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 ...

Provides a one-semester course in probability and statistics with applications in the engineering sciences. Probability of events, discrete and continuous random variables cumulative distribution, ...

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 ...