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What is coefficient of determination?
The coefficient of determination R2 is the square of the correlation coefficient. It is used generally to determine the goodness of fit of a model. See: http://en.wikipedia.org/wiki/Coefficient_of_determination for more details.
If the coefficient of determination is 0.81 the coefficient of correlation?
Given co-efficient of determination, r2 = 0.81. co-efficient of correlation, r = square root of 0.81 = +0.9, if the data have move in the same direction.(Let x and y as variables then x and y have linear relationship and x increase or decrease and y also have increase or decrease) = -0.9, if the data have move in the opposite direction.(Let x and y as variables then x and y have linear relationship and x decrease or increase and y is also increase or decrease)
What is the difference between odds ratio and Chi square?
none
What does the coefficient of determination explain in regression?
The coefficient, also commonly known as R-square, is used as a guideline to measure the accuracy of the model.
How does the difference between fe and fo influence the outcome of a chi-square test?
The larger the difference, the larger the value of chi-square and the greater the likelihood of rejecting the null hypothesis
What is coefficient of determination?
The coefficient of determination R2 is the square of the correlation coefficient. It is used generally to determine the goodness of fit of a model. See: http://en.wikipedia.org/wiki/Coefficient_of_determination for more details.
What did E MC square do?
It defined a direct correlation between matter and energy.
How can you tell if it appears to have a good r-square?
r^2 , the square of the correlation coefficient represents the percentage of variation explained by the independent variable of the dependent variable. It varies between 0 and 100 percent. The user has to make his/her own judgment as to whether the obtained value of r^2 is good enough for him/her.
What does the value of r square interpret?
R2 refers to the fraction of variance. it is the square of the correlation coefficient between two dependent variables. It is a statistical term that tells us how good one variable is at predicting another. If R2 is 1.0, then given the value of one variable you can perfectly predict the value of the other variable. If R2 is 0.0, then knowing either variable does not help you predict the other variable. In turn, the higher the R2 value the more correlation there is between the two variables.
What is difference between centimeter square and square centimeter?
No mathematical difference.
What's the difference between square kilometers and kilometers squared?
There is no difference between square meters and meters square. for simplicity we use these in different form.
What is the difference between a square pyramid and a pyramid?
the difference between them is that the bottom face is different one of them is a rectangle and one of them is a square
What is the difference between 7-8 Reggae and normal 7-8 time?
It is the same as the difference between a blue square and a square.
What is the difference between a square pyramid and a rectangular pyramid?
the difference between them is that the bottom face is different one of them is a rectangle and one of them is a square
How do you calculate Spearman's rank correlation?
# State the null hypothesis i.e. "There is no relationship between the two sets of data." # Rank both sets of data from the highest to the lowest. Make sure to check for tied ranks. # Subtract the two sets of ranks to get the difference d. # Square the values of d. # Add the squared values of d to get Sigma d2. # Use the formula Rs = 1-(6Sigma d2/n3-n) where n is the number of ranks you have. # If the Rs value... ... is -1, there is a perfect negative correlation. ...falls between -1 and -0.5, there is a strong negative correlation. ...falls between -0.5 and 0, there is a weak negative correlation. ... is 0, there is no correlation ...falls between 0 and 0.5, there is a weak positive correlation. ...falls between 0.5 and 1, there is a strong positive correlation ...is 1, there is a perfect positive correlation between the 2 sets of data. # If the Rs value is 0, state that null hypothesis is accepted. Otherwise, say it is rejected. (sourced from http://www.revision-notes.co.uk/revision/181.html)
What is the difference between units square and square units?
There isn't a significant difference, just which ever you prefer.
What is Multiple Correlation?
Let me assume that you are familiar with the (Pearson) correlation coefficient. If you estimate how one variable might be a linear function of another (using least-squares) then the measure of how strong the association is is known as that with which you are correlation coefficient. If you generalise by estimating what linear function one variable is of two or more other variables then the measure of how strong the relationship is is the multiple correlation.For mathematical reasons which may or may not interest you, and which I won't go into here, if we now go backwards we find that the multiple correlation for the situation where one variable is regressed against one other variable is just the square of the Pearson correlation coefficient.As you probably know, the Pearson ranges from -1 to +1. Because the multiple correlation is the squared value it ranges only from 0 to 1 and can indicate only degree of association, not the sense of direction.
