yes
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.
Correlation is a measure of association between two variables and the variables are not designated as dependent or independent. Simple regression is used to examine the relationship between one dependent and one independent variable. It goes beyond correlation by adding prediction capabilities.
It mean that there is no correlation between the two variables. The variables are the same.
"If coefficient of correlation, "r" between two variables is zero, does it mean that there is no relationship between the variables? Justify your answer".
An experiment is when the researcher manipulates the independent variable and records its effect on the dependent variable whilst maintaining strict control over any extraneous variables. A correlation is a statistical relationship between two or more variables. The researcher makes a change in one of the variables to see what is affected.
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.
partial correlation is the relation between two variable after controlling for other variables and multiple correlation is correlation between dependent and group of independent variables.
Yes, a correlation can exist between two variables, regardless of their nature as dependent or independent. The correlation coefficient quantifies the degree of relationship between variables, indicating how changes in one variable are associated with changes in the other. However, correlation does not imply causation.
Multicolinearity shows the relationship of two or more variables in a multi-regression model. Auto-correlation shows the corellation between values of a process at different point in times.
Correlation is a measure of association between two variables and the variables are not designated as dependent or independent. Simple regression is used to examine the relationship between one dependent and one independent variable. It goes beyond correlation by adding prediction capabilities.
It mean that there is no correlation between the two variables. The variables are the same.
A positive correlation between two variables means that there is a direct correlation between the variables. As one variable increases, the other variable will also increase.
"If coefficient of correlation, "r" between two variables is zero, does it mean that there is no relationship between the variables? Justify your answer".
An experiment is when the researcher manipulates the independent variable and records its effect on the dependent variable whilst maintaining strict control over any extraneous variables. A correlation is a statistical relationship between two or more variables. The researcher makes a change in one of the variables to see what is affected.
Either +1 (strongest possible positive correlation between the variables) or -1 (strongest possible negativecorrelation between the variables).
Positive correlation is a relationship between two variables in which both variables move in tandem that is in the same direction.
It means there is no discernable relationship between the two variables. Knowing one variable does not give you any help in working out the other. They are independent of each other.