About the Book
Mathematics is everywhere: weather forecasting, automatic teller machines, secure websites, electronic games, statistical data analysis, opinion polls and many more. Many of the top jobs such as business consultants, computer consultants, airline pilots, company directors and a host of others require a solid understanding of basic mathematics, and in some cases require a quite detailed knowledge of mathematics. It also plays important role in business, like Business mathematics by commercial enterprises to record and manage business operations. That good knowledge of business mathematics, operations research and computer science assist business operators to master specialized areas which help the organization deal with allocation and planning in complex situations involving limited human and material resources like conducting national elections, going to the moon, conducting population census, etc.
The current book presents comprehensive coverage on mathematical concepts and methods used in the analysis of business management, finance and economics. The book covers descriptive and exploratory analysis to discuss meaning, nature, features and implications of the importance of business mathematics to business studies. It further discussed developments in quantitative techniques applications to business as a branch of mathematics as it pertains to banking, manufacturing, planning political campaign strategies and designing oil tankers port facility. The book is designed to meet the needs of a typical large audience in which there are students who have a wide range of mathematical skills and who also require a range of mathematical techniques for the different majors they are involved. Volume 2:
Statistics is the area of mathematics we use to explore and try to explain the uncertain world in which we live. We all are familiar with the use of statistics in opinion polls and market research, but it is also central to the manufacture and testing of many products. The field of statistics has numerous applications in business. Because of technological advancements, large amounts of data are generated by business these days. These data are now being used to make decisions. These better decisions help to improve the running of a department, a company, or the entire economy. Statistics play a vital role in nearly all businesses and form the backbone for all future development Strategies. Business closely analyze data and statistics to work out what they are doing right and what is working for the company while also determining what needs immediate attention or changing if things are not going well.
The current book presents the tools and techniques that are essential for carrying out best practices in the modern business world. First chapter presents a paper establishes the income and risk model in financial investment based on multi-objective programming theory, aiming to analyze the relationship between risk and return in financial investment and discuss the relationship between the risk the investor shall bear and decentralization degree of investment project. MATLAB software is used to analyze the investor?s optimized return under fixed risk level and the minimized risk with defined benefit. Statistical convergence plays a vital role as an extension of the classical convergence in the study of convergence analysis of sequence spaces. Therefore, third chapter focuses on statistical Deferred Nrlund Summability and Korovkin-Type Approximation Theorem. Many decision problems manage linguistic information assessed through several ordered qualitative scales. In these contexts, the main problem arising is how to aggregate this qualitative information. Furthermore, this book presents a multi-criteria decision-making procedure that ranks a set of alternatives assessed by means of a specific ordered qualitative scale for each criterion. These ordered qualitative scales can be non-uniform and be formed by a different number of linguistic terms. Mathematical models are proposed for statistical regularities of maximum daily precipitation within a wet period and total precipitation volume per wet period. The proposed models are based on the generalized negative binomial (GNB) distribution of the duration of a wet period. The GNB distribution is a mixed Poisson distribution, the mixing distribution being generalized gamma (GG). The GNB distribution demonstrates excellent fit with real data of durations of wet periods measured in days. Stochastic processes are used to model stochastic phenomena in various fields of science, engineering, economics and finance. In ninth chapter, readers will study a new family of Gompertz processes, defined by the power of the homogeneous Gompertz diffusion process, which we term the powers of the stochastic Gompertz diffusion process. Finally, one dimensional discrete scan statistic is explained over sequences of random variables generated by block factor dependence models.