8.4.1.3
Assess the reasonableness of predictions using scatterplots by interpreting them in the original context.
Example Problems
A fishery biologist recorded the length of trout, in centimeters, and their weight, in grams.
After plotting her results, the biologist noticed that the relationship between the two variables was fairly linear, so she used the data to calculate the following least squares regression equation for predicting weight, in grams, from length, in centimeters:
What is the residual for a trout that is long and weighs ?
After plotting her results, the biologist noticed that the relationship between the two variables was fairly linear, so she used the data to calculate the following least squares regression equation for predicting weight, in grams, from length, in centimeters:
What is the residual for a trout that is long and weighs ?
A mobile carrier recorded each customer's monthly data usage, in GB, and their monthly bill, in dollars.
After plotting their results, the analysts noticed that the relationship between the two variables was fairly linear, so they used the data to calculate the following least squares regression equation for predicting the monthly bill, in dollars, from data usage, in GB:
What is the residual for a customer who used and was billed ?
After plotting their results, the analysts noticed that the relationship between the two variables was fairly linear, so they used the data to calculate the following least squares regression equation for predicting the monthly bill, in dollars, from data usage, in GB:
What is the residual for a customer who used and was billed ?
A fitness trainer recorded the number of steps a client took in a day and the calories burned, in calories.
After plotting her results, the trainer noticed that the relationship between the two variables was fairly linear, so she used the data to calculate the following least squares regression equation for predicting calories burned from steps taken:
What is the residual for a day with 8000 steps and 560 calories burned?
After plotting her results, the trainer noticed that the relationship between the two variables was fairly linear, so she used the data to calculate the following least squares regression equation for predicting calories burned from steps taken:
What is the residual for a day with 8000 steps and 560 calories burned?
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