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# What one what correlation coefficients reflects the strongest relationship between two variables?

Updated: 12/5/2022

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Q: What one what correlation coefficients reflects the strongest relationship between two variables?
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### What correlation coefficients represents a situation in which there is no relationship between variables?

We would need to have the list of correlation coefficients to respond to this question.

### Define correlation coefficients?

Correlation coefficients measure the strength and direction of a relationship between two variables. They range from -1 to 1: a value of 1 indicates a perfect positive correlation, -1 indicates a perfect negative correlation, and 0 indicates no correlation. They are commonly used in statistics to quantify the relationship between variables.

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### What is the strongest a correlation could be?

Either +1 (strongest possible positive correlation between the variables) or -1 (strongest possible negativecorrelation between the variables).

### What are the possible ranges of correlation coefficients?

The possible range of correlation coefficients depends on the type of correlation being measured. Here are the types for the most common correlation coefficients: Pearson Correlation Coefficient (r) Spearman's Rank Correlation Coefficient (ρ) Kendall's Rank Correlation Coefficient (τ) All of these correlation coefficients ranges from -1 to +1. In all the three cases, -1 represents negative correlation, 0 represents no correlation, and +1 represents positive correlation. It's important to note that correlation coefficients only measure the strength and direction of a linear relationship between variables. They do not capture non-linear relationships or establish causation. For better understanding of correlation analysis, you can get professional help from online platforms like SPSS-Tutor, Silverlake Consult, etc.

### Why are auxiliary regressions more general means of identifying collinear relationships between variables than correlation coefficients?

Where only bivariate collinear relations exist, a matrix of correlation coefficients is a perfectly adequate diagnostic tool for identifying collinearity. However, they are incapable of diagnosing a collinear relationship involving more than two indepdendent variables. This is the advantage of auxilliary regression. They allow a researcher to detect a collinear relationship between as many independent variables as the researcher requires.

### What are the three different types of correlation?

The three different types of correlation are positive correlation (both variables move in the same direction), negative correlation (variables move in opposite directions), and no correlation (variables show no relationship).

### If coefficient of correlation r between two variables is zero does it mean that there is no relationship between the variables Justify your answer?

"If coefficient of correlation, "r" between two variables is zero, does it mean that there is no relationship between the variables? Justify your answer".

### What is positive Correlation?

Positive correlation is a relationship between two variables in which both variables move in tandem that is in the same direction.

### What is a zero correlation?

a zero correlation means that there is no relationship between the two or more variables.

### What is correlatational study?

A correlational study is a research method that examines relationships between variables without manipulating them. It aims to determine if and to what extent a relationship exists between two or more variables, but it does not establish causation. The strength and direction of the relationship are typically measured using statistical techniques such as correlation coefficients.

### A relationship between two or more variables that is shown in an observational study is a?

Correlation-apex (;