t (years since 2010)S(t) (in millions of dollars)011.28 10.9623420.34 38.78 73.425126.14The table above shows the sales S (in millions of dollars) for a portable electric generatorduring hurricane season in the United States for the years 2010 -2015. A quadraticregressiony = at² + bt + c is used to model the function S(t). What is the residual forthe number of portable electric generators sold (in millions) in the year 2014 (t = 4) ?

The data regarding sales of a portable electric generator over the years 2010 and 2015 is…

Answered: t (years since 2010) S(t) (in millions…

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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8
Based on the Regression below, what is the relation between the GDP and gross fixed capital formation(GFCF), trade openness(trade openness), foreign direct investment (FDI). Explain by using A multiple linear regression model (Example y = b0 + b1x1 + b2x2 + …+ bkxk )
Annual high temperatures in a certain location have been tracked for several years. Let X represent the number of years after 2000 and Y the high temperature. Based on the data shown below, calculate the linear regression equation using technology (each constant to 2 decimal places). X y 3 35.01 4 37.78 5 37.35 6 36.72 7 40.09 8 40.36 9 40.83 10 41.3 11 40.57 12 42.64 13 44.21 14 42.58 15 46.05 16 45.12 The equation is ĝ ŷ = X + Interpret the slope O For each additional 33.75 years, the annual high temperature will increase by 1 degree on average. O For each additional year, the annual high temperature will increase by 33.75 degrees on average. For each additional year, the annual high temperature will increase by 0.74 degrees on average. O For each additional 0.74 years, the annual high temperature will increase by 1 degree on average. Interpret the y-intercept O In 2000, the temperature was about 33.75. O In 2003, the temperature was about 33.75. O In 2003, the temperature was about…
Regression methods were used to analyze the data from a study investigating the relationship between roadway surface temperature (x) and pavement deflection (y). The simple linear regression model is y = 0.33 + 0.0042x. (a) Suppose that temperature is measured in °C rather than °F. Determine regression coefficients for the new model y = Bo +B1x. Round your answer to two decimal places (e.g. 98.76). Bo Round your answer to four decimal places (e.g. 98.7654). (b) What change in expected pavement deflection is associated with a 1°C change in surface temperature? Round your answer to four decimal places (e.g. 98.7654). Save for Later Attempts: 0 of 1 used Submit Answer
(Medicare). The annual expenditures for Medicare (in billions of dollars) by the US Government for selected years since 1980 are shown in Table 4. Let x represent the years since 1980. (Use 4 decimal places in all answers.) Table 4: Medicare Expenditures Year Billion $ 1980 37 1985 72 1990 111 1995 181 2000 197 2005 330 A. Find the exponential regression model for the data.M(x) = B. What is the r2 value for this model?r2 = C. Extimate (to the nearest billion) the expenditures in 2008?The Medicare expenditures in 2008 were about $ billion.
The following table shows worldwide sales and projected sales of a certain type of phone and their average selling prices in 2020, 2022, and 2024. Year 2020 2022 2024 Selling Price ($100) p 6 5 4.5 Sales (billions) q 1 1.2 1.3 Find the regression line. 9(p) = Use the regression line to estimate the demand (in millions of units sold) when the selling price was $250. X million 1.6 Need Help? Read It Master It
Demand for Smartphones The following table shows worldwide sales of a type of phone and their average selling prices in 2012, 2013, and 2017. Year 2012 2013 2017 Selling Price p ($100) 4 Sales q (billions) 0.5 3 1 2 2 Find the regression line (round coefficients to one decimal place). q(p) = 1.0166 X Use the regression line to estimate the demand (in millions of units sold) when the selling price was $320. 1016.6 million
Annual high temperatures in a certain location have been tracked for several years. Let X represent the number of years after 2000 and Y the high temperature. Based on the data shown below, calculate the linear regression equation using technology (each constant to 2 decimal places). x y 4 36.68 5 35.85 6 35.52 7 35.99 8 38.46 9 38.93 10 38 11 38.07 12 39.54 13 40.11 14 41.58 The equation is y^ = x + Interpret the slope For each additional 33.38 years, the annual high temperature will increase by 1 degree on average. For each additional 0.52 years, the annual high temperature will increase by 1 degree on average. For each additional year, the annual high temperature will increase by 0.52 degrees on average. For each additional year, the annual high temperature will increase by 33.38 degrees on average. Interpret the y-intercept In 2000, the temperature was about 33.38. It does not make sense to interpret the intercept in this scenario. In 2004, the…
frequency B- A data of 8 employees on ownership of company stock a personal director has collected as: Firm-X 6 12 14 6 9 13 15 9 Versus Y 300 408 560 252 288 650 630 522 1- Determine the regression value 2- For an employee who has been with the firm 10 years. What is the predicted number of shares of stock owned?
The percentage of adults who smoke in America is given below. Year America 1970 37.4 mon n 1980 33.2 1990 25.3 2000 23.1 2010 19.4 a) Write the linear regression model for A(x), representing the percentage of adult smokers in America x years since 1970. [Use your calculator OR Desmos to find the equation, Round coefficients to the nearest 100"] b) What is the slope of A(x)? Explain its meaning. c) Solve A(x) = 15. Show your work. Explain the meaning of your answer. d) Suppose in 2005, there were approximately 200 million adults in America. Use your model to estimate how many were smokers. Show how you get your answer.
Part C

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