Final answer:
The correct answer is (a) Total deviation=unexplained deviation+explained deviation. This represents the overall variation in a dataset which is the sum of both the variation explained by a statistical model and the unexplained or residual variation.
Step-by-step explanation:
The question asks to identify the correct equation that represents total deviation in the context of statistical data analysis. The correct answer is (a) Total deviation=unexplained deviation+explained deviation. In statistics, 'total deviation' refers to the overall variability in your data set. The 'explained deviation' is the portion of the total variation that can be attributed to a model or predictor, while the 'unexplained deviation' is the variation that the model cannot account for, often considered as noise or error.
For example, in the context of a regression model, the explained variation is part of the variation in the dependent variable that is predicted by the model using the independent variables. The unexplained variation is the difference between the observed values and the predicted values by the model, often referred to as the residuals. The sum of the squared residuals represents the unexplained variation, while the sum of the squared differences between the predicted values and the overall mean represents the explained variation.