x(t) = a + bt

x(t) = c + dt + et^{2}

χ^{2} = ∑_{i} \frac{(data_{i} − model_{i})^{2}}{σ_{i}^{2}}

χ^{2} = \frac{(0.00 − 1.54)^{2}}{(0.5)^{2}} + …

χ^{2} = \frac{(0.00 − 0.26)^{2}}{(0.5)^{2}} + …

reduced χ^{2} = \frac{χ^{2}}{number of degrees of freedom}