We introduce a new family of continuous models called the beta odd
log-logistic generalized family of distributions. We study some of its
mathematical properties. Its density function can be symmetrical,
left-skewed, right-skewed, reversed-J, unimodal and bimodal shaped,
and has constant, increasing, decreasing, upside-down bathtub and
J-shaped hazard rates. Five special models are discussed. We obtain explicit expressions for the moments, quantile function, moment
generating function, mean deviations, order statistics, Rényi entropy
and Shannon entropy. We discuss simulation issues, estimation by the
method of maximum likelihood, and the method of minimum spacing
distance estimator. We illustrate the importance of the family by means
of two applications to real data sets.