Final answer:
The unadjusted R-squared value is approximately 73.96%.
Step-by-step explanation:
The adjusted R-squared value is a measure of how well the model with five variables fits the data. In this case, the adjusted R-squared is 0.725, which means that approximately 72.5% of the variation in the dependent variable can be explained by the independent variables.
The corresponding unadjusted R-squared value represents the percentage of variation in the dependent variable that is explained by the independent variables without adjusting for the number of variables and observations in the model. Since there are five variables and 26 observations, we can calculate the unadjusted R-squared value using the formula:
Unadjusted R-squared = 1 - (1 - adjusted R-squared) * (n - 1) / (n - k - 1)
where n is the number of observations and k is the number of variables.
Plugging in the values, we get:
Unadjusted R-squared = 1 - (1 - 0.725) * (26 - 1) / (26 - 5 - 1) = 0.7396
Therefore, the corresponding unadjusted R-squared value is approximately 0.7396, or 73.96%.