Final answer:
To calculate the predicted high temperature, substitute the value of the low temperature into the equation. However, since the equation given has a typo and lacks a y-intercept, we cannot determine the predicted high temperature without the complete and correct linear equation.
Step-by-step explanation:
To predict the high temperature using the given line of best fit, y = 0.92x + high temperature, we need to substitute the low temperature (which seems to be the independent variable 'x') into the equation.
With a low temperature of 50°F, the equation becomes y = 0.92(50) + high temperature. Calculating this gives us y = 46 + high temperature. However, the phrase '+ high temperature' in the equation appears to be a typo, as we are trying to find the predicted high temperature (the dependent variable 'y').
If we ignore the typo, the equation should simply be y = 0.92x, plus the y-intercept, which is not provided. Assuming the y-intercept is the typical starting value of the high temperature in a day, and without additional context, we cannot provide an exact answer.
We need a complete equation with the correct y-intercept to calculate the predicted high temperature.To find the predicted high temperature on a day when the low temperature is 50°F, we can substitute the low temperature value into the given equation y = 0.92x + high temperature.
Given that the low temperature is 50°F, the equation becomes y = 0.92(50) + high temperature. Simplifying the equation, we get y = 46 + high temperature. Therefore, the predicted high temperature on that day would be 46°F + high temperature.