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The T-Value Calculator can be used to calculate the t-value (Student t-value) by entering the Degrees of Freedom and the Significance Level in the standard deviation. The Student t-value calculator can be used online for t-value, p-value and z-value statistics calculations.

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The t-value calculator can be used to calculate the Student t-test:

- Enter the Degrees of Freedom into the t-value calculator
- Enter the significance level into the t-value calculator
- The t-value calculator will automatically calculate the t-value as you type.

The t-value, along with the p-value, is used in statistical analysis where the t-statistic is the 'ratio of the departure of the estimated value of a parameter' from its hypothesized value to its standard error. If you are unfamiliar with statistics, you are probably already encountering a lot of terms that your are unfamiliar with: p-value, t-value, t-test and so on. If you are new to these terms and the t-value calculation, you can review our list of statistics terminology which can be printed as a handy guide or math revision aid.

The t-statistic, introduced by William Sealy Gosset in 1908 as an economical way to monitor the quality of stout as part of Guinness's industrial processes, is used in hypothesis testing via Student's t-test. The t-test is known as the Student t-test as William Sealy Gosset published his statistical work under the pseudonym "Student". Student does not refer to the academic meaning of student but the pseudonym used, the Student t-test would otherwise have been known as the William Sealy Gosset t-test. This t-value calculator can be used to calculate the student t-test.

The Student t-test is any statistical hypothesis test in which the test statistic follows a Student's t-distribution under the null hypothesis.

A statistical hypothesis test, also known as a 'confirmatory data analysis', is a hypothesis that can be tested on the basis of modelled, via a set of random variables, process observation. In simple terms, a statistical hypothesis test is a common method of statistical inference where:

- two statistical data sets are compared
- a data set obtained by sampling is compared against a synthetic data set from an idealized model

A hypothesis is subsequently proposed for the statistical relationship between the data sets. The hypothesis in turn is compared as an alternative to an idealized null hypothesis that proposes no relationship between the data sets.

The comparison is deemed statistically significant if the relationship between the data sets would be an unlikely realization of the null hypothesis according to a threshold probability.

Hypothesis tests are used when determining which outcome(s) of a study would lead to a rejection of the null hypothesis for a pre-specified level of significance.

The t-value is a test statistic that is the result of a statistical test. The t-value can be used to calculate the p-value

The p-value is a probability value. The p-value is a quantitative measure used for the reporting the results of statistical hypothesis testing. The p-value measures the probability of an observed result.

The p-value is used in the context of null hypothesis testing in order to quantify the idea of statistical significance of evidence. Null hypothesis testing is a reductio ad absurdum (argument that attempts either to disprove a statement by showing it inevitably leads to a ridiculous, absurd, or impractical conclusion, or to prove one by showing that if it were not true, the result would be absurd or impossible) argument adapted to statistics. In essence, a claim is assumed valid if its counter-claim is improbable.