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  2. Simple linear regression - Wikipedia

    en.wikipedia.org/wiki/Simple_linear_regression

    The formulas given in the previous section allow one to calculate the point estimates of α and β — that is, the coefficients of the regression line for the given set of data. However, those formulas do not tell us how precise the estimates are, i.e., how much the estimators α ^ {\displaystyle {\widehat {\alpha }}} and β ^ {\displaystyle ...

  3. How to use beta to evaluate a stock’s risk - AOL

    www.aol.com/finance/beta-evaluate-stock-risk...

    Using beta to evaluate a stock’s risk. Beta allows for a good comparison between an individual stock and a market-tracking index fund, but it doesn’t offer a complete portrait of a stock’s ...

  4. Generalized estimating equation - Wikipedia

    en.wikipedia.org/wiki/Generalized_estimating...

    Regression beta coefficient estimates from the Liang-Zeger GEE are consistent, unbiased, and asymptotically normal even when the working correlation is misspecified, under mild regularity conditions. GEE is higher in efficiency than generalized linear models (GLMs) in the presence of high autocorrelation. [ 1 ]

  5. Standardized coefficient - Wikipedia

    en.wikipedia.org/wiki/Standardized_coefficient

    Standardization of the coefficient is usually done to answer the question of which of the independent variables have a greater effect on the dependent variable in a multiple regression analysis where the variables are measured in different units of measurement (for example, income measured in dollars and family size measured in number of individuals).

  6. Beta regression - Wikipedia

    en.wikipedia.org/wiki/Beta_regression

    Beta regression is a form of regression which is used when the response variable, , takes values within (,) and can be assumed to follow a beta distribution. [1] It is generalisable to variables which takes values in the arbitrary open interval ( a , b ) {\displaystyle (a,b)} through transformations. [ 1 ]

  7. Logistic regression - Wikipedia

    en.wikipedia.org/wiki/Logistic_regression

    Again, the optimum beta coefficients may be found by maximizing the log-likelihood function generally using numerical methods. A possible method of solution is to set the derivatives of the log-likelihood with respect to each beta coefficient equal to zero and solve for the beta coefficients:

  8. Numeric precision in Microsoft Excel - Wikipedia

    en.wikipedia.org/wiki/Numeric_precision_in...

    Excel maintains 15 figures in its numbers, but they are not always accurate; mathematically, the bottom line should be the same as the top line, in 'fp-math' the step '1 + 1/9000' leads to a rounding up as the first bit of the 14 bit tail '10111000110010' of the mantissa falling off the table when adding 1 is a '1', this up-rounding is not undone when subtracting the 1 again, since there is no ...

  9. Beta function - Wikipedia

    en.wikipedia.org/wiki/Beta_function

    In mathematics, the beta function, also called the Euler integral of the first kind, is a special function that is closely related to the gamma function and to binomial coefficients. It is defined by the integral