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
Question
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
Solution
To predict the number of minutes Ruben talked on the phone with Kayla based on the number of text messages he sent her, we can substitute the value of x (331 text messages) into the least squares regression line equation:
y = -0.385x + 277.516
Substituting x = 331, we get:
y = -0.385 * 331 + 277.516
Now, perform the multiplication and addition:
y = -127.435 + 277.516
Finally, add the two numbers together:
y = 150.081
So, the line predicts that Ruben talked on the phone with Kayla for approximately 150.081 minutes in the past month.
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