In a linear regression model, the residual degrees of freedom are calculated as:
\[
\text{Residual degrees of freedom} = n - p - 1,
\]
where \( n \) is the number of data points and \( p \) is the number of predictors.
Here, \( n = 100 \) and \( p = 1 \) (since there is a single continuous predictor). Thus, the residual degrees of freedom are:
\[
\text{Residual degrees of freedom} = 100 - 1 - 1 = 98.
\]
Thus, the residual degrees of freedom are \( 98 \).