The authors of the paper "Predicting Yolk Height, Yolk Width, Albumen Length, Eggshell Weight, Egg Shape Index, Eggshell Thickness, Egg SurfaceArea of Japanese Quails Using Various Egg Traits as Regressors"+ used a multiple regression model with two independent variables wherey = quail egg weight (g),X₁ = egg width (mm), andx2 = egg length (mm).The regression function suggested in the paper is -21.658 +0.828x₁ + 0.373x2.(a) What is the mean egg weight for quail eggs that have a width of 16 mm and a length of 49 mm? (Enter your answer to three decimal places.)g

Answered: The authors of the paper "Predicting…

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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Hello, I am working on an assignment in research design. How do I calculate cronbach's alpha for a multiple regression analyis of prayer on a set of 5 different vital signs? (heart rate, blood pressure, temp, O2, and resp)
The following table shows the starting salary and profile of a sample of 10 employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance.What is the equation of the resulting multiple linear regression? starting_salary = 3008.61 + 48.65*GPA + 94.79*years_of_experience + 27.36*civil_service_ratings starting_salary = 15000.00 + 48.65*GPA + 94.79*years_of_experience + 27.36*civil_service_ratings starting_salary = 15001.00 + 41.43*GPA + 84.71*years_of_experience + 37.32*civil_service_ratings starting_salary = 2366.77 + 130.25*GPA + 396.39*years_of_experience + 21.67*civil_service_ratings
Please answer as many as your 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.
A study in the univeristy of massachusetts amherst published in the may 2007 journal of marriage and family found that married women do about one fewer hour of housework a week for every $7500 they earn as a full time workers outside of the home, regardless of their husband's income A) what would be the numerical value of the slope coefficient in the regression model that predicts womens housework hours from their income? what does the sign of the slope (positive or negative) tell us about the relationship between these variables B) Suppose Lynette's salary is $30,000 greater than Gabriells. what would you predict the difference in hours of housework they each do.
The authors of the paper "Predicting Yolk Height, Yolk Width, Albumen Length, Eggshell Weight, Egg Shape Index, Eggshell Thickness, Egg Surface Area of Japanese Quails Using Various Egg Traits as Regressors"t used a multiple regression model with two independent variables where y = quail egg weight (g), X, = egg width (mm), and X2 = egg length (mm). The regression function suggested in the paper is -21.658 + 0.828x, 0.373x2. + (a) What is the mean egg weight for quail eggs that have a width of 20 mm and a length of 48 mm? (Enter your answer to three decimal places.) (b) Interpret the value of B,. O When width is fixed, the mean increase in weight associated with a 1-mm increase in length is 0.373 g. When length is fixed, the mean increase in weight associated with a 1-mm increase in width is 0.373 g. O When length is fixed, the mean increase in weight associated with a 1-mm increase in width is 0.828 g. O When width is fixed, the mean increase in weight associated with a 1-mm increase…
6
Find the slope of regression line, y-intercept of regression line, coefficient of determination (r^2), and the linear correlation coefficient (r)
Study conductes in patients with HIV. Primary outcome is CD4 coubt(measure stage of disease). Lower CD4=more advanced disease. Wqnt to find association between taking vitamins and supplements and CD4 count. Multiple regression analysis done relating CD4 to use of supplements (1=yes 0=no) and to duration of HIV in years. (# of yeara between diagnosis and study date) y=CD4 Count Y=501.41+12.67 supplements -30 23 duration of HIV. A. What is ezpected CD4 count for patients taking supplements who had HIv for 2.5 years? B. Expected CD4 count not takong supplements with HIv at study start date? C. Expected CD4 coubt for patients not taking supplements with HIV for 2.5 years? D. Uf compare 2 patients, 1 HIV for 5 years longer than other, whats expected difference in CD4 count?
What are the different measures used for the OLS estimate of the multiple regression line?
A year-long fitness center study sought to determine if there is a relationship between the amount of muscle mass gained y(kilograms) and the weekly time spent working out under the guidance of a trainer x(minutes). The resulting least-squares regression line for the study is y=2.04 + 0.12x A) predictions using this equation will be fairly good since about 95% of the variation in muscle mass can be explained by the linear relationship with time spent working out. B)Predictions using this equation will be faily good since about 90.25% of the variation in muscle mass can be explained by the linear relationship with time spent working out C)Predictions using this equation will be fairly poor since only about 95% of the variation in muscle mass can be explained by the linear relationship with time spent working out D) Predictions using this equation will be fairly poor since only about 90.25% of the variation in muscle mass can be explained by the linear relationship with time spent…
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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