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Theory, analysis and interpretation of regression

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Theory of regression:
How does regression relate to linear algebra?

Regression terms and symbols:
What is the difference between strong negative and strong positive?

Practical examples of regression analysis:
When would you use regression correlation at a place of employment, or in education, or in politics?

Interpretation of regression outputs in Microsoft Excel:
How do you identify outliers in your data? How do they impact your regression equation?

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Solution Preview

Linear Algebra describes a very powerful method of solving linear equations by matrix method. Since in regression we need to solve for the coefficients of the regression line, matrix method can be used to this end. In this way, linear algebra can help perform linear regression.

The correlation coefficient is a number between -1 and 1 which measures the degree to which two variables are linearly related. If there is perfect ...

Solution Summary

This solution explains regression in terms of linear algebra, strong negative and positive, practical examples, and outliers.