The least squares regression line minimizes the sum of the _____Group of answer choicessquared differences between actual and predicted y valuesabsolute deviations between actual and predicted x valuesdifferences between actual and predicted y valuesabsolute deviations between actual and predicted y values

Read the following description of a data set.The manager at a new bank wants to hire enough tellers to ensure no customer waits in line too long. To gather more information, she waits in line at other local banks.At each bank the manager notes the number of teller windows that are open, x, as well as the number of minutes she has to wait in line before being served, y.The least squares regression line of this data set is:y=–0.607x+4.858Complete the following sentence:The least squares regression line predicts that for each additional open window, the time spent waiting in line decreases by minutes.

Read the following description of a data set.Nick accidentally left food in his backyard one night and noticed a cat eating it the next morning. Nick likes helping out the neighborhood cats, so he wonders if putting out more food will result in more cats coming to his backyard.Over the next few nights, Nick leaves out different amounts of food (in grams), x, and notes the number of cats in his backyard the following morning, y.The least squares regression line of this data set is:y=0.004x–0.358Complete the following sentence:If Nick leaves out one additional gram of food at night, the least squares regression line predicts more cats will be in his backyard the next morning.

In choosing the best fitting line through a set of points in a linear regression, we choose the one with the __________. a. smallest sum of squared residuals b. largest sum of squared residuals c. smallest sum of squared error d. a and c

Use the least squares regression line of this data set to predict a value.Ruben thinks that text messaging is causing him to talk less on the phone. For one month, he examined his text message and call logs with his closest friends.For each friend, Ruben checked the number of text messages he sent to that friend, x, and the number of minutes they spoke on the phone, y.Text messages sent Minutes on the phone156 255167 201210 176263 157276 164350 164The least squares regression line of this data set is:y=–0.385x+277.516If Ruben sent his best friend Kayla 331 text messages in the past month, how many minutes does the line predict they talked on the phone?Round your answer to the nearest thousandth. minutes

The mathematical basis for the best-fitting regression line is called least-squares regression.Group of answer choicesTrueFalse