John estimates a model of demand for ice cream as a function of temperature at the UT Dallas soccer fields on weekend games using a data set of 18 observations. He obtains the following regression: Q with hat on top equals 10,040.059 - 75.232 * T, where Q is quantity (in units of ice cream) and T is temperature (in degrees Fahrenheit). We know the temperature is predicted to be 90 degrees Fahrenheit. We also know from the regression based on the data set of 18 observations: sigma with hat on top squared equals 18.988; the average temperature was 87.157 degrees Fahrenheit (T with bar on top equals 87.157); ∑ (Ti - T )^2 equals 1,582.95. John wants to come up with the 95% forecast/prediction interval for quantity demanded of ice cream. What is the upper bound of the forecast/prediction interval?