Question

For each of the statements below, is it true with Correlation, Regression, Both, or Neither? Please explain. Thank You!
1. Requires a measure for both variables'individual variances
2. Can be tested for statistical significance
3. Provides a way to predict a specific value of one variable (such as weight) from the value of another variable (such as height)

Answer 1

1. True of both correlation and regression. Both requires a measure for both variables individual variances.
2. True of both correlation and regression. Both can be tested for statistical significance.
3. True of regression. Regression provides a way to predict a specific value of one variable from the value of another variable.

1. Correlation is a bivariate analysis that measures the strength of association between two variables and the direction of the relationship. Regression is a statistical method to determine the strength and character of the relationship between one dependent variable and a series of other variables (known as independent variables). So, both correlation and regression require a measure for both variables individual variances.

2. We can test for the statistical significance of a correlation coefficients by performing a hypothesis test on the correlation coefficients. And it's also possible to perform hypothesis tests on the regression slope on the values which is being estimated using a regression analysis. So, both correlation and regression can be tested for statistical significance.

3. Correlation helps us to test the strength of association between two variables. But regression helps us to predict one of the variables from the other. So, it is true for a regression. It is only regression which provides a way to predict a specific value of one variable from the value of another variable.

Learn more about correlation and regression at: https://brainly.com/question/29820584

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