To predict how many hot cocoas Kennedy would sell if the day's high temperature were 40 degrees, we can use the line of best fit. The line of best fit represents the trend in the data and allows us to estimate the number of hot cocoas sold based on the temperature.
To find the predicted number of hot cocoas, we need to look at the equation of the line of best fit. The equation is usually in the form y = mx + b, where y represents the dependent variable (in this case, the number of hot cocoas sold) and x represents the independent variable (the day's high temperature). The coefficient m represents the slope of the line, and b represents the y-intercept.
Let's say the equation of the line of best fit is y = 2x + 10. This means that for every 1-degree increase in the temperature, Kennedy sells 2 more hot cocoas. The y-intercept of 10 indicates that even if the temperature is 0, Kennedy would still sell 10 hot cocoas.
Now, let's substitute x = 40 into the equation to find the predicted number of hot cocoas:
y = 2(40) + 10
y = 80 + 10
y = 90
Based on the line of best fit, if the day's high temperature were 40 degrees, we would predict Kennedy to sell approximately 90 hot cocoas.