Find the required linear model using least-squares regression.The following table shows the number of operating federal credit unions in a certain country for several years.20112012201320142015444842783774YearNumber of federal creditunions(a) The linear model for these data is y =(Round to the nearest tenth as needed.)4114(a) Find a linear model for these data with x = 11 corresponding to the year 2011.(b) Assuming the trend continues, estimate the number of federal credit unions in the year 2016.X +3944O.

The given data, Year 2011 2012 2013 2014 2015 Number of federal credit unions 4448 4278 4114…

Answered: Find the required linear model using…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Find the required linear model using least-squares regression. The following table shows the number of operating federal credit unions in a certain country for several years. 2011 2012 2013 2014 4426 4255 4094 3919 Year Number of federal credit unions (a) The linear model for these data is y = (Round to the nearest tenth as needed.) (a) Find a linear model for these data with x = 11 corresponding to the year 2011. (b) Assuming the trend continues, estimate the number of federal credit unions in the year 2018. X + 2015 (b) The estimated number of credit unions for the year 2018 is (Round to the nearest integer as needed.) 3752
Find the required linear model using least-squares regression. The following table shows the number of operating federal credit unions in a certain country for several years. 2011 2012 2013 2014 4497 4323 4156 3976 Year Number of federal credit unions (a) The linear model for these data is y = (Round to the nearest tenth as needed.) (a) Find a linear model for these data with x = 11 corresponding to the year 2011. (b) Assuming the trend continues, estimate the number of federal credit unions in the year 2018. X + 2015 (b) The estimated number of credit unions for the year 2018 is (Round to the nearest integer as needed.) 3807
Report the equation of the regression line and interpret it in the context of the problem
. Extent of Arctic Sea Ice The National Snow and Ice Data Center monitors the amount of ice in the Arctic year round. The table below gives approximate values for the sea ice extent in millions of square kilometers from 1986 to 2012, in two-year intervals. (a) Make a scatter plot of the data. (b) Find and graph the regression line. (c) Use the linear model in part (b) to estimate the ice extent in the year 2016. Ice extent Ice extent Year (million km?) Year (million km?) 1986 7.5 2000 6.3 1988 7.5 2002 6.0 1990 6.2 2004 6.0 1992 7.5 2006 5.9 1994 7.2 2008 4.7 1996 7.9 2010 4.9 1998 6.6 2012 3.6 Source: National Snow and Ice Data Center
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 $millions) for the 30 Major League Baseball franchises. Suppose you want to develop a simple linear regression model to predict franchise value based on annual revenue generated. Team Revenue Value Baltimore 245 1000 Boston 370 2100 Chicago White Sox 227 975 Cleveland 207 825 Detroit 254 1125 Houston 175 800 Kansas City 231 700 Los Angeles Angels 304 1300 Minnesota 223 895 New York Yankees 508 3200 Oakland 202 725 Seattle 250 1100 Tampa Bay 188 625 Texas 266 1220 Toronto 226 870 Arizona 211 840 Atlanta 267 1150 Chicago Cubs 302 1800 Cincinnati 227 885 Colorado…
Capacity and price data for a collection of USB flash drives is displayed in the table below. Capacity (Gb) Price ($) 8 10 16 13 32 18 64 28 128 49 256 90 Use linear regression to find the best-fit line for the data, with capacity as the independent variable and price as the dependent variable. Round to 2 decimal places.
Develop an estimated multiple linear regression model that could be used to predict the alumni giving rate using the graduation, % of Classes Under 20, and Student/Faculty Ratio as independent variables. Discuss your findings. School SFR LT20 GT50 GRAD FRR GIVE Arizona State 24 42% 16% 59% 81% 8% Arkansas State—Jonesboro 19 49% 4% 37% 69% 11% Auburn 18 24% 17% 66% 87% 31% Air Force 8 74% 0.10% 81% 88% 11% Military Academy 8 95% 0% 86% 92% 28% Akron 20 39% 6% 35% 69% 15% Arizona 20 35% 17% 60% 79% 5% Arkansas 18 28% 18% 58% 83% 23% Ball State 18 34% 12% 57% 78% 11% Baylor 14 49% 9% 71% 85% 14% Boise State 21 33% 11% 27% 67% 8% Boston College 14 47% 6% 91% 96% 27% Bowling Green State 19 33% 7% 61% 75% 8% BYU 21 46% 12% 78% 84% 17% SUNY 16 36% 21% 67% 88% 9% Alabama 19 46% 16% 67% 85% 34% Central Michigan 22 32% 11% 54% 78% 8% Clemson 16 51% 13% 76% 91% 28% Colorado State 18 34% 19% 64% 83% 7% Berkley 17 62% 15% 91% 97% 12% Cincinnati…
The table lists the average tuition and fees at private colleges and universities for selected years. Year 1985 1990 1995 2000 2008 5311 25,115 Tuition and Fees (in dollars) 9375 SO 12,418 (a) Find the equation of the least-squares regression line that models the data. y 840.450 (Type the slope as a decimal rounded to three decimal places. Round the y-intercept to the nearest integer.) (b) Graph the data and the regression line in the same viewing window using the parameters given below the graph choices. Choose the correct graph below. OA. O B. o HE RO OC. 16,230 A o ƠN
Advertising and Sales. Use the technology of your choice to do the following. a. Obtain the scatterplot matrix for the data. b. Use the scatterplot matrix to assess whether a multiple linear regression model might be appropriate for predicting sales. c. Determine the regression equation for the data. d. Apply the regression equation to predict total sales if the amounts spent on television, magazine, and radio advertising are $9.5 million, $4.3 million, and $5.2 million, respectively.
a) Determine the least squares regression equation for the population in years since 2005. Round the slope and y-intercept to the nearest tenth. b) Find the correlation coefficient, r-value, of the line. Round your answer to the nearest thousandth. c) Predict the population for the 2020. ____ thousand people
he table shows the minimum wage rates for the United States during different years. Year 1978 1979 1980 1990 1991 1996 1997 2007 2008 2009 Minimum hourly wage ($) 2.65 2.90 3.35 3.80 4.25 4.75 5.15 5.85 6.55 7.25 Write the least squares regression equation that models the data. Let x = time in years since 1900 and let y = minimum hourly wage. Use the equation to estimate the minimum hourly wage of a U.S. worker in 2025. Show your work. Answer:

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