Michael A. Gallo – författare

This is the first textbook designed to teach statistics to students in aviation courses. All examples and exercises are grounded in an aviation context, including flight instruction, air traffic control, airport management, and human factors.

Structured in six parts, this book covers the key foundational topics relative to descriptive and inferential statistics, including hypothesis testing, confidence intervals, z and t tests, correlation, regression, ANOVA, and chi-square. In addition, this book promotes both procedural knowledge and conceptual understanding.

Detailed, guided examples are presented from the perspective of conducting a research study. Each analysis technique is clearly explained, enabling readers to understand, carry out, and report results correctly. Students are further supported by a range of pedagogical features in each chapter, including objectives, a summary, and a vocabulary check.

Digital supplements comprise downloadable data sets and short video lectures explaining key concepts. Instructors also have access to PPT slides and an instructor’s manual that consists of a test bank with multiple choice exams, exercises with data sets, and solutions.

This is the ideal statistics textbook for aviation courses globally, especially in aviation statistics, research methods in aviation, human factors, and related areas.

This is the first textbook designed to teach statistics to students in aviation courses. All examples and exercises are grounded in an aviation context, including flight instruction, air traffic control, airport management, and human factors.

Structured in six parts, this book covers the key foundational topics relative to descriptive and inferential statistics, including hypothesis testing, confidence intervals, z and t tests, correlation, regression, ANOVA, and chi-square. In addition, this book promotes both procedural knowledge and conceptual understanding.

Detailed, guided examples are presented from the perspective of conducting a research study. Each analysis technique is clearly explained, enabling readers to understand, carry out, and report results correctly. Students are further supported by a range of pedagogical features in each chapter, including objectives, a summary, and a vocabulary check.

Digital supplements comprise downloadable data sets and short video lectures explaining key concepts. Instructors also have access to PPT slides and an instructor’s manual that consists of a test bank with multiple choice exams, exercises with data sets, and solutions.

This is the ideal statistics textbook for aviation courses globally, especially in aviation statistics, research methods in aviation, human factors, and related areas.

Applied Multiple Regression/Correlation Analysis for Aviation Research describes and illustrates multiple regression/correlation (MRC) analysis in an aviation context, including flight instruction, airport design, airline routes, and aviation human factors research. Structured in four parts, the book first reviews the major concepts of bivariate correlation and regression and then extends the bivariate case to two, four, and k predictors coupled with discussions on statistical inference, underlying assumptions, and regression diagnostics relative to MRC analysis. The book then builds on this foundation by presenting MRC variable selection strategies (simultaneous, hierarchical, and statistical regression), analyzing sets of predictors, and introducing coding strategies for nominal predictors. The book concludes by presenting how MRC can be used to conduct an analysis of covariance (ANCOVA), interactions, mediation analysis, and binary logistic regression.

Throughout the presentation, the book provides a balance between procedural knowledge as well as conceptual understanding. Detailed guided examples are presented at the end of each chapter that apply the topics and concepts of the chapter from the perspective of conducting a research study. The analytic strategies demonstrated via these guided examples are clearly explained, enabling readers to understand, conduct, and report results correctly. Pedagogical features associated with each chapter include a set of student learning outcomes and an end-of-chapter package that consists of a summary of the chapter’s main topics/concepts, a list of key terms, and review exercises, including multiple-choice items and a research scenario with data for students to analyze.

Tailored to the needs of aviation students, Applied Multiple Regression/Correlation Analysis for Aviation Research is the ideal textbook for research-oriented graduate aviation programs such as a thesis-based master’s degree or doctoral program that require knowledge of advanced statistical strategies for analyzing research data.