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In null-hypothesis significance testing, the p-value [note 1] is the probability of obtaining test results at least as extreme as the result actually observed, under the assumption that the null hypothesis is correct. [2] [3] A very small p-value means that such an extreme observed outcome would be very unlikely under the null hypothesis.
The p-value is the probability that a test statistic which is at least as extreme as the one obtained would occur under the null hypothesis. At a significance level of 0.05, a fair coin would be expected to (incorrectly) reject the null hypothesis (that it is fair) in 1 out of 20 tests on average.
An important property of a test statistic is that its sampling distribution under the null hypothesis must be calculable, either exactly or approximately, which allows p-values to be calculated. A test statistic shares some of the same qualities of a descriptive statistic, and many statistics can be used as both test statistics and descriptive ...
The t-test p-value for the difference in means, and the regression p-value for the slope, are both 0.00805. The methods give identical results. The methods give identical results. This example shows that, for the special case of a simple linear regression where there is a single x-variable that has values 0 and 1, the t -test gives the same ...
Fisher's exact test is a statistical significance test used in the analysis of contingency tables. [ 1 ] [ 2 ] [ 3 ] Although in practice it is employed when sample sizes are small, it is valid for all sample sizes.
A two-tailed test applied to the normal distribution. A one-tailed test, showing the p-value as the size of one tail.. In statistical significance testing, a one-tailed test and a two-tailed test are alternative ways of computing the statistical significance of a parameter inferred from a data set, in terms of a test statistic.
The p-value of the test statistic is computed either numerically or by looking it up in a table. If the p-value is small enough (usually p < 0.05 by convention), then the null hypothesis is rejected, and we conclude that the observed data does not follow the multinomial distribution.
6. Calculate the p-value Compare the computed Hosmer–Lemeshow statistic to a chi-squared distribution with Q − 2 degrees of freedom to calculate the p-value. There are Q = 10 groups in the caffeine example, giving 10 – 2 = 8 degrees of freedom. The p-value for a chi-squared statistic of 17.103 with df = 8 is p = 0.029. The p-value is ...