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+bx a=-1.778 b=0.143 (a) Write the equation of the Least Squares Regression line of the form ˆyy^= + 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

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+bx a=-1.778 b=0.143 (a) Write the equation of the Least Squares Regression line of the form ˆyy^= + 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

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 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.-
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The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 00 33 44 4.54.5 55 5.55.5 66 Overall Grades 8383 7878 7070 6969 6767 6464 6363 Table Copy Data Step 3 of 6 : Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the value of the independent variable is increased by…
The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 00 11 1.51.5 22 2.52.5 44 4.54.5 Overall Grades 9797 9393 8585 7474 7272 7171 6666 Step 4 of 6 : Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the value of the independent variable is increased by one unit, then…
mean of x = 2.882, standard deviation = 1.634 Mean of y = 2.588, standard deviation = 0.246 The correlation coefficient is 0.159 slope coefficient for regression line = .0239 Find the intercept for the regression line.
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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.