Find the equation for the least squares regression line of the data described below.Judith isn't getting enough sleep and suspects it's due to playing too many video games before bed. To find out, she decided to track how much time she spends gaming.Over several days, Judith recorded how many hours of sleep she had gotten each night, x, as well as how many hours she had spent playing video games before bed, y.Hours of video games Hours of sleep0.7 100.9 101.1 52.6 53.3 4Round your answers to the nearest thousandth.

Read the following description of a data set.Researchers at a sleep clinic want to know how watching television affects a person's ability to fall asleep. In a study, they measure the amount of time it takes subjects to fall asleep at night after watching television.The researchers note the number of minutes the subjects spent watching television in the evening, x, as well as the number of minutes it took them to fall asleep, y.The least squares regression line of this data set is:y=0.111x+4.364How many minutes does this line predict it will take a subject to fall asleep if they watch 175 minutes of television in the evening?Round your answer to the nearest integer. minutes

Interpret the least squares regression line of this data set.Playing video games makes Francesca so happy that she thinks it even helps her complete more schoolwork. Francesca's roommate Justine is skeptical, so over the next few days, Justine asks Francesca about her progress on her daily reading.For each day, Justine notes the number of minutes Francesca spends playing video games, x. She also takes the number of pages Francesca reads and divides it by the total number of pages assigned, y.Minutes playing video games Percentage of reading assignment103 59.56111 54.57112 35.28112 57.78117 32.95The least squares regression line for the data set is:y=–1.821x+250.135Use it to complete the following sentence:If Francesca spends an additional minute playing video games, the least squares regression line predicts her completion percentage drops by points.Submit

Read the following description of a data set.Nate is packing for vacation and is wondering how many books to bring. He wants to make sure he does not run out of reading material, so he looks at his reading journal to see how many books he read on past vacations.For each vacation, he records the vacation's length (in days), x, and how many books he read, y.The least squares regression line of this data set is:y=0.745x–0.044How many books does this line predict Nate would have read on a 13 day vacation?Round your answer to the nearest integer. booksSubmit

orWatch a videoRead the following description of a data set.Mr. Caldwell is offering extra credit on his statistics exam. All students have to do is state how many hours they spent studying for the exam. After he finished grading, Mr. Caldwell looked at how self-reported studying times were related to exam scores.He recorded the number of hours each student had reported studying, x, and his or her exam score (out of 100), y.The least squares regression line of this data set is:y=3.089x+46.103Complete the following sentence:For each additional hour a student had reported studying, the least squares regression line predicts that he or she would score points higher on the exam.Submit

Interpret the least squares regression line of this data set.A gym franchise was considering a television marketing campaign to increase its membership. The franchise's market researchers wanted to get a better sense of the television and exercise habits of the gym's target demographic. To begin, the market researchers surveyed some of the current members about how many hours they had spent watching television and exercising last month.Using the survey responses, the researchers compared the number of hours of television watched, x, to the number of hours of exercise, y, for each member.Hours of television Hours of exercise0.04 28.151.39 33.965.40 33.0424.16 20.6529.85 35.9337.44 7.7640.73 11.39The least squares regression line for the data set is:y=–0.466x+33.657Use it to complete the following sentence:If a gym member had watched one additional hour of television last month, the least squares regression line predicts that they would have spent hours less exercising that month.