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What is multiple correlation coefficient and partial correlation coefficient?
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.
What causes change in a dependent variable?
The dependent variable is dependent on the independent variable, so when the independent variable changes, so does the dependent variable.
What is the dependent and independent in a experiment?
The independent variable of an experiment is the variable that you change, and the dependent variable is the result of the independent variable.
How would you interpret the findings of a correlation study that reported a linear correlation coefficient of 1.67?
There is not enough information to say much. To start with, the correlation may not be significant. Furthermore, a linear relationship may not be an appropriate model. If you assume that a linear model is appropriate and if you assume that there is evidence to indicate that the correlation is significant (by this time you might as well assume anything you want!) then you could say that the dependent variable increases by 1.67 for every unit change in the independent variable - within the range of the independent variable.
How do the independent and dependent variables in an experiment compare?
the independent variable controls the dependent variables
When the correlation coefficient is negative?
The dependent variable has an inverse linear relationship with the dependent variable. When the dependent increases, the independent decreases, and conversely.
Difference between positive and negative corelation?
Positive correlation means that, if something increases, a factor dependent on it also increases. However, if there is negative correlation, the dependent factor decreases.
Is a decrease in the independent variable and a decrease in the dependent variable a positive correlation?
yes
What are the advantages of regression over correlation?
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.
What a correlation of 0.30 means that the independent variable explains -- percent of the variance in the dependent variable?
The independent variable explains .32*100 percent of the variance in the dependent variable.This is 9%.The explainable variance is always the square of the correlation (r).
What is multiple correlation coefficient and partial correlation coefficient?
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.
What is a perfect correlation?
If all variations in the dependent variable can be fully explained by the independent variables - so that there is no residual "error" - the correlation is said to be perfect.
What does it mean when a positive correlation coefficient between the dependent variable Y and the independent variable X indicates?
It means that the two variables are likely dependent. The higher the number of the positive correlation the stronger the connection.
Can a correlation have dependant and 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.
How would you interpret the findings of a correlation study that reported a linear correlation coefficient of -0.13?
There is not enough information to say much. To start with, the correlation may not be significant. Furthermore, a linear relationship may not be an appropriate model. If you assume that a linear model is appropriate and if you assume that there is evidence to indicate that the correlation is significant (by this time you might as well assume anything you want!) then you could say that the dependent variable decreases by 0.13 units for every unit change in the independent variable - within the range of the independent variable.
What serves as standard of comparison to evaluate effect of the independent variable on dependent variable?
The correlation coefficient, plus graphical methods to verify the validity of a linear relationship (which is what the correlation coefficient measures), and the appropriate tests of the statisitical significance of the correlation coefficient.
What is definition of inverse and direct proportion?
Direct proportion means as the independent variable increases, the dependent variable increases, and vice versa. Inverse propostion means just the opposite. As the independent variable increses, the dependent variable decreases, and vice versa.
