answersLogoWhite

0


Best Answer

difference between correlation and regression?

(1) The correlation answers the STRENGTH of linear association between paired variables, say X and Y. On the other hand, the regression tells us the FORM of linear association that best predicts Y from the values of X.

(2a) Correlation is calculated whenever:

* both X and Y is measured in each subject and quantify how much they are linearly associated.

* in particular the Pearson's product moment correlation coefficient is used when the assumption of both X and Y are sampled from normally-distributed populations are satisfied

* or the Spearman's moment order correlation coefficient is used if the assumption of normality is not satisfied.

* correlation is not used when the variables are manipulated, for example, in experiments.

(2b) Linear regression is used whenever:

* at least one of the independent variables (Xi's) is to predict the dependent variable Y. Note: Some of the Xi's are dummy variables, i.e. Xi = 0 or 1, which are used to code some nominal variables.

* if one manipulates the X variable, e.g. in an experiment.

(3) Linear regression are not symmetric in terms of X and Y. That is interchanging X and Y will give a different regression model (i.e. X in terms of Y) against the original Y in terms of X.

On the other hand, if you interchange variables X and Y in the calculation of correlation coefficient you will get the same value of this correlation coefficient.

(4) The "best" linear regression model is obtained by selecting the variables (X's) with at least strong correlation to Y, i.e. >= 0.80 or <= -0.80

(5) The same underlying distribution is assumed for all variables in linear regression. Thus, linear regression will underestimate the correlation of the independent and dependent when they (X's and Y) come from different underlying distributions.

User Avatar

Wiki User

10y ago
This answer is:
User Avatar

Add your answer:

Earn +20 pts
Q: Difference between regression coefficient and correlation coefficient?
Write your answer...
Submit
Still have questions?
magnify glass
imp
Continue Learning about Natural Sciences

What is the difference between a subscript and a coefficient in a chemical formula?

The subscripts tell you how the atoms are bound together. The coefficient tells you how many atoms there are.


What is the correlation between nutrition in insectivorous plants plants and their habitat?

what is the correlation between nutrition in insectivorous plants and their habitat


What is the difference between cause and correlation?

Correlation means that two events are related. Causation means that one event caused another event to happen. Correlation isn't the same as causation.


What kind of test used to analyze data for experimental treatments?

After calculating the mean and standard deviationvalues each value of the independent variable in the data, these are a few common tests that are used to further analyse the data and highlight its significance:1) Pearson Correlation Coefficient- This is to test for a strong/weak positive/negative correlation between the independent variable and the dependent variable. However, correlation does not necessarily imply causation.2) t-test- This post-hoc test is used to determine the level of significance of the difference between two sets of data.3) Chi2 test- This test tests for whether the difference in Expected and Observed values are significant or not.4) Analysis of variance (ANOVA)- This is like a massive t-test to test an entire set of data, without inflating the error of the analysis results. This is usually coupled with Tukey's Honest Significant Difference test.


Is the coefficient of dynamic friction greater than the coefficient of static friction and why?

Millions of classroom experiments would indicate that there is, in fact, a difference, but it is most likely caused by dirt, oil, and imperfections on the surfaces. When care is taken to ensure the surfaces are uniform and clean, the difference between static and dynamic friction disappears.

Related questions

What is regression coefficient and correlation coefficient?

The strength of the linear relationship between the two variables in the regression equation is the correlation coefficient, r, and is always a value between -1 and 1, inclusive. The regression coefficient is the slope of the line of the regression equation.


What is the relationship between correlation coefficient and linear regreassion?

A correlation coefficient is a value between -1 and 1 that shows how close of a good fit the regression line is. For example a regular line has a correlation coefficient of 1. A regression is a best fit and therefore has a correlation coefficient close to one. the closer to one the more accurate the line is to a non regression line.


What are the properties of correlation coefficient?

The correlation coefficient is symmetrical with respect to X and Y i.e.The correlation coefficient is the geometric mean of the two regression coefficients. or .The correlation coefficient lies between -1 and 1. i.e. .


What are the properties of correlation?

The correlation coefficient is symmetrical with respect to X and Y i.e.The correlation coefficient is the geometric mean of the two regression coefficients. or .The correlation coefficient lies between -1 and 1. i.e. .


What Are The Properties Of Regression Coefficient?

(a) Correlation coefficient is the geometric mean between the regression coefficients. (b) If one of the regression coefficients is greater than unity, the other must be less than unity. (c) Arithmetic mean of the regression coefficients is greater than the correlation coefficient r, provided r &gt; 0. (d) Regression coefficients are independent of the changes of origin but not of scale.


Properties of regression coefficient-statistics?

8.7.4 Properties of Regression Coefficients:(a) Correlation coefficient is the geometric mean between the regression coefficients. (b) If one of the regression coefficients is greater than unity, the other must be less than unity.(c) Arithmetic mean of the regression coefficients is greater than the correlation coefficient r, providedr > 0.(d) Regression coefficients are independent of the changes of origin but not of scale.


Distinguish between correlation and regression?

Correlation is a measure of the degree of agreement in the changes (variances) in two or more variables. In the case of two variables, if one of them increases by the same amount for a unit increase in the other, then the correlation coefficient is +1. If one of them decreases by the same amount for a unit increase in the other, then the correlation coefficient is -1. Lesser agreement results in an intermediate value. Regression involves estimating or quantifying this relationship. It is very important to remember that correlation and regression measure only the linear relationship between variables. A symmetrical relationshup, for example, y = x2 between values of x with equal magnitudes (-a &lt; x &lt; a), has a correlation coefficient of 0, and the regression line will be a horizontal line. Also, a relationship found using correlation or regression need not be causal.


What is the difference between correlation and regression?

correlation we can do to find the strength of the variables. but regression helps to fit the best line


which characteristics of a data set makes a linear regression model unreasonable?

A correlation coefficient close to 0 makes a linear regression model unreasonable. Because If the correlation between the two variable is close to zero, we can not expect one variable explaining the variation in other variable.


What is the correlation coefficient of -2?

A serious error. The maximum magnitude for a correlation coefficient is 1.The Correlation coefficient is lies between -1 to 1 if it is 0 mean there is no correlation between them. Here they are given less than -1 value so it is not a value of correlation coefficient.


What is numerical range of regression coefficient?

&#618;f the regresion coefficient is the coefficient of determination, then it's range is between 0 or 1. &#618;f the regression coefficient is the correaltion coefficient (which i think it is) the it must lie between -1 or 1.


What is the difference between Multicollinearity and Autocorrelation?

The difference between multicollinearity and auto correlation is that multicollinearity is a linear relationship between 2 or more explanatory variables in a multiple regression while while auto-correlation is a type of correlation between values of a process at different points in time, as a function of the two times or of the time difference.