Assuming no prior knowledge of computer programming, this textbook begins with the fundamentals and reinforces skill development with exercises and projects. Difficult topics are explained with real-world examples, and students are supported in-text with explainer boxes. Example code and data are provided online.
Assuming no prior knowledge of computer programming, this textbook begins with the fundamentals and reinforces skill development with exercises and projects. Difficult topics are explained with real-world examples, and students are supported in-text with explainer boxes. Example code and data are provided online.
Maxwell Mansolf is Assistant Professor of Team Science in the Department of Medical Social Sciences at the Feinberg School of Medicine, Northwestern University. As a team scientist, Dr. Mansolf is a co-investigator and collaborator on a broad array of research projects, including on child health and education, cognitive aging, healthcare worker well-being, personality, missing data, machine learning, and psychometrics, with over 40 peer-reviewed publications to date. For over six years, he has taught an undergraduate intro to MATLAB course at UCLA.
Inhaltsangabe
Preface To the Student Part I. MATLAB Programming: 1. Basic MATLAB 2. Data Structures and Indexing 3. Functions 4. Logical Values 5. Conditionals and Loops 6. Problem Solving with Conditionals and Loops 7. Text 8. Other Data Structures 9. Loading and Saving Data 10. User-Defined Functions 11. Graphing in MATLAB Part II. Applications of MATLAB Programming in Behavioral Sciences: 12. Computational Modeling 13. Data Analysis 14. Computerized Experiments Glossary Index.
Preface To the Student Part I. MATLAB Programming: 1. Basic MATLAB 2. Data Structures and Indexing 3. Functions 4. Logical Values 5. Conditionals and Loops 6. Problem Solving with Conditionals and Loops 7. Text 8. Other Data Structures 9. Loading and Saving Data 10. User-Defined Functions 11. Graphing in MATLAB Part II. Applications of MATLAB Programming in Behavioral Sciences: 12. Computational Modeling 13. Data Analysis 14. Computerized Experiments Glossary Index.
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