Page 10 - Quantitative Data Analysis

Preface

A basic knowledge of statistics and data analysis for
researcher has become almost as imperative as the ability to read
and write. This book promises to be a salvation for those who,
despite an anxiety of math, need to use statistics in their research. I
tried to introduce the concepts, techniques, principles and
applications of statistics, and teach my readers to extract truth and
draw valid conclusions from quantitative data.

A wide range of statistical methods are discussed in this
book with practical examples pertaining to both manual calculations
to SPSS results, including independent t-test, Paired t-test, ANOVA,
Correlation, Regression. In addition, supplementary material on
Factorial ANOVA, MANOVA, Principal Component Analysis (PCA),
and Factor Analysis are also provided in this book. Practice
problems for self-assessment are also given at the end of each
chapter.

This handy guide for significance tests help researchers to
choose the most appropriate and valid statistical test for specific
research question that play a conspicuous role in their data analysis.

This book is novel for those who want to conduct
quantitative research in their respective fields including Social
sciences, Education, Biology, Health sciences, sociology, and
psychology. Moreover, the book offers fruitful insight to
professionals in handling of numerical data and statistical analysis.

The book is designed with the purpose to give an insight
view to research scholars regarding the use of proper statistical
significance tests for their research and, on the basis of that, making
valid conclusion in informed ways. The chapters of the book are
written in a clear and lucid style. The book is equipped with detailed
illustration of many examples on each data analysis method.