In the regression below y= salary (in thousands of dollars) and x-years of educa
ID: 3233042 • Letter: I
Question
In the regression below y= salary (in thousands of dollars) and x-years of education. Using data collected from a sample, the following results were obtained: y=480 +379x Select the answer that gives a practical interpretation of the estimate of the slope of the least squares line. For each additional year of education, we estimate the salary to increase $4, 800. For each additional year of education, we estimate the salary to increase $3, 790. For each additional one thousand dollars in salary, the years of education increases by 379. For a person with 0 years of education, we estimate the salary to be 859. Define the Coefficient of Determination What is the symbol used for the Coefficient of Determination? Assume that the coefficient of Correlation in problem #3 is 0.9219. Calculate the coefficient of Determination for problem # 3. what is the proper interpretation of the coefficient of Determination for problem #3? Using the output data above, complete the table below. write the null hypothesis for testing the overall adequacy of the following model: y=beta_0 + beta_1x_1 beta_2 x_2 ++ beta_3x_3 + beta_4x_4 + beta_3x_5Explanation / Answer
Solvinf first 4 subparts
3 The correct answer is B. For each additional year of education, salary is estimated to increase by 3.79*1000=3790
4)The coefficient of determination (denoted by R2) is defined as the proportion of the variance in the dependent variable that is predictable from the independent variable.
5) Coefficient of determination is denoted by R2
6) Coefficient of determination = (Coefficient of correlation)^2 = 0.9219^2 = 0.8499
7) 84.99% of of the variance in the dependent variable(Salary) is predicted from the independent variable(Years of education).