Pls help I need in one hour Thankyou ### Understanding Residuals and Regression Lines#### a. What is a residual?- **A.** A residual is a point that has a strong effect on the regression equation.- **B.** A residual is a value of \( y - \hat{y} \), which is the difference between an observed value of \( y \) and a predicted value of \( y \).- **C.** A residual is a value that is determined exactly, without any error.- **D.** A residual is the amount that one variable changes when the other variable changes by exactly one unit.#### b. In what sense is the regression line the straight line that "best" fits the points in a scatterplot?The regression line has the property that the [sum or sum of squares] of the residuals is the [smallest or largest] possible sum.- Options for first box: sum, sum of squares- Options for second box: smallest, largestThis section provides a multiple-choice format to help understand the concept of residuals in statistical analysis and the properties of regression lines in scatterplots. The interactive aspect allows learners to consider and select the correct definitions and implications in the context of data fitting. **Title: Understanding Residuals and Regression Lines****a. What is a residual?**1. **A.** A residual is a point that has a strong effect on the regression equation.2. **B.** A residual is a value of \( y - \hat{y} \), which is the difference between an observed value of \( y \) and a predicted value of \( y \).3. **C.** A residual is a value that is determined exactly, without any error.4. **D.** A residual is the amount that one variable changes when the other variable changes by exactly one unit.**b. In what sense is the regression line the straight line that "best" fits the points in a scatterplot?**The regression line has the property that the [Dropdown: "sum of the squares"] of the residuals is the [Dropdown: "lowest"] possible sum. **Explanation:**In the context of linear regression, residuals represent the discrepancies between the observed values and the values predicted by the regression model. The goal is to minimize these discrepancies to find the best-fitting line. The method used is typically least squares, which minimizes the sum of the squares of the residuals, ensuring the most accurate prediction possible for the given data.

Here we need to define residual and best fit of the scatter plot.

a. What is a residual? b. In what sense is the regression line the straight line that "best" fits the points in a scatterplot? a. What is a residual? O A. A residual is a point that has a strong effect on the regression equation. O B. A residual is a value of y -y, which is the difference between an observed value of y and a predicted value of y. OC. A residual is a value that is determined exactly, without any error. O D. A residual is the amount that one variable changes when the other variable changes by exactly one unit. b. In what sense is the regression line the straight line that "best" fits the points in a scatterplot? The regression line has the property that the V of the residuals is the V possible sum. sum sum of squares

a. What is a residual? b. In what sense is the regression line the straight line that "best" fits the points in a scatterplot? a. What is a residual? O A. A residual is a point that has a strong effect on the regression equation. O B. A residual is a value of y -y, which is the difference between an observed value of y and a predicted value of y. OC. A residual is a value that is determined exactly, without any error. O D. A residual is the amount that one variable changes when the other variable changes by exactly one unit. b. In what sense is the regression line the straight line that "best" fits the points in a scatterplot? The regression line has the property that the V of the residuals is the V possible sum. sum sum of squares

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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