First Part Conduct an investigation taking into consideration the following concepts: Correlation coefficient Simple linear regression Dependent variable Independent variable Regression line Explain...

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Answered 1 days AfterJun 28, 2021

Answer To: First Part Conduct an investigation taking into consideration the following concepts: Correlation...

Mohd answered on Jun 30 2021
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First Part
Conduct an investigation taking into consideration the following concepts:
Correlation coefficient
The sole purpose of correlation coefficients are to evaluate strength of relationship between
two continuous variables. There are three methods to evaluate correlation coefficients Pearson, Spearman, and kendall. Generally we use Pearson correlation in linear regression. Correlation coefficients vary from -1 to 1. Negative correlation coefficient(coefficient value between -1 to 0) indicates inverse relationship between variables. Positive correlation(coefficient value between 0 to 1) coefficient indicates direct relationship between variables.
Simple linear regression
Simple linear regression is a statistical tool which enables us to describe and investigate relationships between two continuous variables. In simple linear regression we have one predictor and one response variable.
First variable can be represented as a response variable (quantitative dependent variable). Second Variable can be represented as an explanatory variable or independent variable. Explanatory variables are also termed as predictors.
Dependent variable:
The change in dependent variable depends on independent variables. If we examine children's age and height. Height will be a dependent variable and age will be an independent variable. As we know, if we increase the age , the height of the child is likely to be higher. Child age does not depend on any variable except itself.
Independent variable:
If we examine children's age and height. Height will be a dependent variable and age will be an independent variable. As we know, if we increase the age , the height of the child is likely to be higher. Child age does not depend on any variable except itself.
Regression line:
The linear relationship between two variable can be formulated as below.
y = mx + c
Where
y = dependent variable
m = Slope of the line
x = independent variables
C= Intercept of the line.
Explain the assumptions of the simple linear regression model.
Assumption 1: Linear...
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