In conducting a multiple linear regression analysis, an R2 value of 0.46 is obtained. An extra variable is added and R2 improves to 0.52

The analyst conducting the regression analysis concludes that this is a meaningful increase in R2 and determines that the latter model is an appropriate model to be used. Is this decision justified?

No, this decision is not justified. When conducting multiple regression, adding new independent variables to the model will always increase the value of R.2 Thus, trying to maximize R2 is not a useful criterion. A better way of evaluating the relative fit of different models is to use Adjusted R2. Adjusted R2 reflects both the number of independent variables and the sample size, and may either increase or decrease when an independent variable is added or dropped, thus providing an indication of the value of adding or removing independent variables in the model. An increase in Adjusted R2 indicates that the model has improved.