. Do it fast.
Listed below are altitudes (thousands of feet) and outside air temperatures (°F) recorded during a flight. Find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 95% confidence level with the altitude of 6327 ft (or 6.327 thousand feet). Altitude Temperature a. Find the explained variation. (Round to two decimal places as needed.) 2 55 8 40 13 25 20 - 3 28 - 26 31 - 41 34 - 53
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Exercise 6. Regression Fallacy. Historically, scores on the two midterms had a correlation of 0.48. Suppose that Jeri scored 2.1 standard deviations below the mean on the first midterm. (a) How many standard deviations [above or below?] the mean would you predict for her second midterm?
e) Perform the F Test making sure to state the null and alternative hypothesis.
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Let's study the relationship between brand, camera resolution, and internal storage capacity on the price of smartphones. Use α = .05 to perform a regression analysis of the Smartphones01CS dataset, and then answer the following questions. When you copy and paste output from MegaStat to answer a question, remember to choose to "Keep Formatting" to paste the text. a. Did you find any evidence of multicollinearity and variance inflation among the predictors. Explain your answer using a VIF analysis. b. Copy and paste the normal probability plot for your analysis. Is there any evidence that the errors are not normally distributed? Explain. c. Copy and paste the Residuals vs. Predicted Y-values. Does the pattern support the null hypothesis of constant variance for the errors? Explain. d. Study the residuals analysis. Which observations, if any, have unusual residuals? e. Study the residuals analysis. Calculate the leverage statistic. Which observations, if any, are high leverage…

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