The table shows the number of cellular phone subscribers (in millions) in the United States for selected years. Year 1990 1993 1996 1999 2002 2005 Number 5 16 44 86 141 206 (a) Use the regression capabilities of a graphing utility to find a mathematical model of the form y = at² + bt + c for the data. In the model, y represents the number of subscribers and t represents the year, with t = 0 corresponding to 1990. (Round your coefficients to three decimal places.) y = (b) Use a graphing utility to plot the data and graph the model. 350 300 250 200 y 150 100 50- 350 300 y 250 200 150 100 01990 1996 8 10 12 14 16 18 20 1 2000 1 2005 2010 Y O y O 350 300 250 200 150 100 50- 01900 350 300 250 200 150 100 50- 1995 24 2000 t 2005 2010 8 10 12 14 16 18 20 t (c) Use the model to predict the number of cellular phone subscribers in the United States in the year 2017. (Round your answer to three decimal places.)

Based on data taken from airline fares and distances One of the flights was 350 miles and its residual was - flown, it is determined that the equation of the least- 105.00. What was the fare for this flight? squares regression line is ŷ = 102.50+ 0.65x, where y is the predicted fare and x is the distance, in miles. $102.50 $435.00 $225.00 $330.00

The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years, construct and interpret a 98% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $888 the equation of the regression line is y= 1.453x-47.386. Wages(state), X | 739|760|784|822|898|921|937|954|965| Wages (federal), Y |1,036|1,054|1,105|1,136|1,192|1,253|1,266|1,327|1,400|

The file Galton on D2L contains the 928 observations Francis Galton used in 1885 to estimate the relationship between the heights of parents and the heights of their children. The column Children refers to the height (in inches) of a child, and the column Mid-Parents refers to the average height (in inches) of the mother and father of that child. You can download this file into Excel and Minitab. a. Calculate the regression Height of Children = a +b (Height of Mid-Parents). b. Calculate the average for Height of Children, and calculate the average Height of Mid-Parents. c. Create a new variable in Minitab which is the Height of Children measured in terms of deviations from its mean. Call this new variable y. Also, create a new variable in Minitab with is the Height of Mid-Parents measured in terms of deviations from its mean. Call this new variable x. Calculate the regression y = a + bx. You can create the new y and x variables in Excel of Minitab, whichever you find more convenient.…

2. The table below lists the annual land-line phone cost per costumer: Year 2012 2013 2014 2015 Cost ($) a. 692 610 Find a linear regression model for this data b. Interpret the slope of the model 580 C. Predict the annual land-line phone cost per customer in 2022 495 2016 434

b. Find the equation of the regression line for the minutes the actor appeared shirtless in a film and the film's opening weekend gross. y = ___x + ____(Round to two decimal places as needed)

The annual expenditure for cell phones varies by the age of an individual. The average annual expenditure E(a) (in $) for individuals of age a (in years) is given below:a: 20, 30, 40, 50, 60, 70E(a): 502, 658, 649, 627, 476, 2131. Use quadratic regression to find the model that best represents the data.2. At what age is the yearly expenditure for cell phones the greatest? Round the answer to the nearest year. YOU MUST SHOW THE WORK FOR THIS PART!

Give the equation of the regression line: -913.2969+0.4808years(y)   a) Plug an actual x value into the equation and discuss the difference between the real y and the predicted yb) Discuss the domain of your datac) Include the scatterplot with line of best fit

A biology student is investigating the claim that the temperature can be predicted by counting cricket chirps. She has found a linear regression equation T=42.2+0.21r, where T is the temperature in degrees Fahrenheit and r is the number of chirps per minute. What is the predicted temperature for 90 chirps per minute?   18.9 degrees 227.6 degrees 23.3 degrees 61.1 degrees

This was not the correct quadratic model for the data