The artificial intelligence method was used to optimize an early cancer detection test to ensure high sensitivity and specificity.

In this paper, a new class of lower bounds on the probability of error for m-ary hypothesis tests is proposed. Computation of the minimum probability of error w ...

Sharp, nonasymptotic bounds are derived for the best achievable error probability in binary hypothesis testing between two probability distributions with indepe ...

Therefore, proper understanding of how statistical tests work is paramount for enhancing reproducibility. In this article, we’ll be diving into the one-sample t-test and z-test. We’ll be starting with ...

In Hypothesis Testing 1, 2 and 3, you have used normal and t-distributions to test hypotheses. Chi-Square tests use the Chi-Square probability distribution. You will be introduced to the use of that ...

The usual diagnostic tests may simply be too sensitive and too slow to contain the spread of the virus.

Python notebooks for my graduate class on Detection, Estimation, and Learning. Intended for in-class demonstration. Notebooks illustrate a variety of concepts, from hypothesis testing to estimation to ...