When the temperature outside is 120 (units depending on the data provided), the predicted number of chirps per minute based on this model would be 340.
From the scatter plot and the line of best fit, it seems the researcher was examining the relationship between the temperature outside (x-axis) and the number of times a cricket chirps in one minute (y-axis).
When the x-value is 120 (assuming it represents the temperature), you'd follow the line of best fit to find the corresponding y-value, which would be the predicted number of chirps per minute at that temperature.
If the line of best fit equation is known (usually in the form of y = mx + c, where m is the slope and c is the y-intercept), you can substitute x = 120 into the equation to find the y-value. If the equation isn't provided, you'd have to estimate it based on the trend shown by the line in the scatter plot.
Let's say for example the equation of the line of best fit is
y=2x+100, where y represents the number of chirps and x is the temperature. Then, when x = 120:
y=2×120+100
y=240+100
y=340
So, when the temperature outside is 120 (units depending on the data provided), the predicted number of chirps per minute based on this model would be 340.