ACADEMIC RESOURCE
Introduction to Nonparametric Statistical
Methods
Nonparametric Statistics
Statistics
45 pages · professionally formatted edition
STUDY · REVIEW · REFERENCE
, INTRODUCTION TO
NONPARAMETRIC
STATISTICAL METHODS
INTRODUCTION TO
NONPARAMETRIC
STATISTICAL METHODS
C. A. HESSE, BSc, MPhil, PhD.
Senior Lecturer of Statistics,
Methodist University College Ghana.
J. B. OFOSU, BSc, PhD, FSS.
Professor of Statistics,
Methodist University College Ghana.
E. N. NORTEY, BSc, MPhil, PhD.
Senior Lecturer of Statistics,
University of Ghana.
NONPARAMETRIC STATISTICS 1
, INTRODUCTION TO
NONPARAMETRIC
STATISTICAL METHODS
Copyright © 2017
Akrong Publications Ltd.
All rights reserved
No part of this publication may be reproduced, in part or in whole, stored in a retrievable
system, or transmitted in any form or by any means, electronic, mechanical, photocopying,
recording or otherwise, without prior permission of the publisher.
Published and Printed by
AKRONG PUBLICATIONS LIMITED
P. O. BOX M. 31
ACCRA, GHANA
(0244 648 757, 0264 648 757)
ISBN: 978–9988–2–6059–0
Published, 2017
.
ii
NONPARAMETRIC STATISTICS 2
, INTRODUCTION TO
NONPARAMETRIC
STATISTICAL METHODS
PREFACE
A statistical method is called non-parametric if it makes no assumption on the population
distribution or sample size. This is in contrast with most parametric methods in elementary
statistics that assume that the data set used is quantitative, the population has a normal
distribution and the sample size is sufficiently large. In general, conclusions drawn from non-
parametric methods are not as powerful as the parametric ones. However, as non-parametric
methods make fewer assumptions, they are more flexible, more robust, and applicable to non-
quantitative data.
This book is designed for students to acquire basic skills needed for solving real life
problems where data meet minimal assumption and secondly to beef up their reading list as
well as provide them with a “one shop stop” textbook on Nonparametric.
Our Approach
This book is an introduction to basic ideas and techniques of nonparametric statistical methods
and is intended to prepare students of the sciences as well as the humanities, for a better
understanding of some underlying explanations of real life situations. Researchers will find
the text useful since it provides a step-by-step presentation of procedures, use of more practical
data sets, and new problems from real-life situations. The book continues to emphasize the
importance of nonparametric methods as a significant branch of modern statistics and equips
readers with the conceptual and technical skills necessary to select and apply the appropriate
procedures for any given situation.
Written by leading statisticians, Introduction to Nonparametric Statistical Methods,
provides readers with crucial nonparametric techniques in a variety of settings, emphasizing
the assumptions underlying the methods. The book provides an extensive array of examples
that clearly illustrate how to use nonparametric approaches for handling one- or two-sample
location and dispersion problems, dichotomous data, one-way analysis of variance, rank tests,
goodness-of-fit tests and tests of randomness.
A wide range of topics is covered in this text although the treatment is limited to the
elementary level. There are solved, partly solved and unsolved assignments with every section,
to make the student or reader familiar with the methods introduced.
C. A. Hesse
J. B. Ofosu
E. N. Nortey
July, 2017
iii
NONPARAMETRIC STATISTICS 3
Introduction to Nonparametric Statistical
Methods
Nonparametric Statistics
Statistics
45 pages · professionally formatted edition
STUDY · REVIEW · REFERENCE
, INTRODUCTION TO
NONPARAMETRIC
STATISTICAL METHODS
INTRODUCTION TO
NONPARAMETRIC
STATISTICAL METHODS
C. A. HESSE, BSc, MPhil, PhD.
Senior Lecturer of Statistics,
Methodist University College Ghana.
J. B. OFOSU, BSc, PhD, FSS.
Professor of Statistics,
Methodist University College Ghana.
E. N. NORTEY, BSc, MPhil, PhD.
Senior Lecturer of Statistics,
University of Ghana.
NONPARAMETRIC STATISTICS 1
, INTRODUCTION TO
NONPARAMETRIC
STATISTICAL METHODS
Copyright © 2017
Akrong Publications Ltd.
All rights reserved
No part of this publication may be reproduced, in part or in whole, stored in a retrievable
system, or transmitted in any form or by any means, electronic, mechanical, photocopying,
recording or otherwise, without prior permission of the publisher.
Published and Printed by
AKRONG PUBLICATIONS LIMITED
P. O. BOX M. 31
ACCRA, GHANA
(0244 648 757, 0264 648 757)
ISBN: 978–9988–2–6059–0
Published, 2017
.
ii
NONPARAMETRIC STATISTICS 2
, INTRODUCTION TO
NONPARAMETRIC
STATISTICAL METHODS
PREFACE
A statistical method is called non-parametric if it makes no assumption on the population
distribution or sample size. This is in contrast with most parametric methods in elementary
statistics that assume that the data set used is quantitative, the population has a normal
distribution and the sample size is sufficiently large. In general, conclusions drawn from non-
parametric methods are not as powerful as the parametric ones. However, as non-parametric
methods make fewer assumptions, they are more flexible, more robust, and applicable to non-
quantitative data.
This book is designed for students to acquire basic skills needed for solving real life
problems where data meet minimal assumption and secondly to beef up their reading list as
well as provide them with a “one shop stop” textbook on Nonparametric.
Our Approach
This book is an introduction to basic ideas and techniques of nonparametric statistical methods
and is intended to prepare students of the sciences as well as the humanities, for a better
understanding of some underlying explanations of real life situations. Researchers will find
the text useful since it provides a step-by-step presentation of procedures, use of more practical
data sets, and new problems from real-life situations. The book continues to emphasize the
importance of nonparametric methods as a significant branch of modern statistics and equips
readers with the conceptual and technical skills necessary to select and apply the appropriate
procedures for any given situation.
Written by leading statisticians, Introduction to Nonparametric Statistical Methods,
provides readers with crucial nonparametric techniques in a variety of settings, emphasizing
the assumptions underlying the methods. The book provides an extensive array of examples
that clearly illustrate how to use nonparametric approaches for handling one- or two-sample
location and dispersion problems, dichotomous data, one-way analysis of variance, rank tests,
goodness-of-fit tests and tests of randomness.
A wide range of topics is covered in this text although the treatment is limited to the
elementary level. There are solved, partly solved and unsolved assignments with every section,
to make the student or reader familiar with the methods introduced.
C. A. Hesse
J. B. Ofosu
E. N. Nortey
July, 2017
iii
NONPARAMETRIC STATISTICS 3
