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The Ultimate Resource for Frank S Budnick Applied Mathematics for Business, Economics and Social Sciences: Free PDF Book Included


How to Learn Applied Mathematics for Business, Economics and Social Sciences with a Free PDF Book




If you are looking for a comprehensive and practical guide to applied mathematics for business, economics and social sciences, you might be interested in the book by Frank S. Budnick. This book covers selected topics in finite mathematics and calculus, with an informal and non-intimidating presentation of the mathematical principles, techniques and applications most useful to students in these fields.




Frank S Budnick Applied Mathematics For Business Economics And Social Sciences Pdf Book Free 14



In this article, we will give you an overview of the book and show you how you can download it for free in 14 easy steps.


What is the book about?




The book by Frank S. Budnick is divided into 14 chapters, each covering a different topic in applied mathematics. The topics include:


  • Some preliminaries: sets, functions, graphs, linear equations and inequalities



  • Matrix algebra: operations, inverses, determinants, systems of linear equations



  • Linear programming: graphical and simplex methods, duality, sensitivity analysis



  • Mathematics of finance: simple and compound interest, annuities, amortization, sinking funds



  • Sets and counting: basic concepts, permutations and combinations, binomial theorem



  • Probability: axioms and rules, conditional probability, Bayes' theorem



  • Probability distributions: discrete and continuous random variables, expected value, variance



  • Statistics: descriptive measures, sampling distributions, confidence intervals, hypothesis testing



  • Limits and continuity: intuitive concepts, formal definitions, properties



  • Differentiation: rules, applications to optimization and elasticity



  • Integration: antiderivatives, definite integrals, applications to consumer and producer surplus



  • Functions of several variables: partial derivatives, optimization with constraints



  • Exponential and logarithmic functions: properties, applications to growth and decay models