Digital library
Textbooks, references and open learning resources.
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The Stories Behind Social Statistics: Data Analysis, Interpretation, and Communication
Ezra Temko · Southern Illinois University Edwardsville
This text presents introductory social statistics concepts and techniques and how to use SPSS software.
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Applied Event-Related Potential Data Analysis
Steven J Luck · University of California, Davis
In the contents: 3.08: Exercise- Simple Statistical Analysis of N400 Data · 3.09: Exercise- A More Complex Analysis · 6.10: Exercise - Sequential Analysis of the P3b
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Social Data Analysis: Qualitative and Quantitative Approaches
Mikaila Mariel Lemonik Arthur and Roger Clark · Rhode Islange College
In the contents: 01: Introducing Social Data Analysis · 1.01: Introducing Social Data Analysis · 02: Quantitative Data Analysis
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Statistical Analysis of Data for Engineers
Joshua Steimel · Cal Poly Humbolt
In the contents: Chapter 09: Analysis of Variance (ANOVA)
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Algorithm Design and Analysis
Godfry Justo · African Virtual University
In the contents: 01: Fundamental Design and Analysis Techniques · 1.01: Activity 1 - Overview of Algorithm Design and Analysis
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A Brief Introduction to Engineering Computation with MATLAB
Serhat Beyenir · British Columbia Institute of Technology
In the contents: 1.07: Regression Analysis
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Open Data Structures - An Introduction
Pat Morin · Carleton University
In the contents: 4.04: Analysis of Skiplists
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Geographic Information Systems and Cartography
Adam Dastrup · Salt Lake Community College
In the contents: 07: Vector Data Analysis · 7.02: Single Layer Analysis · 7.03: Multiple Layer Analysis
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Data Structures
Wikipedia · LibreTexts
This book is about the creation and analysis of efficient data structures. To understand the material in this book you should be comfortable enough in a programming language to be capable of working with and writing your own variables, arithmetic expressions, if-else conditions, loops, subroutines (also known as functions), pointers (also known as references or object handles), structures (also known as records or classes), simple input and output, and simple recursion.
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CISP 430: Data Structures
Suha Aljuboori · Folsom Lake College
This course applies object-oriented techniques for systematic problem analysis and the managing of program complexity using abstraction. Specifications, design, coding, testing, and documentation of large multi-file programs are covered. It uses advanced language features such as classes, strings, non-text files, pointers, and recursion. Abstract data types such as stacks, queues, lists, binary trees, heaps/priority queues, hash tables, and graphs are examined.
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CPSI10003 Microcomputer Applications 1 - Microsoft Excel
LueCrecy Ragan · Arkansas State University-Beebe
In the contents: 2.1.05: What-If Analysis
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Linear Regression Using R - An Introduction to Data Modeling
David Lilja · University of Minnesota
In the contents: 3.04: Residual Analysis · 4.05: Residual Analysis
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Deep into Pharo
Alexandre Bergel, Damien Cassou, Stéphane Ducasse, Jannik Laval · LibreTexts
In the contents: 13: Blocks A Detailed Analysis · 16.05: Illustrative Analysis
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CISC 302: Computer Familiarization
Marjorie Duffy · Cosumnes River College
In the contents: 4.10: Formatting and Data Analysis
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C++ Programming I (McClanahan)
Patrick McClanahan · San Joaquin Delta College
In the contents: 1.05: Compiling- Analysis Phase
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Introduction to Data Analytics
Felix Amoruwa · De Anza College
In the contents: 1.03: Running Case Study - Mobile App Customer Churn Analysis · 1.6.04: Case Study Analysis · 2.7.04: Case Study Analysis
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Introduction to Database Systems
LibreTexts
In the contents: 06: Relationship Diagram for Data Analysis-ER and SQL
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Introduction to Computer Applications and Concepts (Lumen)
LibreTexts
In the contents: 16.15: Assignment- PowerPoint Analysis Discussion
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Workplace Software and Skills
OpenStax · LibreTexts
In the contents: 11: Advanced Excel Spreadsheets- Statistical and Data Analysis · 11.03: What-If Analysis · 11.05: Data Analysis Charts
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Answering Questions with Data - Introductory Statistics for Psychology Students
Matthew J. C. Crump · Brooklyn College of CUNY
In the contents: 7.01: ANOVA is Analysis of Variance · 9.05: Simple analysis of 2x2 repeated measures design