• ###### central limit t
• The normal distribution is useful because of the central limit theorem. (wikipedia.org)
• This same distribution had been discovered by Laplace in 1778 when he derived the extremely important central limit theorem , the topic of a later section of this chapter. (onlinestatbook.com)
• ###### symmetric
• Circular symmetric complex normal random variables are used extensively in signal processing, and are sometimes referred to as just complex normal in signal processing literature. (wikipedia.org)
• ###### quantile
• The normality of the data may be evaluated by using the MINITAB "NSCORES" command to calculate the normal scores for the data, then plotting the observed data against the normal quantile values. (yale.edu)
• The standardized values in the second column and the corresponding normal quantile scores are very similar, indicating that the temperature data seem to fit a normal distribution. (yale.edu)
• The plot of these columns, with the temperature values on the horizontal axis and the normal quantile scores on the vertical axis, is shown to the right (the two scales in the horizontal axis provide original and standardized values). (yale.edu)
• ###### statistical
• You can easily generate data from a normal distribution using any of the commonly available statistical packages. (uvm.edu)
• A log-normal process is the statistical realization of the multiplicative product of many independent random variables , each of which is positive. (wikipedia.org)
• ###### subclass
• The NIG distribution was noted by Blaesild in 1977 as a subclass of the generalised hyperbolic distribution discovered by Ole Barndorff-Nielsen, in the next year Barndorff-Nielsen published the NIG in another paper. (wikipedia.org)
• ###### Given
• Approximations to this distribution that are easier to manipulate mathematically have been given by Ashour and Abdel-Hamid (2010) and by Mudholkar and Hutson (2000). (wikipedia.org)
• ###### measurement
• Physical quantities that are expected to be the sum of many independent processes (such as measurement errors) often have distributions that are nearly normal. (wikipedia.org)
• One of the first applications of the normal distribution was to the analysis of errors of measurement made in astronomical observations, errors that occurred because of imperfect instruments and imperfect observers. (onlinestatbook.com)
• ###### often
• As a consequence, when we have samples of hundreds of observations we can often ignore the distribution of the data. (bmj.com)
• ###### approximate
• Well, the final position of each ball is determined by many (here only 8) independent, random events of whether to drop to the left or the right of the pin, thus the (approximate) normal distribution. (uky.edu)
• It is possible to fit the generalized normal distribution adopting an approximate maximum likelihood method. (wikipedia.org)
• ###### follow a normal distribution
• This plot indicates that the data appear to follow a normal distribution, with only the three largest values deviating from a straight diagonal line. (yale.edu)