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Collaborative Statistics: Linear Regression and Correlation: Homework Susan Dean and Barbara Allows, PhD EXERCISE 1 For each situation below, state the independent variable and the dependent variable.

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What is regression and correlation?

Regression is a statistical analysis technique used to determine the relationship between dependent and independent variables. Correlation, on the other hand, measures the strength and direction of the linear relationship between two variables.

Who is required to file regression and correlation?

Regression and correlation are typically performed by researchers, statisticians, or analysts who want to analyze data and understand the relationship between variables.

How to fill out regression and correlation?

To fill out regression and correlation, you need to collect the data for both dependent and independent variables. Then, you can use statistical software or tools to perform the analysis and generate the regression and correlation results.

What is the purpose of regression and correlation?

The purpose of regression and correlation is to understand and quantify the relationship between variables. Regression helps in predicting the value of the dependent variable based on the values of independent variables, while correlation helps in determining the strength and direction of the relationship.

What information must be reported on regression and correlation?

In regression, the coefficients, p-values, and R-squared value are typically reported. For correlation, the correlation coefficient (r) and p-value are reported.

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