Author Profile

Katherine Stewart received her Ph.D. in Experimental Psychology from the University of South Carolina in 1994. Since that time, she has been teaching and conducting research at Georgia Southern University. Dr. Stewart currently conducts research in two areas: teaching and ego depletion. Research on teaching and learning focuses on the importance of building rapport with students, including student perceptions of teachers based on early contacts with students and perceived teacher age. She conducts correlational and experimental studies on student evaluations of rapport as related to students' attitudes, motivation, and even grades. Completed projects include building rapport through touch such as a handshake, electronic communication such as email, and first-day-of-class activities. Her research interests are in developing and analysing estimation, inference, and optimization tools for structured high-dimensional data problems such as sparse regression, sparse nonparametric models, and low-rank models.

About The Book

Statistic covers methods used for gathering, organising (transforming and cleansing), analysing, and publishing results from measured data. Data represent specific parts of World which are observed and measured. Necessary note that data are represented by numbers (values) or symbols (strings). Measured data, stored typically in digital form, could be structured in tables, but they do not bring news and facts about measured part of World. On the other hand, if data are used in the (statistical) computational process, provided results could be called information. The information enables typically answer questions 'who', 'where', 'what', etc. Finally, the interpretation of information and providing a comprehensive summary of the observed research area is known as knowledge. Research Methodology and Statistical Methods provides students with a working introduction to statistical methods offering a wide range of applications that emphasize the quantitative skills useful across many academic disciplines. This text takes a classic approach that emphasizes concepts and techniques for working out problems and intepreting results. The book includes research projects, real-world case studies and numerous examples. Students are required to be familiar with algebra. This user-friendly textbook teaches students to understand and apply procedural steps in completing quantitative studies. It explains statistics while progressing through the steps of the hypothesis-testing process from hypothesis to results. The research problems used in the book reflect statistical applications related to interesting and important topics. In addition, the book provides a Research Analysis and Interpretation Guide to help students analyze research articles. Research Methodology and Statistical Methods is a fundamental reference for individuals who are deeply engaged in the complex realm of scientific investigation. This book offers an exhaustive examination of fundamental methodologies and statistical tools, serving as a comprehensive guide that provides academicians, students, and researchers with invaluable insights. Commence the expedition by laying a robust groundwork in research methodology. The reader is provided with proficient guidance throughout the procedure of developing research inquiries and planning investigations, guaranteeing a comprehensive comprehension of the ethical and efficacious principles that regulate the research process. A hallmark of the book is its practicality. It illustrates theoretical principles with real-world examples. This method allows readers to understand theoretical concepts and learn how to apply them to their study. The book explains descriptive statistics to sophisticated analytical methods to demystify statistics. Statistical literacy helps researchers traverse the statistical world and draw relevant conclusions from their data. The book includes multidisciplinary views to acknowledge the diversity of modern research. Contributors from different domains provide a variety of experiences and methods, making it useful for scholars across disciplines.

Table of Contents

Preface
Chapter 1. Introduction to Research in Remote Sensing
Chapter 2. Research Design and Proposal Writing
Chapter 3. Data Acquisition in Remote Sensing
Chapter 4. Measurement Scales and Data Types
Chapter 5. Descriptive Statistics for Remote Sensing
Chapter 6. Probability and Statistical Inference
Chapter 7. Hypothesis Testing and Statistical Significance
Chapter 8. Correlation and Regression Analysis
Chapter 9. Multivariate Statistical Techniques
Chapter 10. Time Series and Spatial Statistics
Bibliography
Index