The table gives the amount of money (in dollars) spent on football by a major university. Letting arepresent the number of years since 2011, and letting y represent the amount of money spent on football,in thousands of dollars, use the regression capabilities of a graphing calculator to find the equation of theline of best fit.Round values off to the nearest hundredth.Then, use your equation to make the following predictions.Year2011Dollars spent on football 178,000The equation of the line of best fit is:Hint2012 2013 2014 2015196,000 211,000 222,000 244,000Predict the amount of money that will be spent on football in the year 2024.Predict the amount of money that will be spent on football in the year 2043.2016284,000

The question is about regression Given : To find : 1 ) Eq. of the line of best fit 2 ) Pred.…

Answered: The table gives the amount of money (in…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The table and scatter plot show the number of years of experience, x, and the hourly pay rate, v, for each of 11 cashiers in Florida. The equation of the line of best fit is y= 0.9x+8.02. Experience, x | Hourly pay rate, y (in years) (in dollars) 22 0.8 7.42 20- 1.0 9.71 18- 16- 1.3 8.00 Hourly 14- 2.0 9.08 pay rate 12- (in dollars) 3.3 11.40 10 3.6 12.12 8. 3.8 13.00 6. 5.0 14.50 7.0 12.40 8.6 15.46 10 Experience (in years) 8.8 15.87 Use the equation of the line of best fit to fill in the blanks below. Give exact answers, not rounded approximations. Observed hourly pay Predicted hourly pay Number of years of experience Residual rate (in dollars) rate (in dollars) (in dollars) 5.0 7.0
Tell whether a linear model or a quadratic model is appropriate for the data. If linear, tell whether the slope should be positive or negative. If quadratic, decide whether the leading coefficient of x should be positive or negative. O A. linear, negative O B. quadratic; negative O C. quadratic; positive O D. linear; positive 3- 2- -5 43 2 2. 3 4 5 20 -4-
Darnell has recorded the estimated value of his car each year since 2017. Let x=1 correspond to the year 2017. Find the slope-intercept form of the equation for the line that passes through the points representing the value of his car in 2017, (1,24,349), and the value of his car in 2021, (5,17,999). Round the slope to the nearest hundredth, if necessary. Year Value, $$ 2017 24,349 2018 22,200 2019 20,100 2020 19,100 2021 17,999
Find the regression equation, letting the first variable be the predictor (x) variable. Find the best predicted Nobel Laureate rate for a country that has 78.5 Internet users per 100 people. How does it compare to the country's actual Nobel Laureate rate of 1.9 per 10 million people? Click the icon to view the data. Data table Find the equation of the regression line. Internet Users Per 100 Nobel Laureates V = + (Round the constant to one decimal place as needed. Round the coefficient to three decimal places as needed.) 79 5.4 79.6 24.5 78.7 8.5 44.7 0.1 83.6 6.1 38.6 0.1 90.2 25.5 89.4 7.7 79.1 9. 83.1 12.8 52.7 1.9 76.8 12.7 57.1 3.3 79.8 1.5 92.3 11.5 93.8 25.7 64.7 3.1 58.2 1.9 67.3 1.7 94 31.8 84.5 31.3 87 18.9 77.1 10.7
The table and scatter plot show the number of years of experience, x, and the hourly pay rate, y, for each of 10 cashiers in Arizona. The equation of the line of best fit is y = 0.9xr+8.22. Experience, x Hourly pay rate, y (in years) 22 (in dollars) 20+ 0.8 7.47 18- 1.1 9.46 +16- Hourly 2.2 8.91 14+ pay rate 3.1 11.46 (in dollars) 124 10 3.8 12.31 3.8 13.00 6- 5.0 14.50 6.9 12.40 8.5 15.44 10 10 11 8.8 15.79 Experience (in years) Use the equation of the line of best fit to fill in the blanks below. Give exact answers, not rounded approximations. Observed hourly pay Predicted hourly pay Number of years Residual (in dollars) rate rate of experience (in dollars) (in dollars) 5.0 6.9
In the regression equation Y = 85.65 + 0.70X1 - 3.43X2, the intercept is a. 0.70 b. -3.43 c. 1 d. 85.65
Use the data below for the PHONES questions that follow. Data compiled from the CIA World Factbook, https://www.cia.gov/. The number of cell phones in use in a country can be approximated from the number of main lines in use in that country by using the regression equation yhat=25+3x which had an R² of about 90%. (The numbers here are millions. For example, "1.2" would represent 1.2 million or 1,200,000.) PHONES 1 At the time the data was collected, the USA had about 314 million cell phones in use and about 150 million main lines in use. What was the residual for the USA? Enter a number of millions. For example, if your answer is 2.85 million enter "2.85". Do not enter anything else such as symbols or words.
A scientist measures the velocity of a major river at various depths. After collecting and analyzing the data, the scientist determines that the equation -0. 114x + 1. 658, where y = x represents the depth, in feet, and y represents the velocity of the river, in feet per second, can be used to model the data. The linear model has a correlation coefficient of 0. 964. Part A: Explain what the slope and intercept of the equation mean in terms of the context. Part B: Explain what the correlation coefficient indicates about the relationship between the two variables.
please please help me i need help
Aviation The Federal Aviation Administration tracks airline delays for airports around the country. During the first half of 2007, the flights delayed at Dallas-Fort Worth Airport averaged 4,500 per month. Use this information to write an equation in slope-intercept form that could be used to predict the total number of delays throughout the year. Let x equal the month of the year and y equal the cumulative delays.

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