1. The log-log and exponential models were used to fit given data on (y) and (x)
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Question
1. The log-log and exponential models were used to fit given data on (y) and (x), and the following table summarizes the regression results. Which of the two models provides a better fit?
a). The log-log model.
b). The exponential model.
c). The models are not comparable.
d). The provided information is not sufficient to make the conclusion.
2. The quadratic and logarithmic models were used to fit given data on (y) and (x), and the following table summarizes the regression results. Which of the two models provides a better fit?
a). The logarithmic model.
b). The quadratic model.
c). The models are not comparable.
d). The provided information is not sufficient to make the conclusion.
3. The logarithmic and log-log models were used to fit given data on (y) and (x), and the following table summarizes the regression results. Which of the two models provides a better fit?
a). The logarithmic model.
b). The log-log model.
c). The models are not comparable.
d). The provided information is not sufficient to make the conclusion.
Variable Log-Log Exponential Int 0.75 1.04 X NA 0.24 ln(x) 1.08 NA R^2 0.85 0.87 Adj R^2 0.84 0.85Explanation / Answer
The coefficient of determination, R2, defines the proportion of variation explained by the model. Higher the value, better the model.
1. The Adjusted R sqaure values of log-log is 0.84 and for Exponential is 0.85 . Therefore Exponential Model is a better fit.
2. The Adjusted R sqaure values of Quadratic is 0.75 and for Logarithmic as 0.76. Therefore Logarithmic Model is a better fit.
3. The Adjusted R sqaure values of Logarithmic is 0.87 and for log-log as 0.84. Therefore Logarithmic Model is a better fit.
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