Match the regression equation with the appropriate graph.Drag each graph given below to its corresponding regression equation to the right.13. y = - 1.361x+ 21.952NyAy140-30-120-25-100-20-80-15-60-40-10-20-5-14. y = 2.115x+21.9581020304050248.10AyAy30-70-60-25-50-20-40-15-30-10-20-5-10-15. y = 2.125x + 9.5885 10 15 20 25 30 35 405101520253016. y = - 0.705x + 27.214

since, slope is upwards to the right, so positive slope. and y-intercept is nearly 21, so correct…

Answered: Match the regression equation with the…

Match the regression equation with the appropriate graph. Drag each graph given below to its corresponding regression equation to the right.

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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Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

Match the regression equation with the appropriate graph.
Drag each graph given below to its corresponding regression equation to the right.
13. y = - 1.361x+ 21.952
Ny
Ay
140-
30-
120-
25-
100-
20-
80-
15-
60-
40-
10-
20-
5-
14. y = 2.115x+21.958
10
20
30
40
50
2
4
8.
10
Ay
Ay
30-
70-
60-
25-
50-
20-
40-
15-
30-
10-
20-
5-
10-
15. y = 2.125x + 9.588
5 10 15 20 25 30 35 40
5
10
15
20
25
30
16. y = - 0.705x + 27.214

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