Please assist with the following questions with the answers 26. The annual numbers of fatal traffic motor accidents are monitored inthree different geographical regions, with the results given in Table 5.14.Two analysts are asked to predict the number of fatal traffic accidentsfor Region A for next year. Analyst 1 would like to like to use theempirical Bayes Model 1 to make a prediction. Analyst 2 is going to usea Bayesian approach assuming the number of annual traffic accidents isa Poisson variable with parameter A, and where she can assume priorknowledge of A summarized by a gamma I (54, 3) distribution. Find thepredictions which the two analysts would make in this situation!TABLE 5.14Annual fatal traffic accidents.Year →>> 123 4 5 6Region A141712 1918 16Region B213216717 33Region C117981213

To solve this problem, we need to find the predictions made by Analyst 1 and Analyst 2 using two…

Answered: 26. The annual numbers of fatal traffic…

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter7: Distance And Approximation

Section7.3: Least Squares Approximation

Problem 31EQ

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9) The following results are from a regression where the dependent variable is GRADUATION RATE and the independent variables are % OF CLASSES UNDER 20, % OF CLASSES OF 50 OR MORE, STUDENT/FACULTY RATIO, ACCEPTANCE RATE, 1ST YEAR STUDENTS IN TOP 10% OF HS CLASS. The data were split into 2 samples and the following regression results were obtained from the split data. a) What is heteroscedasticity? (b) Why is heteroscedasticity a problem? c) Based on a comparison of the two sets of output, does it appear that there is heteroscedasticity in the data set? Explain. Be sure to write down your null and alternative hypothesis, calculate the test statistic, and find your critical value (test at the 5% level of significance).
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A weight-loss program wants to test how well their program is working. The company selects a simple random sample of 51 individual that have been using their program for 15 months. For each individual person, the company records the individual's weight when they started the program 15 months ago as an x-value. The subject's current weight is recorded as a y-value. Therefore, a data point such as (205, 190) would be for a specific person and it would indicate that the individual started the program weighing 205 pounds and currently weighs 190 pounds. In other words, they lost 15 pounds. When the company performed a regression analysis, they found a correlation coefficient of r = 0.707. This clearly shows there is strong correlation, which got the company excited. However, when they showed their data to a statistics professor, the professor pointed out that correlation was not the right tool to show that their program was effective. Correlation will NOT show whether or not there is…
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