. Consider the scatterplot and least-squares regression line shown here.20000+15000+10000+y5000-of-5000-012345678910x Which of the following could represent a residual plot for this fit?(A)(B)0(E)Residuals01 2 3 45 6 7 8 9 10x012 3456 7 8 9 10x012 3 4 5 6 7 8 9 100123456 7 8 9 10xx0123456 79 10x

In order to determine which residual plot could represent a good fit, we need to understand the…

Answered: . Consider the scatterplot and…

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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The tables show the amount of revenue (y) in billions for different companies x years after 2005. Match the table with the correct description of its regression model and correlation. Negative Linear Regression 1. a0 1 2 3 4 5 6 78 9 10 Strong Negative Correlation y 12 12 13 14 15 16 18 19 21 22 25 Positive Linear Regression * 0 1 2 3 4 5 6 7 89 10 y 20 18 17 15 13 14 16 18 21 25 28 2. Strong Positive Correlation Quadratic Regression * 0123 4 5 6 7 8 9 10 3. Strong Positive Correlation y 5679 13 15 18 24 25 28 30 Increasing Exponential Regression 4. x0 1 2 3 4 5 6 789 10 Strong Positive Correlation y 20 20 19 18 16 15 12 8765 Decreasing Exponential Regression z0 1 2 3 4 5 6 7 8 9 10 5. Strong Negative Correlation y 20 19 20 18 16 15 13 11 10 11 10
For a linear regression problem, the least squares line is y = 2x+2. Determine the predicted value of y when x = 5 19 not enough information 12 oooo
Suppose there is 1 dependent variable (dissolved oxygen, Y) and 3 independent variables (water temp X1, depth X2, and hardness of water X3). Below is the result of the multiple linear regression. Coefficients Standard Error t Stat P-value Intercept 24.84 4.36 5.69 0.00 Water Temperature (C) -1.17 0.37 -3.20 0.02 Depth (feet) -0.15 0.24 -0.61 0.56 Hardness as mg/L CaCO3 -0.04 0.04 -0.95 0.37 Which of the three independent variable(s) is (are) significant predictor(s) of dissolved oxygen? Use .05 level of significance.
year- 2000,2005,2010,2014,2019 tuition-$1242,$1809,$2680,$3356,$5132 what is the equation for the least squares regression line? what will tuitions be for the year 2025? when will tuitions be $6500?
The equation of the least-squares regression line is ý = 68.5 + 11.4x, where ý is the number of students enrolled and x is number of years the school has been The number of students enrolled at a school varies from year to year. For the first eight years the school is open, the number of students enrolled is recorded in the table shown. open. Which shows the residual plot? Students 92 Year 2. 94 100 104 80 4 60 113 131 40 7. 8. 147 176 20 -20 0. 2. 4. 8. Number of Years 3. 56
The poverty level for a family of four, two parents with two children under 18, for selected years from 1990 is shown in the following table. Poverty Threshold for a Family of Four Year 1990 1997 2000 2005 Threshold $14,300 $15,400 $18,800 $20,150 (a) Find the least squares linear regression function for threshold level as a function of years since 1990. (Let x = 0 represent the year 1990. Round your coefficients to one decimal place.) y = (b) Use the linear function to estimate when the poverty threshold level will reach $27,000. (Round your answer down to the nearest year.) The threshold level is estimated to reach $27,000 in the year 2016
Use least squares regression to fit a line to the table data below.
Draw a graph of the least-squares regression line on your scatterplot. (For hand-drawing, round the slope and y-intercept to one decimal place before drawing the line.) Be sure to show how you were able to plot the line starting with its equation. Model City Miles per Gallon Highway Miles per Gallon Acura RLX 20 29 BMW 530i 24 34 Buick LaCrosse eAssist 25 35 Chevrolet Malibu 29 36 Ford Hybrid FWD 43 41 Honda Civic 32 42 Infiniti Q50 Red Sport 20 26 Kia Forte 30 40 Lexus ES 350 22 33 Mercedes Benz AMG S 21 30 Mini Cooper Clubman 24 32 Nissan Maxima 20 30 Suburu Legacy AWD 25 34 Toyota Prius ECO 58 53
For a linear regression problem, The actual observed y-value when x = 2 is y = 6. The least squares line is y = 2x+1. The predicted value when x=2 is y = 5. Determine the value of the residual (prediction error) oooo 1 6 5 Cannot be determined from the information given
Fit the regression line X1 3 5 6 8 12 14 X2 16 10 7 4 3 2
5. Write the equation of the least-squares regression line defining any variables used. Round coefficients to 4 decimal places .
A student is preparing to take a stand allies exam she was told that she needs to get plenty of sleep the night before the exam she is interested in the relationship between the number of hours of sleep a student gets her for an exam and the score earned on the exam. She collects information from 10 other students who have already taken the exam as shown on the table. she fits at least squares regression line to the data and determines the equation of the line is why equals 26-0.18 X where why is the score earn on the exam and ask is the number of hours of sleep the night before the exam. The residual is given. based on the residual plot is the linear model appropriate? no, there is no clear pattern in the residual plot. yes, there is no clear pattern in the residual plot. no, the student who got the most you've had a negative residual yes, there are more negative residuals (6) then positive residuals (4)

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