In statistics, the p-value is the probability of obtaining results at least as extreme as the observed results of a statistical hypothesis test, assuming that the null hypothesis is correct. The p-value serves as an alternative to rejection points to provide the smallest level of significance at which the null hypothesis would be rejected. A smaller p-value means that there is stronger evidence in favor of the alternative hypothesis.
P-value is often used to promote credibility for studies or reports by government agencies. For example, the United States Census Bureau stipulates any analysis with a p-value greater than 0.10 must be accompanied by a statement that the difference is not statistically different from zero The Census Bureau also has standards in place stipulating what p-values are acceptable for various publications.
P value is commonly used. The prevalent use of P values to summarize the results of research articles could result from the increased quantity and complexity of data in recent scientific research.
Quantitative measurements are numerical values, they involve amounts and units like measuring things. Qualitative observations appeal to the five senses, like what does the interaction look and sound like
Oxygen is an element on the periodic table, but when it's combined with the element Hydrogen, it produces water, which is a compound (H2O). When two elements combine, it produces a compound.
