Explain why probability is important to statistics and data science. See the relationship between conditional and independent events in a statistical experiment. Calculate the expectation and variance ...

Bayes' theorem is a formula for calculating the probability of an event. Learn how to calculate Bayes' theorem and see examples.

In statistics, a frequentist interpretation looks only at the simple probability. But Bayes' theorem works with conditional information rather than just looking at a positive result, says Adam Frank.

The world is full of uncertainty: accidents, storms, unruly financial markets, noisy communications. The world is also full of data. Build foundational knowledge of data science with this introduction ...

Nonparametric maximum likelihood estimation of the probability of failing from a particular cause by time t in the presence of other acting causes (i.e., the cause-specific failure probability) is ...

We apply our methods to the analysis of a yeast eQTL data set and demonstrate that the conditional Gaussian graphical model leads to a more interpretable gene network than a standard Gaussian ...