Question

Look at the following output from a linear regression in R. What is the amount of variability in Y that is explained by the model? ## Call: ## lm(formula = y ~ x, data = my.data) ## ## Residuals: ## Min 1Q Median 3Q Max ## -29.069 -9.525 -2.272 9.215 43.201 ## ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) ## (Intercept) 42.9800 2.1750 19.761 < 2e-16 * ## x 3.9324 0.4155 9.464 1.49e-12 * ## --- ## Signif. codes: 0 '' 0.001 '' 0.01 '' 0.05 '.' 0.1 ' ' 1 ## ## Residual standard error: 15.38 on 48 degrees of freedom ## Multiple R-squared: 0.6511, Adjusted R-squared: 0.6438 ## F-statistic: 89.57 on 1 and 48 DF, p-value: 1.49e-12 About 89.6%, using the F statistic 3.93%, using the coefficient for the variable X There is no information on this output for me to answer the question. About 64%, using the adjusted R-squared

          Look at the following output from a linear regression in R. What is the amount of variability in Y that is explained by the model?
## Call:
## lm(formula = y ~ x, data = my.data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -29.069 -9.525 -2.272 9.215 43.201
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 42.9800 2.1750 19.761 < 2e-16 ***
## x 3.9324 0.4155 9.464 1.49e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 15.38 on 48 degrees of freedom
## Multiple R-squared: 0.6511, Adjusted R-squared: 0.6438
## F-statistic: 89.57 on 1 and 48 DF, p-value: 1.49e-12
About 89.6%, using the F statistic
3.93%, using the coefficient for the variable X
There is no information on this output for me to answer the question.
About 64%, using the adjusted R-squared

Look at the following output from a linear regression in R. What is the amount of variability in Y that is explained by the model?
## Call:
## lm(formula = y x, data = my.data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -29.069 -9.525 -2.272 9.215 43.201
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 42.9800 2.1750 19.761 < 2e-16 ***
## x 3.9324 0.4155 9.464 1.49e-12 ***
## —
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 15.38 on 48 degrees of freedom
## Multiple R-squared: 0.6511, Adjusted R-squared: 0.6438
## F-statistic: 89.57 on 1 and 48 DF, p-value: 1.49e-12
About 89.6%, using the F statistic
3.93%, using the coefficient for the variable X
There is no information on this output for me to answer the question.
About 64%, using the adjusted R-squared

Added by Jeremy W.

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