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What does Studentized mean in statistics?
In statistics, Studentization, named after William Sealy Gosset, who wrote under the pseudonym Student, is the adjustment consisting of division of a first-degree statistic derived from a sample, by a sample-based estimate of a population standard deviation.
What means Studentized?
n. a procedure to eliminate a nuisance parameter in particular calculations. It transforms a statistic whose distribution of probable values relies upon the unknown parameter into one whose distribution relies on quantities that can be derived from the sample data.
What term refers to a random variable where its set of possible outcomes is measurable?
As a function, a random variable is required to be measurable, which allows for probabilities to be assigned to sets of its potential values. The domain of a random variable is called a sample space, defined as the set of possible outcomes of a non-deterministic event.
What do you mean by studentized range in statistics?
Studentized range. Jump to navigation Jump to search. In statistics, the studentized range is the difference between the largest and smallest data in a sample measured in units of sample standard deviations.
How did the studentized range get its name?
The studentized range, q, is named for William Sealy Gosset (who wrote under the pseudonym ” Student “), and was introduced by him (1927). The concept was later presented by a number of actual students, Newman (1939) and Keuls (1952) and John Tukey in some unpublished notes.
How is the Student’s t distribution used in statistics?
Student’s t -distribution. The t -distribution plays a role in a number of widely used statistical analyses, including Student’s t-test for assessing the statistical significance of the difference between two sample means, the construction of confidence intervals for the difference between two population means,…
How is the Student’s t distribution with degrees of freedom defined?
Student’s t -distribution. If we take a sample of n observations from a normal distribution, then the t -distribution with degrees of freedom can be defined as the distribution of the location of the sample mean relative to the true mean, divided by the sample standard deviation, after multiplying by the standardizing term .