To explain: The difference between
Answer to Problem 1TP
It is very difficult to distinguish the differences between analysis of variance (ANOVA) and regression. This is because both terms have more similarities than differences. It can be said that ANOVA and regression are the two sides of the same coin.
ANOVA is mainly used to determine if data from various groups have a common means or not. Regression is widely used for forecasting and predictions.
Explanation of Solution
Analysis of variance (ANOVA) and regression statistical models are only applicable if there is a continuous outcome variable. The main difference between regression and ANOVA is,
- The regression model is based on one or more continuous predictor variables. On the other hand, the ANOVA model is based on one or more categorical predictor’s variables.
- ANOVA focuses on the random variable and regression focuses on fixed variable.
- In ANOVA there can be several error terms whereas there is only one error term in regression.
- ANOVA is mainly used to determine if data from various groups have a common means or not. Regression is widely used for forecasting and predictions.
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