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To apply a Q test for bad data, arrange the data in order of increasing values and calculate Q as defined: Q = gap range {\displaystyle Q={\frac {\text{gap}}{\text{range}}}} Where gap is the absolute difference between the outlier in question and the closest number to it.
The Q-statistic or q-statistic is a test statistic: . The Box-Pierce test outputs a Q-statistic (uppercase) which follows the chi-squared distribution . The Ljung-Box test is a modified version of the Box-Pierce test which provides better small sample properties
Tobin's q [a] (or the q ratio, and Kaldor's v), is the ratio between a physical asset's market value and its replacement value. It was first introduced by Nicholas Kaldor in 1966 in his paper: Marginal Productivity and the Macro-Economic Theories of Distribution: Comment on Samuelson and Modigliani .
Mathematically, the markup rule can be derived for a firm with price-setting power by maximizing the following expression for profit: = () where Q = quantity sold, P(Q) = inverse demand function, and thereby the price at which Q can be sold given the existing demand C(Q) = total cost of producing Q.
The q-value can be interpreted as the false discovery rate (FDR): the proportion of false positives among all positive results. Given a set of test statistics and their associated q-values, rejecting the null hypothesis for all tests whose q-value is less than or equal to some threshold ensures that the expected value of the false discovery rate is .
In statistics, the Q-function is the tail distribution function of the standard normal distribution. [ 1 ] [ 2 ] In other words, Q ( x ) {\displaystyle Q(x)} is the probability that a normal (Gaussian) random variable will obtain a value larger than x {\displaystyle x} standard deviations.
First, with a data sample of length n, the data analyst may run the regression over only q of the data points (with q < n), holding back the other n – q data points with the specific purpose of using them to compute the estimated model’s MSPE out of sample (i.e., not using data that were used in the model estimation process).
The Q Score (popularly known as Q-Rating) is a measurement of the familiarity and appeal of a brand, celebrity, company, or entertainment product (e.g., television show) used in the United States. The more highly regarded the item or person is, the higher the Q Score among those who are aware of the subject.