Fundamental notions such as random variables, distribution functions and probability density functions facilitate the analysis of both discrete and continuous outcomes.

A probability density function, also known as a bell curve, is a fundamental statistics concept, that describes the likelihood of a continuous random variable taking on a specific value.

Sankhyā: The Indian Journal of Statistics, Series B (1960-2002), Vol. 29, No. 3/4 (Dec., 1967), pp. 235-248 (14 pages) The paper presents a concise discussion of some probability density functions ...

A non-Bayesian derivation of the predictive estimate of a multivariate normal density function is given. The estimate is obtained as best invariant estimate in terms of a goodness-of-fit criterion ...

The course covers the probability, distribution theory and statistical inference needed for advanced courses in statistics and econometrics. Michaelmas term: Probability.

By an isometric transformation of density functions, the constrained nature of density functions is explicitly taken into account. Then, we introduce a regression model where the income distribution ...

Analysis and algebra at the level of a BSc in pure or applied mathematics and basic statistics and probability theory with stochastic processes. Knowledge of measure theory is not required as the ...