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Ordinary least squares regression of Okun's law.Since the regression line does not miss any of the points by very much, the R 2 of the regression is relatively high.. In statistics, the coefficient of determination, denoted R 2 or r 2 and pronounced "R squared", is the proportion of the variation in the dependent variable that is predictable from the independent variable(s).
Commonly used checks of goodness of fit include the R-squared, analyses of the pattern of residuals and hypothesis testing. Statistical significance can be checked by an F-test of the overall fit, followed by t-tests of individual parameters. Interpretations of these diagnostic tests rest heavily on the model's assumptions.
In statistics, the standard deviation is a measure of the amount of variation of the values of a variable about its mean. [1] A low standard deviation indicates that the values tend to be close to the mean (also called the expected value ) of the set, while a high standard deviation indicates that the values are spread out over a wider range.
In statistics, the logistic model (or logit model) is a statistical model that models the log-odds of an event as a linear combination of one or more independent variables. In regression analysis, logistic regression [1] (or logit regression) estimates the parameters of a logistic model (the coefficients in the linear or non linear combinations).
In probability theory and statistics, Covariance is a measure of the joint variability of two random variables. [ 1 ] The sign of the covariance, therefore, shows the tendency in the linear relationship between the variables.
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Likelihood-ratio test for nested models; Log-rank test in survival analysis; Cochran–Mantel–Haenszel test for stratified contingency tables; Wald test; Score test; It is also a component of the definition of the t-distribution and the F-distribution used in t-tests, analysis of variance, and regression analysis.
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