Mathematics + Statistics

Permanent URI for this collectionhttp://scholar.mzumbe.ac.tz/handle/123456789/1878

Browse

Filters

2001 - 20093

Settings

Search Results

Now showing 1 - 3 of 3
  • No Thumbnail Available
    Item
    Non-parametric statistics
    (Mzumbe University, 2009) Ndunguru Philibert, C.
    The book is structured as follows: Chapter one introduces the basic concepts of a statistical inference problem. Chapter two focuses on inference techniques that are appropriate for nominal data. Chapters three and four dwell on inference techniques using ordinal data; with chapter three focusing on sample median test techniques and chapter four on rank-sum techniques. Both techniques typically rely on data that are capable of being ranked. Chapter five is exclusively presenting material on testing randomness of a set of sample observations, which is a universal premise for all inference methods. The technique adopted in this book is based on Wald-Wolfowitz one-sample runs test procedure. The final chapter dwells on correlational inference techniques that are appropriate for nominal and/or ordinal data. The author has streamlined the material to be reader-friendly. The solved examples, exercises, and review questions that are drawn from real and contextualized business, economics, management, and social life situations enable readers to understand the topical concepts covered. The optional exercises on parametric techniques enable readers to reflect on the link between parametric and non-parametric statistical techniques as applied in social science research. Chapters two through six each contain a section on SPSS tutorial, in which the use of SPSS software in solving non- Parametric inference problems is demonstrated. In this way, readers get to know and/or exercise their skills in the application of the statistical package.
  • No Thumbnail Available
    Item
    Topics in mathematics for economists
    (Research and Publications Department, 2006) Wiketye Enock J.M
    The book is divided into four parts a sixteen chapters. Part I consists of chapters one to four. Chapter one deals with the Set Theory. This is followed by chapter two which deals with Functions and models. Chapter three is about Exponential and Logarithmic Functions. The last chapter in part one deals with Progressions. Part II of the book is about Linear Algebra. It consists of chapters five through eight. Chapter five deals with Matrix Algebra. This is followed by chapter six which is about Systems of Linear equations. Chapter seven looks at some Applications of Matrix Algebra while chapter eight is on Characteristic Values a Vectors. Part Ill of the book is about calculus. It consists of chapters nine through thirteen. Chapter nine gives an introduction on Differential Calculus. This is followed by chapter ten which looks at Partial Differentiation. Chapter eleven is about Optimization whereas chapter twelve is on Constrained Optimization. The last chapter of this part, chapter thirteen, is about Integral Calculus. Part IV is about Programming. This consists of chapters fourteen, fifteen and sixteen. Chapter Fourteen introduces the concept of Linear Programming. This is followed by chapter fifteen which is about the Simplex Method of solving linear programs. The last chapter of this part (and of this book) is chapter sixteen. This chapter deals with Duality and Sensitivity Analysis.
  • No Thumbnail Available
    Item
    Basic concepts of probability theory
    (Research, Information and Publication Department, 2001) Ndunguru Philibert, C.
    This book is organized into four parts which are logically and systematically presented. Part one, sets the fundamental aspects of probability theory in which apart from introducing the reader to the basic vocabulary of the subject, it also answers three fundamental questions for learning probability theory. These are: What basic outcomes are possible; How many such possibilities exist and what basic outcome is likely to happen, for a given random experiment or phenomenon. The algebra of probability is discussed in part two, while part three focuses on building probability models based on simple statistical random experiments. The last part deals with the application of probability theory in decision making. Moreover there are problems at the end of each chapter which the reader can test the understanding of the material covered. Besides, each chapter begins with a clear statement about the silent features of the issues discussed in it. This is meant to guide the reader to have a sense of direction while reading the chapter.