Macmillan LearningSelect all the statements that are true of a least-squares regression line.Theslope of the regression line is resistant to outliers.In the equation of the least-squares regression line, Y is a predicted value when X is known.The regression line maximizes the residuals between the observed values and the predicted values.In the equation of the least-squares regression line, Ŷ is an observed value when X is known.R² measures how much of the variation in Y is explained by X in the estimated linear regression.The sum of the residuals is always close to zero.

Objective of this question is that which options are correct choice for the regression line.

Answered: Select all the statements that are true…

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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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.
Use The t Distribution Table to find the t, value for a 98% confidence interval for the mean when the sample size is 17. a/2 ta/2=
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The image contains two graphs typical of the analysis of a simple linear regression model. It can be stated that: a. The variance of the errors seems constant b. The errors do not come from a normal distribution c. The linear model does not seem appropriate d. The residuals are close to the line and therefore there is normality in the data. Why? Thanks
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