Consider the R output below that pertains a multiple regression model under the usual assumptions.anova (lm (body mass - flipper_len,data-workDF),lm (body_mass~ flipper_len +bill_len,data=workDF))## Analysis of Variance Table#### Model 1: body mass - flipper_len## Model 2: body mass flipper_len + bill_len## Res. DfRSS Df Sum of SqF Pr(>F)0.14 0.9046 0.3422## 1331 51.212## 2 330 51.072 11. The p-value is equal to (write the number):2. Do you reject the null hypothesis (Yes/No):_

The output shows the multiple regression model under the usual assumptions.

Answered: Consider the R output below that…

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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Here is the link for the excel https://docs.google.com/spreadsheets/d/10QitIiY-vJVaC88bhhduSVoBw0cXRzsYbPZ-vCZx_Kg/edit?usp=sharing
A regression was run to determine if there is a relationship between the happiness index (y) and lifeexpectancy in years of a given country (x). The results of the regression were: y^=a+bx ; a=-0.423 ,b=0.07 a. Write the equation of the Least Squares Regression line.b. Find the value for the correlation coefficient, r?c. If a country increases its life expectancy, the happiness index will Increase or decrease ( circleone)d. If the life expectancy is increased by 1 year in a certain country, how much will the happinessindex change? Round to two decimal places.e. Use the regression line to predict the happiness index of a country with a life expectancy of 85years. Round to two decimal places.-
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.
https://drive.google.com/file/d/1-aOh_O4aiPAqBldOcC70gIxAYx5PCMnx/view?usp=sharing
Create a multiple regression model with the total number of wins as the response variable, and average points scored, average relative skill, and average points differential as predictor variables. This regression model will help your coach predict how many games your team might win in a regular season based on metrics like the average score, average relative skill, and the average points differential between the team and their opponents. What is the Null Hypothesis (statistical notation and its description in words) Alternative Hypothesis (statistical notation and its description in words)
what is a confidence coefficinent for a simple linear regression line whoes alpha =0.05 and line is y(hat)=-7.45-10x
Researchers found a positive assodation between the students' performance in STAT 1000 and their first-year cumulative college GPA. Furthermore, STAT 1000 course GPA explained 62% of the variation in students'first-year cumulative college GPA. The summarized data is given below: Mean STAT 1000 GPA = 25 Std. dev. - 0.21 Mean cumulative College GPA = 325 Std. dev, = 03 The slope and intercept of the least squares regression line for predicting first-year college GPA from STAT 1000 scores are, respectively. Oa Slope 055 Intercept 1.88 Ob Slope = 1.12 Intercept 1.88 Oc Slope = 1.12 Intercept 044 Od. Slope 044 Intercept 055 Oe Slope- 1.88 Intercept 055
A consumer advocacy group recorded several variables on 140 models of cars.The resulting information was used to produce two models for predicting miles per gallon in the city (mpg_city), one based on the engine displacement (in cubic inches) and a second one based the power of the engine (in horsepower).Model 1: mpg vs engine displacementThe regression equation ismpg_city=33.8 - 0.063*displacementS = 3.26269R-squared = 66.7%Model 2: mpg vs horsepowerThe regression equation ismpg_city=32.2 - 0.0577*horsepowerS = 4.06386R-squared = 49.7% The displacement variable is better because it has a higher R-square (66.7%).The variable horsepower is better because it has a higher residual standard error (S=4.06386). The variable horsepower is better because it has a higher residual standard error (S=4.06386) and a lower R-square (49.7%).The displacement variable is better because it has a lower estimate for the residual standard error (S=3.26269).The displacement variable is better because it…
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.
4 what are the limitations of accuracy when using the best fit line compared to equation of the least squares regression line to make predictions
What are the different measures used for the OLS estimate of the multiple regression line?

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