Understand the reason for the log transformation. There is usually only one reason for using a log dependent variable: the data show an exponential trend. This means that when graphed, the dependent variable grows exponentially with the independent variable. Because of the difficulty involved in analyzing nonlinear functions, many researchers decide to use the log of the transformation, which transforms the shape of the data into that of a line.
Acknowledge the relationship between the dependent variable and the independent variable. If the dependent variable is a log dependent variable, it means the dependent variable grows slowly with respect to the independent variable at first. However, when the independent variable grows to a larger size, the dependent variable gets out of hand, growing at speeds that make it difficult for the researcher to analyze in a practical manner. Thus, knowing that the dependent variable is a log dependent variable is enough to understand the effect of the independent variable on the dependent variable.
Find the true values of the data. Because the dependent variable is a log transformation of the original data, these dependent variables mean nothing in real terms. To return the dependent variables to interpretable values, use the exponential function, applying the dependent variable's individual data points. After using the function exp(x) on a data point "x," you will have the original data point for that dependent variable, which can be interpreted in terms of the real meaning of the data.