Special Issue on Mathematical Statistics and Data Analysis

Statistics is the science that makes sense of quantitative information. Statisticians describe and analyse data, using mathematical statistical and probability models. Based on these analyses, conclusions and calculated decisions can be made under uncertainty. The goal of this special issue is to provide a platform for scientists and academicians all over the world to promote, share, and discuss various new issues and developments in the area of mathematical statistics and data analysis.

In this special issue, we intend to invite front-line researchers and authors to submit original research and review articles on exploring mathematical statistics and data analysis. In this special issue, potential topics include, but are not limited to:

• Resampling methods
• Markov chain monte carlo methods
• Local regression and kernel density estimation 
• Error and data processing
• Calculation of distribution functions and quantiles 
• Generation and verification of random Numbers
• Stochastic simulation method
• Combinatorics and basic set theory notation
• Common discrete and continuous distributions
• Random variables, expectation, variance
• Confidence Intervals: definitions, duality with hypothesis tests

Authors should read over the journal’s For Authors carefully before submission. Prospective authors should submit an electronic copy of their complete manuscript through the journal’s Paper Submission System.

Please kindly notice that the “Special Issue” under your manuscript title is supposed to be specified and the research field “Special Issue - Mathematical Statistics and Data Analysis” should be chosen during your submission.

According to the following timetable:

Guest Editor:

For further questions or inquiries

Please contact Editorial Assistant at

ojs@scirp.org