Please assist with the following questions with the answers 7. In a study undertaken to model automobile accident rates for youngadults, a Poisson (regression) GLM model is fitted with linear predictorof the formε = αG + BGx,260GENERALIZED LINEAR MODELSwhere ag and BG are parameters for the factor gender and the vari-ate age (in years). ML estimates of these parameters are given by»F = −0.72, ÔM = −0.54, ®r = −0.06, Ôm = −0.05 where F and Mrepresent females and males, respectively.(a) What is the predicted automobile accident rate for a 25-year-oldmale?(b) Express the ratio of accident rates for females over males as afunction of age. What is the maximum value of this ratio in the[20, 35] age range?

Step 1:The problem provided involves modeling automobile accident rates for young adults using a…

Answered: 7. In a study undertaken to model…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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A regression was run to determine if there is a relationship between the happiness index (y) and life expectancy in years of a given country (x).The results of the regression were: ˆyy^=a+bxa=-1.239b=0.084 (a) Write the equation of the Least Squares Regression line of the formˆyy^= + x(b) Which is a possible value for the correlation coefficient, rr? -0.983 1.173 -1.173 0.983 (c) If a country increases its life expectancy, the happiness index will increase decrease (d) If the life expectancy is increased by 1 years in a certain country, how much will the happiness index change? Round to two decimal places.(e) Use the regression line to predict the happiness index of a country with a life expectancy of 77 years. Round to two decimal places.
A regression was run to determine if there is a relationship between the happiness index (y) and life expectancy in years of a given country (x).The results of the regression were: ˆyy^=a+bxa=-1.778b=0.143 (a) Write the equation of the Least Squares Regression line of the formˆyy^= + x(b) Which is a possible value for the correlation coefficient, rr? -0.853 0.853 -1.931 1.931 (c) If a country increases its life expectancy, the happiness index will decrease increase
"What does the coefficient of determination (R^2) indicate in a linear regression model? A) The correlation between two variables B) The proportion of the variance in the dependent variable that is predictable from the independent variable(s) C) The slope of the regression line D) The intercept of the regression line"
please anwer whatever you are allowed too. Thank you. A regression was run to determine if there is a relationship between the happiness index (y) and life expectancy in years of a given country (x).The results of the regression were: ˆyy^=a+bxa=-1.68b=0.168 (a) Write the equation of the Least Squares Regression line of the formˆyy^= + x(b) Which is a possible value for the correlation coefficient, rr? -1.417 1.417 0.702 -0.702 (c) If a country increases its life expectancy, the happiness index will increase decrease (d) If the life expectancy is increased by 0.5 years in a certain country, how much will the happiness index change? Round to two decimal places.(e) Use the regression line to predict the happiness index of a country with a life expectancy of 69 years. Round to two decimal places.
Suppose you estimated the relationship between the exam scores and class sizes. score^ = b0 + b1*Size + e^ Based on the OLS estimate, you obtain the following standard errors and parameter estimates: b0= 95; se(b0) = 30 ; b1= −1.2; se(b1 ) = 0.4 ; n = 25 a) What kind of relationship exist between the exam scores and the clas sizes? Interpret the regression. b) Conduct the following hypothesis test at the 1% significance level: H0 : b1 ≥ 0 H1 : b1 < 0 In your answer draw the distribution of the test statistic that you use, and clearly define the rejection region(s), indicating the critical value(s).
The monthly premium quoted by an insurance company for a critical illness policy was collected from a sample of 6 adult male smokers at different age. The data for the sample are shown: Age 28 25 50 39 47 31 Premium ($) 75 40 175 125 250 105 Using Age to predict premium, the Linear Regression equation is given by: ŷ =6.556X−112 and r2=0.813y^=6.556X−112 and r2=0.813 a. Identify the independent and Dependent variables. Dependent: Age Premium Independent: Age Premium b. Determine the slope. Slope = Slope = Round to 3 decimal places c. Determine |r||r| . |r|=|r|= Round to 3 decimal places d. Interpret rr : and e. Determine critical r value at 5% significance level and determine if there is a significant linear correlation exists. |r| critical=|r| critical= Round to 3 decimal places Linear Correlation:Linear Correlation: Significant Not Significant f. Predict the monthly premium for a 40 years old adult male smoker.…
Mental development in humans is related to the volume of the part of the brain known as the hippocampus. The given regression output shows the mental development index at age 24 months vs. the hippocampus volume in ml at birth for a representative sample of 17 premature infants. MDI_24 By Vol(ml) 2.5 2.4- 2.3- 2.2- 2.1- 2- 1.9- 1.8- 1.7- 1.6- 1.5- 50 60 70 80 90 100 110 12 Vol(ml) Regression Analysis MDI_24MO = 1.1359094 + 0.0093475*HippoVol Summary of Fit RSquare RSquare Adj S Mean of Response 0.265 0.216 0.223 1.97758 NObservations 17 Analysis of Variance Source Model DF Sum of Squares 1 0.268 Mean Square F Ratio 0.268 5.4023 MDI_24M0
(1) For neighborhoods with more than 66% of schools participating in free school lunch program, the estimated regression model is: crime_rate = 142.5737 - 1.9215(Prop_change_income) - 38.8741(0) - 19.20521(0) = 142.5737 - 1.9215(Prop_change_income) (2) For neighborhoods with 33% to 66% of schools participating in free school lunch program, the estimated regression model is: crime_rate = 142.5737 - 1.9215(Prop_change_income) - 38.8741(0) - 19.20521(1) = 123.36849 - 1.9215(Prop_change_income) (3) For neighborhoods with less than 33% of schools participating in free school lunch program, the estimated regression model is: crime_rate = 142.5737 - 1.9215(Prop_change_income) - 38.8741(1) - 19.20521(0) = 103.69959 - 1.9215(Prop_change_income) Questions: 1. What is difference between models in 1,2,and 3? 2. Which estimated model 1,2, or 3 results in the line with the highest estimated crime rates (the highest positioned line)?
(1) For neighborhoods with more than 66% of schools participating in free school lunch program, the estimated regression model is: crime_rate = 142.5737 - 1.9215(Prop_change_income) - 38.8741(0) - 19.20521(0) = 142.5737 - 1.9215(Prop_change_income) (2) For neighborhoods with 33% to 66% of schools participating in free school lunch program, the estimated regression model is: crime_rate = 142.5737 - 1.9215(Prop_change_income) - 38.8741(0) - 19.20521(1) = 123.36849 - 1.9215(Prop_change_income) (3) For neighborhoods with less than 33% of schools participating in free school lunch program, the estimated regression model is: crime_rate = 142.5737 - 1.9215(Prop_change_income) - 38.8741(1) - 19.20521(0) = 103.69959 - 1.9215(Prop_change_income) Questions: 1. What is difference between models in 1,2,and 3? 2. Which estimated model 1,2, or 3 results in the line with the highest estimated crime rates (the highest positioned line)? 3. Test whether the crime rate in neighborhoods with 33% to 66% of…
7
Acrylamide is a chemical that is sometimes found in cooked starchy foods and which is thought to increase the risk of certain kinds of cancer. The paper "A Statistical Regression Model for the Estimation of Acrylamide Concentrations in French Fries for Excess Lifetime Cancer Risk Assessment"† describes a study to investigate the effect of x = frying time (in seconds) and y = acrylamide concentration (in micrograms per kg) in French fries. The data in the accompanying table are approximate values read from a graph that appeared in the paper. FryingTime AcrylamideConcentration 150 155 240 115 240 190 270 180 300 140 300 265 (a) Construct a scatterplot of these data. A scatterplot has 6 points.The horizontal axis is labeled "x" and ranges from 100 to 350.The vertical axis is labeled "y" and ranges from 50 to 350.The points are plotted from left to right in a horizontal direction starting from the lower left side of the diagram.Along the horizontal axis, there is 1 point at 150, 2 points…

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