Null Hypothesis: The null hypothesis is a foundational concept in statistical hypothesis testing. It represents the assumption of no effect, no difference, or no relationship between variables. It ...

In order to test a hypothesis in traditional (“frequentist”) statistics, you posit an alternative called the “null hypothesis”. The null hypothesis should be chosen so as to represent the default ...

Technologies of measuring millions of quantities at once have been rapidly developed and used in biological and biomedical research and other fields in the past decade. Yet a key issue remains ...

The probability that the null hypothesis will be rejected when it is actually true is called the false positive rate and is determined by the significance level of the test (called alpha which is ...

In science and health, we are often looking for results that are considered to be “statistically significant.” The golden rule is if the p-value is less than 0.05, then the result is statistically ...

Omnibus tests for various nonparametric hypotheses are developed using the empirical likelihood method. These include tests for symmetry about zero, changes in distribution, independence and ...

Central to the theme of hypothesis testing is the P-value, which is often misunderstood or misinterpreted. While it is often stated as the probability of the data having arisen by chance, the P-value ...

Whether you rely on fundamental analysis or technical analysis to identify promising investments, it’s helpful to have a working knowledge of statistical terms. Not every investor will be competent to ...