Question

if the lines of regression are parallel to coordinate axis than the coefficient of correlation is​

Answer 1

Answer:

Zero

Step-by-step explanation:

Answer 2

Concept: Procedures for forecasting can benefit from using regression lines. Its goal is to describe how the dependent variable (y variable) and one or more independent variables are related (x variable).

When modelling the relationship between a scalar answer and one or more explanatory variables in statistics, linear regression is a linear method. Simple linear regression is used when there is only one explanatory variable; multiple linear regression is used when there are numerous explanatory variables.

To gauge how closely two variables are related to one another, correlation coefficients are used. The most common correlation coefficient is Pearson's, though there are other varieties as well. The correlation coefficient known as Pearson's correlation, sometimes known as Pearson's R, is frequently employed in linear regression. When learning statistics for the first time, you'll probably start with Pearson's R. In fact, Pearson's is typically mentioned when someone mentions the correlation coefficient.

Given: the lines of regression are parallel to coordinate axis

To find: the coefficient of correlation

Solution: Refer the figure for clear explanation

if the lines of regression are parallel to the co-ordinate axis then the coefficient of correlation r = 1.

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