If the p-value is smaller than the level of significance, what does that always mean in terms of the null hypothesis? Why? What do we conclude if the p-value is larger than the significance level (\alpha)? What do we conclude if the p-value is the same or smaller than the signif...
One typical situation is when the p value is larger than the significance level 伪 which results in an inconclusive case. In many studies, a common mistake is to claim that the null hypothesis is true or most likely whereas a big p value merely implies that the null hypothesis is ...
I find statements (1) and (2) contradictory because of the following. In making the decision about whether to reject the null hypothesis one compares the p-value to the significance level. (If pvalue is lower than the preset significance level one rejects the null hypothesis). It is possibl...
The critical z-score values when using a 95 percent confidence level are -1.96 and +1.96 standard deviations. The uncorrected p-value associated with a 95 percent confidence level is 0.05. If your z-score is between -1.96 and +1.96, your uncorrected p-value will be larger than 0.05,...
values of the test statistic seem more plausible under the alternative hypothesis than under the null hypothesis. Then we want a measure of how far out our test statistic is in the right-hand tail of the null distribution. The P-value provides a measure of this distance. The P-value ...
significance level, there is no real scientific reason for choosing that versus any other small value. Always rejecting H0 when p is less than 5% results in an incorrect rejection of the null hypothesis 5% of the time. However, as there is no real practical difference between a p value of...
Answer to: Calculate the test statistic and the p-value when x = 140, s = 50, and n = 100. Use a 5% significance level. H0: mu = 150 H1: mu less...
Only rs7098387 showed a significant association, with a P-value (P ¼ 0.0011) lesser than the significance level (a ¼ 0.0016) of the Bonferroni correction for multiple testing (Table 2). When imputation was performed with the data for the 11 SNPs, a total of 38 neighboring SNPs were ...
The p-value is the probability of seeing an effect as large as or larger than the observed effect assuming that the null hypothesis is true. A small p-value indicates that either we have observed something highly unusual or that the null hypothesis is not true. Fisher regarded p-values as...
How was the p value larger than 0.05 when there seems to be an obvious difference between the two means? To get a less-than 0.05 p value or to reject the null hypothesis is, in fact, not difficult as long as we have a large enough statistical power, which is the probability of ...