Think STATS: Exploratory Data Analysis (Downey Allen B.)(Paperback)

Think STATS: Exploratory Data Analysis (Downey Allen B.)(Paperback)

If you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. By working with a single

Think Bayes: Bayesian Statistics in Python (Downey Allen B.)(Paperback)

Think Java: How to Think Like a Computer Scientist (Downey Allen B.)(Paperback)

Think Java is a hands-on introduction to computer science and programming used by many universities and high schools around the world. Its conciseness, emphasis on vocabulary, and informal tone make it particularly appealing for readers with little or no experience. The book starts with the most

Think Data Structures: Algorithms and Information Retrieval in Java (Downey Allen B.)(Paperback)

If you're a student studying computer science or a software developer preparing for technical interviews, this practical book will help you learn and review some of the most important ideas in software engineering--data structures and algorithms--in a way that's clearer, more concise, and more

Think Complexity: Complexity Science and Computational Modeling (Downey Allen B.)(Paperback)

Complexity science uses computation to explore the physical and social sciences. In Think Complexity, you'll use graphs, cellular automata, and agent-based models to study topics in physics, biology, and economics. Whether you're an intermediate-level Python programmer or a student of

Think Python: How to Think Like a Computer Scientist (Downey Allen B.)(Paperback)

If you want to learn how to program, working with Python is an excellent way to start. This hands-on guide takes you through the language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. This second

Think DSP: Digital Signal Processing in Python (Downey Allen B.)(Paperback)

If you understand basic mathematics and know how to program with Python, you're ready to dive into signal processing. While most resources start with theory to teach this complex subject, this practical book introduces techniques by showing you how they're applied in the real world. In the first

Qualitative Data Analysis: A Methods Sourcebook (Miles Matthew B.)(Paperback)

How to Think about Analysis (Alcock Lara)(Paperback)

Analysis (sometimes called Real Analysis or Advanced Calculus) is a core subject in most undergraduate mathematics degrees. It is elegant, clever and rewarding to learn, but it is hard. Even the best students find it challenging, and those who are unprepared often find it incomprehensible at first

Luminescence: Data Analysis and Modeling Using R (Pagonis Vasilis)(Paperback)

1. Introduction.- 2. Analysis and Modeling of TL Data.- 3. Analysis of Experimental OSL Data.- 4. Dose Response of Dosimetric Materials.- 5. Monte Carlo Simulations With Fixed Time Interval.- 6. Luminescence as a Stochastic Life-and-Death Process.- 7. Delocalized Transitions: The R Package

An Introduction to Data Analysis (Bergin Tiffany)(Paperback)

Covering the general process of data analysis to finding, collecting, organizing, and presenting data, this book offers a complete introduction to the fundamentals of data analysis. Using real-world case studies as illustrations, it helps readers understand theories behind and develop techniques

An Introduction to Statistical Genetic Data Analysis (Mills Melinda C.)(Paperback)

A comprehensive introduction to modern applied statistical genetic data analysis, accessible to those without a background in molecular biology or genetics.Human genetic research is now relevant beyond biology, epidemiology, and the medical sciences, with applications in such fields as psychology,

Introduction to Spatial Data Analysis (Wegmann Martin)(Paperback)

Genome Data Analysis (Kim Ju Han)(Paperback)

Data Analysis with Mplus (Geiser Christian)(Paperback)

A practical introduction to using Mplus for the analysis of multivariate data, this volume provides step-by-step guidance, complete with real data examples, numerous screen shots, and output excerpts. The author shows how to prepare a data set for import in Mplus using SPSS. He explains how to

Analysis of Economic Data 4e (Koop Gary)(Paperback)

Analysis of Economic Data has, over three editions, become firmly established as a successful textbook for students studying data analysis whose primary interest is not in econometrics, statistics or mathematics. It introduces students to basic econometric techniques and shows the reader how to

Data Analysis Using Stata, Third Edition (Kohler Ulrich)(Paperback)

Data Analysis Using Stata, Third Edition is a comprehensive introduction to both statistical methods and Stata. Beginners will learn the logic of data analysis and interpretation and easily become self-sufficient data analysts. Readers already familiar with Stata will find it an enjoyable resource

Multi-Domain Master Data Management: Advanced MDM and Data Governance in Practice (Allen Mark)(Paperback)

Data Analysis for Continuous School Improvement (Bernhardt Victoria L.)(Paperback)

Data Analysis for Continuous School Improvement provides a new definition of school improvement, away from a singular focus on compliance, toward a true commitment to excellence. This book is a call to action. It is about inspiring schools and school districts to commit to continuous school

How Dogs Think: What the World Looks Like to Them and Why They Act the Way They Do (Coren Stanley)(Paperback)

How Dogs Think is 'a sharp-eyed analysis and wry wit' (The Seattle Times) analysis of dog behavior from bestselling author, psychologist, and world-renowned expert, Dr. Stanley Coren. With smart humor, Cohen presents informative, in-depth, and fascinating details that shatter many common

Qualitative Data Analysis: An Introduction (Grbich Carol)(Paperback)

A one-stop-shop for students new to qualitative data analysis! In this fully updated and expanded Second Edition, Carol Grbich provides a guide through current issues in the analysis of qualitative data. Packed with detailed examples, a glossary, further reading lists and a section on writing up,

Applied Spatial Statistics and Econometrics: Data Analysis in R (Kopczewska Katarzyna)(Paperback)

This textbook is a comprehensive introduction to applied spatial data analysis using R. Each chapter walks the reader through a different method, explaining how to interpret the results and what conclusions can be drawn. The author team showcases key topics, including unsupervised learning, causal

Quantitative Longitudinal Data Analysis: Research Methods (Gayle Vernon)(Paperback)

First published as What is Quantitative Longitudinal Data Analysis?, this title is now available as part of the Bloomsbury Research Methods series. Across the social sciences, there is widespread agreement that quantitative longitudinal research designs offer analysts powerful scientific data

Data Analysis Using Regression and Multilevel Hierarchical Models (Gelman Andrew)(Paperback)

Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing