A social scientist could be considered to be a tool-less mechanic if he/she does not have the appropriate statistical tools for collecting, analyzing and interpreting a dataset. Good tools are required for a mechanic to make a good vehicle. In the same way, good statistical tools are required for a social scientist to collect, analyze and interpret a dataset. The dependency of a social scientist on statistical tools is in no way less than the dependency of a mechanic on mechanical tools. A mechanic cannot build a vehicle without mechanical tools. A social scientist cannot build a model of a phenomenon for a society without collecting, analyzing and interpreting the views of persons from the same society in an appropriate way. In this talk, like a magician can show several birds flying out of an empty basket, we shall show that at least seven parameters of interest to a social scientist can be estimated from a single sample and one response from each respondent in the sample.

Keywords: Randomized response sampling; Estimation of several parameters; Privacy; Sensitive characters

Biography: Dr. Sarjinder Singh has been playing with randomized response devices for several years like little kids play with marbles and kites. He introduced the ideas of hidden gangs, stochastic randomized response device, efficient use of two decks of cards, forced quantitative randomized response models and several other new randomized response models. He is the author of a two volume monograph “Advanced Sampling Theory with Applications: How Michael Selected Amy”; and a textbook “Advanced Sampling Theory with Applications: How Michael Selected Amy”. He is also a founder of an international journal: Model Assisted Statistics and Applications. He has published more than 100 peer reviewed articles in survey sampling and applied statistics. At present, he is on a tenure track position at the Texas A&M University-Kingsville, USA.