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.Year202020222024Selling Price ($100) p654.5Sales (billions) q11.21.3Find 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 million1.6Need Help?Read ItMaster It

The data related to selling price and sales for a certain type of phone is given.We have to…

Answered: The following table shows worldwide…

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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What is the dollar amount of change in sales for each new year according to the regression (slope) model? Do not use commas or $ in your answer.
Use the linear regression models above to answer this question. There are two break-even points. Find the smaller production level where the company breaks even. Round to the nearest treadmill. treadmills attached ss thanks
The table contains price-supply data and price-demand data for corn. Find a linear regression model for the price-supply data where x is supply (in billions of bushels) and y is price (in dollars). Do the same for the price-demand data. Find the equilibrium price for corn. Price ($/bu) Supply (billion bu) Price ($/bu) Demand (billion bu) 2.14 6.41 2.06 9.96 2.25 7.38 2.15 9.42 2.34 7.51 2.26 8.33 2.41 7.78 2.32 8.08 2.46 8.13 2.36 7.86 2.57 8.35 2.48 6.96 ... Question content area right Part 1 Find a linear regression model for the price-supply data where x is supply (in billions ofbushels) and y is price (in dollars). y=enter your response here (Type an equation using x as the variable. Round to two decimal places as needed.)
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
Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion). Use the horizontal axis for the customer age to graph. Find the linear regression line that models the data by each type of customer. Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales. What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y / Change in x
The value of a sports franchise is directly related to the amount of revenue that a franchise can generate. The following data represents the value in 2014 (in $millions) and the annual revenue (in $millions) for the 30 Major League Baseball franchises. Suppose you want to develop a simple linear regression model to predict franchise value based on annual revenue generated. Team Revenue Value Baltimore 245 1000 Boston 370 2100 Chicago White Sox 227 975 Cleveland 207 825 Detroit 254 1125 Houston 175 800 Kansas City 231 700 Los Angeles Angels 304 1300 Minnesota 223 895 New York Yankees 508 3200 Oakland 202 725 Seattle 250 1100 Tampa Bay 188 625 Texas 266 1220 Toronto 226 870 Arizona 211 840 Atlanta 267 1150 Chicago Cubs 302 1800 Cincinnati 227 885 Colorado…
The table shows a country's average fuel consumption for "light duty" vehicles (passenger cars and small trucks) for several years. Let x be the number of years since 1985, so that x = 5 stands for 1990 and so forth. Year Fuel Economy (mpg) 1990 16.9 1995 17.7 2000 18.3 (a) Find the linear regression model for these data. What does the slope in the regression model represent? 2005 18.9 (b) Use the linear regression model to predict the country's average fuel economy for light duty vehicles in the year 2035. 2010 19.6 (a) Find the linear regression model for these data. Choose the correct answer below. (Use integers or decimals for any numbers in the equation. Round to the nearest hundredth as needed.)
What is the explanatory variable, what is the response variable. What is the regression equation for this data. Plot the regression line in your calculator and draw it on your graph. Interpret in context the slope. Interpret in context the y-intercept. What is the residual at 45 years of age. Plot the residual plot on the axis to the right

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