You can find your regression equation after you have found what?

You can find your regression equation after you have found what?

• A. Pearson's r
• B. Spearman's rho
• C. Chi-square value
• D. Standard deviation

Answer: (A)

The main idea is that the regression equation for a simple linear relationship relies on how strongly and in what direction the two variables are related, which is measured by Pearson’s correlation coefficient. In simple linear regression, the slope of the line is calculated using that correlation together with the standard deviations of the variables: slope = r × (sy / sx). The intercept is then found from the means: intercept = ȳ − (slope × x̄). So you can write the regression equation once you have the correlation coefficient. Spearman’s rho is a rank-based measure suited for monotonic or ordinal relationships, not the standard linear regression slope calculation. Chi-square is used for categorical data to test independence or goodness of fit, not to derive a regression line. Standard deviation describes dispersion within one variable, not the relationship between two variables needed to form the regression equation.

The main idea is that the regression equation for a simple linear relationship relies on how strongly and in what direction the two variables are related, which is measured by Pearson’s correlation coefficient. In simple linear regression, the slope of the line is calculated using that correlation together with the standard deviations of the variables: slope = r × (sy / sx). The intercept is then found from the means: intercept = ȳ − (slope × x̄). So you can write the regression equation once you have the correlation coefficient.

Spearman’s rho is a rank-based measure suited for monotonic or ordinal relationships, not the standard linear regression slope calculation. Chi-square is used for categorical data to test independence or goodness of fit, not to derive a regression line. Standard deviation describes dispersion within one variable, not the relationship between two variables needed to form the regression equation.