Regression equation: H=36.1-0.57T (H is Candle height in cm and T is the burn time in min.
a) comment on the appropriateness of using the regression equation to predict Candle height when burn time is 55 min. Guys help this boy..
I'd say it depends on the correlation coefficient. 55 is in the domain of the function, so if it's a good fit, then why not use the equation?
All right!!!!!!!!!!!!!!!hero
To assess the appropriateness of using the regression equation to predict the candle height when the burn time is 55 minutes, we need to evaluate the key assumptions and limitations of regression analysis.
1. Linearity: Regression assumes a linear relationship between the independent variable (burn time) and the dependent variable (candle height). It is essential to examine the scatterplot of the data points to confirm if a linear relationship exists. If the scatterplot shows a clear linear pattern, the regression equation may be suitable for prediction.
2. Independence: Regression analysis assumes that the observations are independent of each other. In this case, it means that the candle heights at different burn times are not influenced by one another. If the data violates this assumption, such as if the candle heights at different burn times are interdependent, the regression equation may not be appropriate.
3. Homoscedasticity: Regression analysis assumes that the variance of the dependent variable is constant across all levels of the independent variable. It is essential to examine the residual plot, which shows the differences between the observed and predicted values. If the residual plot shows a consistent spread around zero, it suggests homoscedasticity, making the regression equation more suitable.
4. Normality: Another assumption is that the residuals follow a normal distribution. You can examine the normality assumption by creating a histogram or a normal probability plot of the residuals. Deviations from normality may affect the validity of the regression equation.
After considering these assumptions, limitations, and checking relevant plots, you can evaluate the appropriateness of using the regression equation to predict the candle height at a burn time of 55 minutes.