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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.
If the resulting p-value of Levene's test is less than some significance level (typically 0.05), the obtained differences in sample variances are unlikely to have occurred based on random sampling from a population with equal variances. Thus, the null hypothesis of equal variances is rejected and it is concluded that there is a difference ...
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 ...
Report the exact level of significance (e.g. p = 0.051 or p = 0.049). Do not refer to "accepting" or "rejecting" hypotheses. If the result is "not significant", draw no conclusions and make no decisions, but suspend judgement until further data is available. If the data falls into the rejection region of H1, accept H2; otherwise accept H1.
The partition coefficient, abbreviated P, is defined as a particular ratio of the concentrations of a solute between the two solvents (a biphase of liquid phases), specifically for un- ionized solutes, and the logarithm of the ratio is thus log P. [10]: 275ff When one of the solvents is water and the other is a non-polar solvent, then the log P ...
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.
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.
The last line describes the omnibus F test for model fit. The interpretation is that the null hypothesis is rejected (P = 0.02692<0.05, α=0.05). So Either β1 or β2 appears to be non-zero (or perhaps both). Note that the conclusion from Coefficients: table is that only β1 is significant (P-Value shown on Pr(>|t|) column is 4.37e-05 << 0.001).