Sports Research with Analytical Solution using SPSS

J. P. Verma

• Publisher: Wiley
• Year: 2016
• ISBN:
  9781119206736
• Edition: 1
• Topic: Medicine
• Subtopic: Sports Medicine

A step-by-step approach to problem-solving techniques using SPSS® in the fields of sports science and physical education

Featuring a clear and accessible approach to the methods, processes, and statistical techniques used in sports science and physical education, Sports Research with Analytical Solution using SPSS® emphasizes how to conduct and interpret a range of statistical analysis using SPSS. The book also addresses issues faced by research scholars in these fields by providing analytical solutions to various research problems without reliance on mathematical rigor.

Logically arranged to cover both fundamental and advanced concepts, the book presents standard univariate and complex multivariate statistical techniques used in sports research such as multiple regression analysis, discriminant analysis, cluster analysis, and factor analysis. The author focuses on the treatment of various parametric and nonparametric statistical tests, which are shown through the techniques and interpretations of the SPSS outputs that are generated for each analysis. Sports Research with Analytical Solution using SPSS® also features:

• Numerous examples and case studies to provide readers with practical applications of the analytical concepts and techniques
• Plentiful screen shots throughout to help demonstrate the implementation of SPSS outputs
• Illustrative studies with simulated realistic data to clarify the analytical techniques covered
• End-of-chapter short answer questions, multiple choice questions, assignments, and practice exercises to help build a better understanding of the presented concepts
• A companion website with associated SPSS data files and PowerPoint® presentations for each chapter

Sports Research with Analytical Solution using SPSS® is an excellent textbook for upper-undergraduate, graduate, and PhD-level courses in research methods, kinesiology, sports science, medicine, nutrition, health education, and physical education. The book is also an ideal reference for researchers and professionals in the fields of sports research, sports science, physical education, and social sciences, as well as anyone interested in learning SPSS.

1
INTRODUCTION TO DATA TYPES AND SPSS OPERATIONS

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LEARNING OBJECTIVES

After completing this chapter, you should be able to do the following:

• Understand different data types generated in research
• Learn the nature of variables
• Know various data cleaning methods
• Learn to install SPSS package in computer
• Prepare data file in SPSS

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1.1 INTRODUCTION

Due to large stake involved in sports, research in this area is gaining momentum in different universities of the world. Even developing countries have started introducing sports sciences in different universities. The sole purpose is to create specific knowledge required for enhancing sports performance. Everyday, enormous data is being generated in the area of sports all over the world, which can be used to draw meaningful conclusions. Scientists have started organizing experiments by taking athletes as subjects. It is therefore required to support these scientists with analytical skill set to carry out their business. Since they deal with the data, it is essential that they are aware of its nature. Depending upon the data types, one identifies the relevant analytical technique for addressing research issues. Sports research can broadly be classified into two categories: descriptive and analytical. In descriptive research, the nature of dataset is investigated from different perspectives. Several statistics like mean, standard deviation, coefficient of variation, skewness, kurtosis, and percentiles are used to describe the characteristics of the dataset. Many interesting facts about the population can be investigated by using these descriptive statistics. Analytical research broadly follows two approach: exploratory and confirmatory. In explorative research, focus is on discovering the hidden relationships. It is done by hypothesis testing, data modeling, and using multivariate analysis. On the other hand, in confirmatory studies, some of the facts are either confirmed or denied on the basis of hypothesis testing.

Numerous statistical techniques are available to the researchers for analyzing their research data. Selection of an appropriate technique depends upon the research questions being investigated in the study. Due to complexities of different analytical solutions in sports research, one needs to use some user-friendly software package. This chapter will acquaint you with different types of data that are generated in sports research and some of the widely used statistical techniques by the research scholars to solve them for answering different research questions by using the most popular IBM SPSS Statistics package.

1.2 TYPES OF DATA

It is essential to know the types of data generated in research studies because choosing statistical test for analyzing data depends upon its type. Data can be classified into two categories: metric and nonmetric. Metric data is analyzed by using parametric tests such as t, F, Z, correlation coefficient, etc., whereas nonparametric tests such as Wilcoxon signed-ranked, Chi-square, Mann–Whitney U, and Kruskal Wallis are used to analyze nonmetric data.

Parametric tests are more reliable than the nonparametric, but to use such tests certain assumptions must be satisfied. On the other hand, nonparametric tests are more flexible, easy to use, and not many assumptions are required to use them.

Nonmetric and metric data are also known as qualitative and quantitative data, respective...

Table of contents

• COVER
• TITLE PAGE
• TABLE OF CONTENTS
• PREFACE
• ABOUT THE COMPANION WEBSITE
• ACKNOWLEDGMENTS
• 1 INTRODUCTION TO DATA TYPES AND SPSS OPERATIONS
• 2 DESCRIPTIVE PROFILE
• 3 CORRELATION COEFFICIENT AND PARTIAL CORRELATION
• 4 COMPARING MEANS
• 5 INDEPENDENT MEASURES ANOVA
• 6 REPEATED MEASURES ANOVA
• 7 ANALYSIS OF COVARIANCE
• 8 NONPARAMETRIC TESTS IN SPORTS RESEARCH
• 9 REGRESSION ANALYSIS AND MULTIPLE CORRELATIONS
• 10 APPLICATION OF DISCRIMINANT FUNCTION ANALYSIS
• 11 LOGISTIC REGRESSION FOR DEVELOPING LOGIT MODEL IN SPORT
• 12 APPLICATION OF FACTOR ANALYSIS
• APPENDIX
• BIBLIOGRAPHY
• INDEX
• END USER LICENSE AGREEMENT