Which is a correct interpretation of r-squared = 0.885 (assume this is for a linear regression model) There is an 88.5% chance that we can accurately predict y given an x 88.5% of the variability in x can be explained by the linear relationship with y 88.5% of the variability in y can be explained by the linear relationship with x There was an average of 88.5 y's
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885 for a linear regression model. The R-squared value represents the proportion of the variance in the dependent variable that is predictable from the independent variable(s). In other words, it tells us how well the regression model fits the data. Now, we need Show more…
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In the following regression, X = total assets ($ billions), Y = total revenue ($ billions), and n = 64 large banks. R^2: 0.519 Std. Error: 6.977 n: 64 ANOVA table: Source SS df MS F p-value Regression 3,260.0981 1 3,260.0981 66.97 1.90E-11 Residual 3,018.3339 62 48.6828 Total 6,278.4320 63 Regression output: confidence interval variables coefficients std. error t Stat p-value Lower 95% Upper 95% Intercept 6.5763 1.9254 3.416 .0011 2.7275 10.4252 X1 0.0452 0.0055 8.183 1.90E-11 0.0342 0.0563 (a) Write the fitted regression equation. Å· = 6.5763 + 0.0452X
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