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The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4]
In statistics, the sample maximum and sample minimum, also called the largest observation and smallest observation, are the values of the greatest and least elements of a sample. [1] They are basic summary statistics , used in descriptive statistics such as the five-number summary and Bowley's seven-figure summary and the associated box plot .
In descriptive statistics, the range of a set of data is size of the narrowest interval which contains all the data. It is calculated as the difference between the largest and smallest values (also known as the sample maximum and minimum). [1] It is expressed in the same units as the data.
The five-number summary is a set of descriptive statistics that provides information about a dataset. It consists of the five most important sample percentiles: the sample minimum (smallest observation) the lower quartile or first quartile; the median (the middle value) the upper quartile or third quartile; the sample maximum (largest observation)
1 bit – 0 or 1, false or true, Low or High (a.k.a. unibit) 1.442695 bits (log 2 e) – approximate size of a nat (a unit of information based on natural logarithms) 1.5849625 bits (log 2 3) – approximate size of a trit (a base-3 digit) 2 1: 2 bits – a crumb (a.k.a. dibit) enough to uniquely identify one base pair of DNA
Probability density functions of the order statistics for a sample of size n = 5 from an exponential distribution with unit scale parameter. In statistics, the kth order statistic of a statistical sample is equal to its kth-smallest value. [1]
The data must be ordered from smallest to largest to compute quartiles; as such, quartiles are a form of order statistic. The three quartiles, resulting in four data divisions, are as follows: The first quartile (Q 1) is defined as the 25th percentile where lowest 25% data is below this point.
The byte, 8 bits, 2 nibbles, is possibly the most commonly known and used base unit to describe data size. The word is a size that varies by and has a special importance for a particular hardware context. On modern hardware, a word is typically 2, 4 or 8 bytes, but the size varies dramatically on older hardware.