why is regression mainly connected to models and equations while correlation is mainly connected to numeric...

why is regression mainly connected to models and equations while correlation is mainly connected to numeric variables? Could it be used differently ?

Expert Solution

Its about regression and correlation.

orchestra answered 1 year ago

True or False: Regression analysis is used for prediction, while correlation analysis is used to measure...

True or False: Regression analysis is used for prediction, while correlation analysis is used to measure the strength of the association between two numerical variables. A. True B. False In performing a regression analysis involving two numerical variables, we are assuming A. the variances of X and Y are equal. B. the variation around the line of regression is the same for each X value. C. that X and Y are independent. D. All of these. Which of the following...

Use table below to analyze correlation and to develop regression equations describing the relationships between person’s...

Use table below to analyze correlation and to develop regression equations describing the relationships between person’s height and weight. Make separate regression lines for men and women. gender height weight 0 72 155 0 67 145 0 65 125 1 67 120 1 63 105 1 54 120 1 66 125 1 64 125 0 72 160 0 66 133 0 66 175 0 71 205 0 71 175 1 57 82 1 66 125 1 67 133 0 70...

Illustrate why outliers are so important to identify in the correlation/regression context.

Why is regression analysis necessary in business? What two categories of regression models are used? Explain

Check off the equations below that are accurate A , B, C are numeric variables A...

Check off the equations below that are accurate A , B, C are numeric variables A = 3, B= 2, C = 1 note , the symbol == means a test for equality, not assignment.. 3 * 5 > 2 * 6 is True A > B or A < C is True 3 + 5 > 2 + 6 is True A > B and not ( A < C) is True A < 5 or A == 5 or A >5 is True...

Discussion Prompt 2: Correlation and Regression Correlation and regression are two important terms in statistics. Select...

Discussion Prompt 2: Correlation and Regression Correlation and regression are two important terms in statistics. Select an area that interests you and use it to answer the following: Explain the difference between correlation and regression using examples Explain the different types of regression using examples

In a multiple regression, why is the estimated correlation between the coefficients beta 1 hat and...

In a multiple regression, why is the estimated correlation between the coefficients beta 1 hat and beta 2 hat positive when the correlation between regressors is negative?

Why would researchers believe that an ordinary least squares regression is superior to a partial correlation...

Why would researchers believe that an ordinary least squares regression is superior to a partial correlation coefficient?

Intro Discussion and Questions- Regression and Correlation: How does correlation analysis differ from regression analysis? What...

Intro Discussion and Questions- Regression and Correlation: How does correlation analysis differ from regression analysis? What are the goals of each? What does the correlation coefficient r measure? Be specific. What values can it take on? What do the values indicate? What values can the coefficient of determination take on? What does it measure? What are some of the limitations of simple linear regression? Describe the equation for multiple linear regression; be sure to clearly define all of its parts....

This week, we learn about regression analysis and regression “models’.

This week, we learn about regression analysis and regression “models’. Discuss the role of regression analysis in business by using examples of how these models might work to make predictions. In your discussion, consider the various components of the output and how it might be of value to understanding the data.

Question