Search results
Results from the WOW.Com Content Network
p. -value. In null-hypothesis significance testing, the -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.
These values can be calculated evaluating the quantile function (also known as "inverse CDF" or "ICDF") of the chi-squared distribution; [21] e. g., the χ 2 ICDF for p = 0.05 and df = 7 yields 2.1673 ≈ 2.17 as in the table above, noticing that 1 – p is the p-value from the table.
The test statistic is approximately F-distributed with and degrees of freedom, and hence is the significance of the outcome of tested against (;,) where is a quantile of the F-distribution, with and degrees of freedom, and is the chosen level of significance (usually 0.05 or 0.01).
Toxic equivalency factor (TEF) expresses the toxicity of dioxins, furans and PCBs in terms of the most toxic form of dioxin, 2,3,7,8-TCDD. [1] The toxicity of the individual congeners may vary by orders of magnitude. With the TEFs, the toxicity of a mixture of dioxins and dioxin-like compounds can be expressed in a single number – the toxic ...
Statistical significance. In statistical hypothesis testing, [1][2] a result has statistical significance when a result at least as "extreme" would be very infrequent if the null hypothesis were true. [3] More precisely, a study's defined significance level, denoted by , is the probability of the study rejecting the null hypothesis, given that ...
The chi-squared test indicates a statistically significant association between the level of education completed and routine check-up attendance (chi2(3) = 14.6090, p = 0.002). The proportions suggest that as the level of education increases, so does the proportion of individuals attending routine check-ups.
For example, if z = 2.2 is observed and a two-sided p-value is desired to test the null hypothesis that =, the p-value is 2 Φ(−2.2) = 0.028, where Φ is the standard normal cumulative distribution function. To obtain a confidence interval for ρ, we first compute a confidence interval for F():
Direct interpretation of the harmonic mean p-value. The weighted harmonic mean of p -values is defined as where are weights that must sum to one, i.e. . Equal weights may be chosen, in which case . In general, interpreting the HMP directly as a p -value is anti-conservative, meaning that the false positive rate is higher than expected.