Use the following code and results to help you answer the questions. > Im(Numerical_data$y2~Numerical_data$x) Call: Im(formula = Numerical_data$y2 ~ Numerical_data$x) Coefficients: (Intercept) Numerical_data$x -118869.2 267.7 > cor(Numerical_data$x,Numerical_data$y2) 0.4459767 What is the equation of the least squares regression line that models the relationship between x and y1? [Select] Which of the following statements is true regarding the slope of the linear regression line? [Select] Which of the following statements is true regarding the y- intercept of the linear regression line? [Select]
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Step 1: The equation of the least squares regression line is given by: $$y = mx + b$$ where $m$ is the slope and $b$ is the y-intercept. Show more…
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Linear Regression and Correlation. x y 2 10.16 3 2.19 4 3.12 5 -1.75 6 7.48 7 9.31 Compute the equation of the linear regression line in the form y = mx + b, where m is the slope and b is the intercept. Use at least 3 decimal places. y = __x + ___ Compute the correlation coefficient for this data set. Use at least 3 decimal places. r = Compute the P-value (Use H_A: slope ≠ 0 for the alternative hypothesis.) P-value = At the alpha = 0.01 significance level, is the correlation significant? Yes, significant correlation No
Adi S.
Linear Regression and Correlation. x y 1 -0.02 2 -3.84 3 -1.06 4 -4.98 5 1.5 6 -1.92 7 -2.84 8 -1.16 9 -11.58 10 -3.2 Compute the equation of the linear regression line in the form y = mx + b, where m is the slope and b is the intercept. Use at least 3 decimal places. (Round if necessary) y = x + Compute the correlation coeficient for this data set. Use at least 3 decimal places. (Round if necessary) r= Compute the P-value (Use HA: slope ≠ 0 for the alternative hypothesis.) Use at least 3 decimal places. (Round if necessary) P-value = At the alpha = 0.01 significance level, is the correlation significant? No Yes, significant correlation
Madhur L.
1) a) Linear Regression and Correlation. x y 1 2.51 2 -2.58 3 6.33 4 0.64 5 9.05 6 2.86 7 7.67 Compute the equation of the linear regression line in the form y = mx + b, where m is the slope and b is the intercept. Use at least 3 decimal places. (Round if necessary) y = __x + __ Compute the correlation coeficient for this data set. Use at least 3 decimal places. (Round if necessary) r= __ Compute the P-value (Use HA: slope ≠ 0 for the alternative hypothesis.) Use at least 3 decimal places. (Round if necessary) P-value = __ At the alpha = 0.05 significance level, is the correlation significant? Yes, significant correlation No b) Linear Regression and Correlation. x y 2 -3.26 3 7.96 4 0.08 5 -6.3 6 2.62 7 2.34 8 3.56 9 -8.62 Compute the equation of the linear regression line in the form y = mx + b, where m is the slope and b is the intercept. Use at least 3 decimal places. (Round if necessary) y = __x + __ Compute the correlation coeficient for this data set. Use at least 3 decimal places. (Round if necessary) r= ___ Compute the P-value (Use HA: slope ≠ 0 for the alternative hypothesis.) Use at least 3 decimal places. (Round if necessary) P-value = ___ At the alpha = 0.01 significance level, is the correlation significant? No Yes, significant correlation
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