To estimate \( h^{\prime}(1.5) \), we can use the concept of numerical differentiation, specifically the symmetric difference quotient. This involves using the values of \( h(q) \) at points around 1.5, which are 1 and 2 in this case. The formula for the symmetric difference quotient is:
\[
h^{\prime}(1.5) \approx \frac{h(2) - h(1)}{2 - 1}
\]
To estimate \( h^{\prime}(1.5) \), we need the values of \( h(q) \) at points around \( q = 1.5 \). From the given data, these points are \( q = 1 \) and \( q = 2 \) with corresponding \( h(q) \) values of 31 and 141, respectively.
The symmetric difference quotient formula for estimating the derivative at a point is:
\[
h^{\prime}(1.5) \approx \frac{h(2) - h(1)}{2 - 1}
\]
Substituting the values from the data:
\[
h^{\prime}(1.5) \approx \frac{141 - 31}{2 - 1} = \frac{110}{1} = 110.0
\]