The least-square regression line for the given data is y=-0.206x + 2.097. Determine the residual of a data point forwhich x= 1 and y=-3, rounding to three decimal places.X -5y11OA. - 4.891OB. - 1.715O C.- 1.109OD. 1.891- 3-6481- 3- 1-2-21ло0525-536-407

given data regression equation : y^ = -0.206x + 2.097when x= 1;y = -3find residual at that point =…

Answered: The least-square regression line for…

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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37-38. Given the following data pairs (x, y): (1, 1.24), (2, 5.23). (3, 7.24). (4, 7.60), (5, 9.97), (6, 14.31), (7, 13.99).(8, 14.88), (9, 18.04), (10, 20.70). Find the regression equation O A. y = 0.490 x - 0.053 O B. y = 2.04 x O C. y = 1.98 x + 0.436 O D. y = 0.49 x
8
H. Find the slope and y-intercept of each regression line. Then, determine if the correlation between the variables is positive or negative. (12 points) Regression Line Equation 1. Y = 1.751X – 21.722 Slope y-intercept Kind of Correlation 2. Y = -221.943X+65.434 3. Y = -82.455X –314.986 4. Y = 0.997X + 0.168
The sales of a company (in million dollars) for each year shown in the table below (25)X(year) 2005 2006 2007 2008 2009Y (sales) 12 19 39 37 45a. Find the regression line of the data. Draw the inference about the dataset.b. Use the regression line as a model to estimate the sales of the company in 2012.
An automobile rental company wants to predict the yearly maintenance expense (Y) for an automobile using the number of miles driven during the year () and the age of the car (, in years) at the beginning of the year. The company has gathered the data on 10 automobiles and run a regression analysis with the results shown below:. Summary measures Multiple R 0.9689 R-Square 0.9387 Adj R-Square 0.9212 StErr of Estimate 72.218 Regression coefficients Coefficient Std Err t-value p-value Constant 33.796 48.181 0.7014 0.5057 Miles Driven 0.0549 0.0191 2.8666 0.0241 Age of car 21.467 20.573 1.0434 0.3314 Use the information above to estimate the annual maintenance expense for a 10 years old car with 60,000 miles.
Use the regression equation to predict the value of y for x = -1.6. Assume that the variables x and y have a significant correlation. -5-34 1 -1-2 X 0 2 3 -4 y - -10 8 9 1 -2-6 -1 3 6 -8 OA. 1.214 OB. -2.803 O C. 2.980 OD. -3.907

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The least-square regression line for the given data is y=-0.206x + 2.097. Determine the residual of a data point for which x= 1 and y=-3, rounding to three decimal places. X y -5 11 OA. -4.891 B. -1.715 C. -1.109 OD. 1.891 -3 -6 4 8 1 - 3 -1 -2 -2 1 05 2 -5 36 -40 7