It tells you that something has a value of -13644.
The coefficient of determination, is when someone tries to predict the outcome of the testing of a hypothesis, or their guess at to what will happen. It helps determine how well outcomes are determined beforehand.
Adjusted R2
The coefficient of determination, denoted as (R^2), is always a non-negative value, regardless of whether the correlation coefficient (r-value) is negative or positive. The value of (R^2) indicates the proportion of the variance in the dependent variable that can be explained by the independent variable(s). While a negative r-value signifies an inverse relationship between the variables, (R^2) will still be a positive number, ranging from 0 to 1. Thus, a negative r-value does not imply a negative coefficient of determination.
A coefficient is a number (or a representation of a number such as x or y) that comes before a number, variable, or an expression. Typically used in algebraic notation, a coefficient is usually used to indication some sort of multiplication. For example: 6a The coefficient in this case is 6, and is is being used to indicate multiplying the term "a" by 6.
coefficient of determination
It's not quite possible for the coefficient of determination to be negative at all, because of its definition as r2 (coefficient of correlation squared). The coefficient of determination is useful since tells us how accurate the regression line's predictions will be but it cannot tell us which direction the line is going since it will always be a positive quantity even if the correlation is negative. On the other hand, r (the coefficient of correlation) gives the strength and direction of the correlation but says nothing about the regression line equation. Both r and r2 are found similarly but they are typically used to tell us different things.
it is da same as 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.
It tells you that something has a value of -13644.
= CORREL(x values,y values) ***clarification**** CORREL gives you the correlation coefficient (r), which is different than the coefficient of determination (R2) outside of simple linear regression situations.
The coefficient of determination, is when someone tries to predict the outcome of the testing of a hypothesis, or their guess at to what will happen. It helps determine how well outcomes are determined beforehand.
Adjusted R2
ɪf the regresion coefficient is the coefficient of determination, then it's range is between 0 or 1. ɪf the regression coefficient is the correaltion coefficient (which i think it is) the it must lie between -1 or 1.
The coefficient, also commonly known as R-square, is used as a guideline to measure the accuracy of the model.
True
1- Determination of activity coefficient . 2-determination of of composition of complex ion. 3-Potentiometric titrations.