The total amount of consumer credit has been increasing steadily in recent years. The following table gives the totaloutstanding consumer credit (in billions of dollars). Answer parts (a) through (e) below.Year20042005200620072008ConsumerCredit2210.52319.82415.02551.92592.1Year20092010201120122013GOTOConsumerCredit2551.52643.12756.02924.33094.2a. Find an equation for the least squares line, letting x equal the number of years since 2000.The equation is Y=x+0(Use integers or decimals for any numbers in the equation. Round to two decimal places as needed.) Part 2b. Based on the answer to part (a), at approximatelywhat rate is consumer credit growing per year?The consumer credit is growing about $ billion peryear.(Round to two decimal places as needed.)Part 3c. Use the result from part (a) to predict the amountof consumer credit in the year2016The amount of consumer credit in the year2016 will be $ billion.(Round to the nearest whole number.)Part 4d. If this trend continues linearly, in what year will thetotal debt first exceed $4000 billion?Part 5e. Find and interpret the correlation coefficient.Select the correct choice below and fill in the answerbox to complete your choice.(Type an integer or decimal rounded to four decimalplaces as needed.

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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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We use the form ŷ = a + bx for the least-squares line. In some computer printouts, the least-squares equation is not given directly. Instead, the value of the constant a is given, and the coefficient b of the explanatory or predictor variable is displayed. Sometimes a is referred to as the constant, and sometimes as the intercept. Data from a report showed the following relationship between elevation (in thousands of feet) and average number of frost-free days per year in a state. A Minitab printout provides the following information. Predictor Coef SE Coef T P Constant 315.27 28.31 11.24 0.002 Elevation -31.812 3.511 -8.79 0.003 S = 11.8603 R-Sq = 96.8% Notice that "Elevation" is listed under "Predictor." This means that elevation is the explanatory variable x. Its coefficient is the slope b. "Constant" refers to a in the equation ŷ = a + bx. (a) Use the printout to write the least-squares equation. ŷ = + x (b) For each 1000-foot increase in elevation,…
We use the form ŷ = a + bx for the least-squares line. In some computer printouts, the least-squares equation is not given directly. Instead, the value of the constant a is given, and the coefficient b of the explanatory or predictor variable is displayed. Sometimes a is referred to as the constant, and sometimes as the intercept. Data from a report showed the following relationship between elevation (in thousands of feet) and average number of frost-free days per year in a state. A Minitab printout provides the following information. Predictor Coef SE Coef T P Constant 316.62 28.31 11.24 0.002 Elevation -30.516 3.511 -8.79 0.003 S = 11.8603 R-Sq = 96.2% The printout gives the value of the coefficient of determination r2. What is the value of r? Be sure to give the correct sign for r based on the sign of b. (Round your answer to four decimal places.) What percentage of the variation in y can be explained by the corresponding variation in x and the least-squares…
2. The Mach number of a moving object is the ratio of its speedto the speed of sound. The following table shows the speeds of a jet aircraft, in terms of Mach numbers, and the time tafter it starts to accelerate. Find the least- squares line of s as a function of t. t(min) 0.00 s(Mach Number) 0.88 0.60 0.97 1.20 1.03 1.80 1.11 2.40 1.19 3.00 1.25
When a stone is dropped in a pond, ripples are formed and travel in concentric circles away from where the stone was dropped. The equation of the least-squares regression line is log(Area) = 0.490 + 2.004 log(Time). WWhat is the predicted area of the circle, in cm2, 4 seconds after the stone is dropped? O 49.72 cm2 O 199.43 cm2 O 311.89 cm? O 1854.10 cm2
terpreting technology: A biologist computed a least-squares regression line for predicting the brain weight in grams of a bird from its body weight in grams. e results are presented in the following Excel output. Coefficients Intercept 3.74691917 Body Weight 0.08444928 Part: 0 / 2 Part 1 of 2 Write the equation of the least-squares regression line. Use the full accuracy shown in the Excel output (do not round your answers). Regression line equation: y X 3
Interpreting technology: A biologist computed a least-squares regression line for predicting the brain weight in grams of a bird from its body weight in grams. The results are presented in the following Excel output. Coefficients Intercept 3.68952298 Body Weight 0.07800925 Part: 0 / 2 Part 1 of 2 Write the equation of the least-squares regression line. Use the full accuracy shown in the Excel output (do not round your answers). Regression line equation: y = X
Data for motor vehicle production in a country for the years 1997 to 2004 are given in the table. Year 1997 1998 1999 2000 2001 2002 2003 2004 Thousands 1,578 1,671 1,805 2,009 2,391 3,219 4,415 5,092 (A) Find the least squares line for the data, using x = 0 for 1990. y = (Use integers or decimals for any numbers in the expression. Do not round until the final answer. Then round to the nearest tenth as needed.)
Percentages of public school students in fourth grade in 1996 and in eighth grade in 2000 who were at or above the proficient level in mathematics are given for eight western states. Find the equation of the least-squares line that summarizes the relationship between x = 1996 fourth-grade math proficiency percentage and y = 2000 eighth-grade math proficiency percentage. (Give the numerical values to four decimal places.) |4th grade 8th grade (1996) State (2000) Arizona 15 21 California 11 18 Hawaii 16 16 Montana 22 37 New Mexico 13 13 Oregon 21 32 Utah 23 26 Wyoming 19 25 n USE SALT ŷ =

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Year 2004 2005 2006 2007 2008 Consumer Credit 2210.5 2319.8 2415.0 2551.9 2592.1 Year 2009 2010 2011 2012 2013 Consumer Credit 2551.5 2643.1 2756.0 2924.3 3094.2 nd an equation for the least squares line, letting x equal the number of yea