Represent differences between measured and predicted responses using residual plots.
Example Problems
A bakery owner recorded the daily number of social media posts and the number of cupcakes sold that day.
After plotting his results, the owner noticed that the relationship between the two variables was fairly linear, so he used the data to calculate the following least squares regression equation for predicting cupcakes sold from social media posts:
What is the residual for a day with 5 posts and 120 cupcakes sold?
After plotting his results, the owner noticed that the relationship between the two variables was fairly linear, so he used the data to calculate the following least squares regression equation for predicting cupcakes sold from social media posts:
What is the residual for a day with 5 posts and 120 cupcakes sold?
A volleyball statistician recorded the number of serves attempted in a match and the number of aces scored per player.
After plotting her results, the statistician 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 aces scored from serves attempted:
What is the residual for a player who attempted serves and scored aces?
After plotting her results, the statistician 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 aces scored from serves attempted:
What is the residual for a player who attempted serves and scored aces?
A theater club tracked the number of rehearsals before each show and the number of tickets sold to the show.
After plotting their results, the club president 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 tickets sold from the number of rehearsals:
What is the residual for a show with rehearsals that sold tickets?
After plotting their results, the club president 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 tickets sold from the number of rehearsals:
What is the residual for a show with rehearsals that sold tickets?
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