For parts a and b, round all number values in your answer to the nearest hundredth. a) The linear regression equation is y = _________________________ b) The exponential regression equation is y = _________________________ c) Which regression model is the better choice, linear or exponential? _________________ d) To the nearest thousandth, what is the r-value for the better model? ________________ 13. Use your calculator to make two lists and a scatterplot for the data below. Find both thelinear and exponential equations-of-best-fit, (regression equations) and the correspondingr values fore each equation. Then answer the questions that follow.X•WNHOS0123456y2824.520.41715.513.912.7

X Y 0 28 1 24.5 2 20.4 3 17 4 15.5 5 13.9 6 12.7 Note that here we will solve this…

For parts a and b, round all number values in your answer to the nearest hundredth. a) The linear regression equation is y = _________________________ b) The exponential regression equation is y = _________________________ c) Which regression model is the better choice, linear or exponential? _________________ d) To the nearest thousandth, what is the r-value for the better model? ________________

For parts a and b, round all number values in your answer to the nearest hundredth. a) The linear regression equation is y = _________ b) The exponential regression equation is y = _ c) Which regression model is the better choice, linear or exponential? _ d) To the nearest thousandth, what is the r-value for the better model? ________

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

) In a regression equation to what does a refer? ) What does the regression coefficient, or b, account for in a regression equation? ) If b = 3 and a = 7, a person with a score of x = 15 would be predicted to have a score y = __________. ) r-squared (r2) is the _______________________________________________. What does this tell us? ) What does the coefficient of non-determination tell us?
Fill in the blanks.a. In multiple linear regression, a(n) _______ is a data point that lies far from the multiple linear regression plane, relative to the other data points.b. In multiple linear regression, a(n) _______ is a data point whose removal causes the multiple linear regression equation to change considerably.
A sales manager collected the following data on annual sales for new customer accounts and the number of years of experience for a sample of 10 salespersons. Click on the datafile logo to reference the data. DATA file A, 140 Annual Sales ($1000s) +120 +100 +80 +60 Salesperson 1 +40 2 3 4 5 6 7 8 9 10 Years of Experience 1 + 3 4 a. Choose the correct scatter diagram for these data with years of experience as the independent variable. 4 6 8 10 10 11 13 Annual Sales ($1000s) 80 97 92 102 103 111 119 123 117 136
esc The following estimated regression equation has been proposed to predict sales at a fast food outlet. ŷ = 51 - 5x₁ + 25x₂ + 12x3 where f1 1 Predict sales (in dollars) for the store with the competitor's previous day's sale of $6,000, a population of 29,000 within 1 mile, and five radio advertisements. $758 X ? x₁ = competitor's previous day's sales (in $1,000s) X1 Need Help? Read It Q x₂ = population within 1 mile (in 1,000s) X3 = 1 if radio advertising was used; 0 otherwise ý = estimated sales (in $1,000s) @ f2 2 * W f3 # * 3 E f4 ***** A $ 4 R f5 40 do O 5 f6 T 4- A 6 f7 ♫+ Y C & 7 fg KAA U * fg 8 hp DII f10 o DDI 9 f11 O f12. insert P prt sc + [ } K ] delete backspa
pediatrician wants to determine the relation that exists between a child's height, x, and head circur nd head circumferences and obtains the accompanying data. Complete parts (a) through (e). Data Table A Click the icon to view the data table. Round to four decimal places as needed.) Full data set B Нead Head (b) Use the regression equation to predict the head circumference of a child who is 25 inches tall. Height, x circumference, Height, x circumference, (inches) (inches) y (inches) y (inches) The predicted value of the head circumference of a child who is 25 inches tall is 17.05 inches. (Round to two decimal places as needed.) 27.75 17.7 26.5 17.3 24.5 17.1 27 175 25.5 17.1 26.75 17.3 (c) Compute the residual based on the observed head circumference of the 25-inch-tall child in the t 26 26.75 17.5 17.3 25 16.9 27.5 17.5 The residual based on the observed head circumference of the 25-inch-tall child is inches. 27.75 17.6 (Round to two decimal places as needed.) Print Done Enter your…
The following table shows unit sales of iPhones for the given year. t = years since 2010 0 1 2 3 I – units sold in millions 8 16 37 47 Find the equation of the regression line. ________________________ How many units sold does the regression line predict for 2015? ________________________ Explain in practical terms the meaning of the slope.
C) if a country increases its life expectancy, the happiness index will increase or decrease d) if the life expectancy is increased by 4.5 years in a certain country .how much will the happiness index change? Round two decimal places e) use the regression line to predict that happiness index of a country with a life expectancy of 89 years . Round to two decimal places use the space below to type your answers
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The number of hours 6 students spent for a test and their scores on that test are shown below. Hours spent studying, x Test score, y 4 (a) x = 2 hours (c) x = 13 hours (b) x= 2.5 hours (d) x = 4.5 hours 2 3 5 40 45 52 49 63 70 Find the regression equation. ý =x+ (O (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. O A. OB. OC. OD. 80- 80- Hours studying Hours studying Hours studying Hours studying (a) Predict the value of y for x= 2. Choose the correct answer below. O A. 52.2 О В. 49.2 ОС. 64.2 O D. not meaningful (b) Predict the value of y for x = 2.5. Choose the correct answer below. O A. 115.4 О В. 52.2…
Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a year in which there are 450 metric tons of lemon imports. Is the prediction worthwhile? 233 270 Lemon Imports Crash Fatality Rate 16 15.9 B ew an example Get more help w S Find the equation of the regression line. ŷ=0+0x (Round the y-intercept to three decimal places as needed. Round the slope to four decimal places as needed.) X f 3 E D HO C 358 492 535 D 15.6 15.3 15 $ 4 R 74 F V % 5 T G NVAC 6 B MacBook Air Y H 7 N U J 8 EHEE F I M ( 9 K 2 ww O O L qqqqqqqqı 10 P command Clear all > 31 { . ; I option ? Check answer 11 I Gw 1 delete
P QUESTION 2 The value V of a piece of equipment between 1990 and 1995 is given in the table. Let t represent the year with t = 0 corresponding to 1990. Find the regression equation for the data in the table: Time, t 0 Value, V ($) 500 O y = 514.770(0.8x O y = -50x + 500 Oy=-x2 - 50x + 500 O y = 50x + 500 QUESTION 3 1 2 3 4 5 450 400 350 400 350 300 250 The table gives the average heights of children for ages 1-10, where x = the age (in years) and y = the height (in cm). 3 4 5 6 7 8 9 10 1 Age (years) Click Save and Submit to save and submit. Click Save All Answers to save all answers. 2 E; M 64 Save All Answer
Fill in the blanks. a. The cross-product term in a regression equation is often referred to as an _______ term. b. If two predictor variables x1 and x2 interact, then the change in the conditional mean of y for a change of one unit in x2 (with x1 held fixed) depends on _______. c. In a regression model, the cross-product term between x1 and x2 is given by ________.
Use the following linear regression equation to answer the questions. x1 = 2.0 + 3.6x2 – 7.8x3 + 2.1x4 a) Which variables are the explanatory variables? (Select all that apply.) x3 x1 x2 x4 (b) Which number is the constant term? List the coefficients with their corresponding explanatory variables. constant _____ x2 coefficient _____ x3 coefficient _____ x4 coefficient ______ (c) If x2 = 9, x3 = 3, and x4 = 6, what is the predicted value for x1? (Use 1 decimal place.)