To provide a background for those who are unfamiliar with statistical concepts, what's called student's t statistics, or t-stats, usually presented in regression result tables, are a measure of how confident we can be that the coefficients are different from zero not just because of randomness. The higher a t-stat is, the more likely that the coefficient is really significant in contributing predictive values to the equation. For example, in model I, the t-stat of the Dusting Factor is very low compared with the one associated with the Floor Factor. This means that the Floor Factor does affect man-minutes while the Dusting Factor does not.
R-squared is a measure of the goodness-of-fit of the model. The higher R-squared, the better the model fits the data.