Statistical hypothesis testing (also 'confirmatory data analysis') is used in inferential statistics to either confirm or falsify a hypothesis based on empirical observations. Performing hypothesis ...

When reading testimonials from those who have taken the Securities Analyst Level I exam, statistics is the subject most ...

The first thing any scientist does before performing an experiment is to form a hypothesis about the experiment's outcome. This often takes the form of a null hypothesis, which is a statistical ...

Statistical significance is a critical concept in data analysis and research. In essence, it’s a measure that allows researchers to assess whether the results of an experiment or study are due to ...

Permutation methods provide flexible, distribution-free approaches to statistical inference by rearranging data labels to generate an empirical null distribution for a test statistic. Historically ...

During his Ph.D. research, mathematician Tyron Lardy worked on a new approach to hypothesis testing. Instead of the traditional p-value, he uses so-called e-values. These turn out to be more ...

An analysis of temperature data since 1500 all but rules out the possibility that global warming in the industrial era is just a natural fluctuation in the earth's climate, according to a new study by ...

It may be common knowledge that p < .05 indicates statistical significance. Psychology students (and others) are often taught that p < .05 means the probability (p) of rejecting the null hypothesis ...