orWatch a videoFind 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

Use the least squares regression line of this data set to predict a value.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 of this data set is:y=–1.821x+250.135If Francesca spends 109 minutes playing video games, what percentage of her daily reading assignment does this line predict she will complete?Round your answer to the nearest thousandth. percent

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.

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

Marlene has noticed that she spends a lot of time in front of a screen. She spends all day working in front of a computer screen, she spends time relaxing and watching her favourite shows in front of a TV screen and before she goes to sleep she spends time looking at things on her phone screen. Marlene thinks she should probably cut down on the time she spends on her phone before going to sleep. On any given night, Marlene believes that the amount of time she spends on her phone is uniformly distributed between 41.3 and 73.4 minutes. Assume that the amount of time Marlene spends on her phone is independent from night to night.