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Video Data Analysis

Video Data Analysis
Author: Anne Nassauer
Publisher: SAGE
Total Pages: 318
Release: 2022-03-17
Genre: Social Science
ISBN: 1529779162

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Video data is transforming the possibilities of social science research. Whether through mobile phone footage, body-worn cameras or public video surveillance, we have access to an ever-expanding pool of data on real-life situations and interactions. This book provides a flexible framework for working with video data and understanding what it says about social life. With examples from a range of real video research projects, the book showcases step-by-step how to analyse any kind of data, including both found and generated videos. It also includes a non-technical discussion of computer vision and its opportunities for social science research. With this book you will be able to: · Complete each step of the research process fully and efficiently, from data collection to management, analysis, and interpretation · Use video data in an ethical and effective way to maximise its impact · Utilise contemporary technology and accessible platforms such as YouTube, Twitter, Tik Tok and Facebook. This book is an ideal toolkit for researchers or postgraduate students across the social sciences working with video data as a part of their research projects. Accessible and practical, is written for qualitative and quantitative researchers, newcomers and experienced scholars. Features include interactive activities for different skill levels and ‘what to read next’ sections to help you engage further with the research mentioned in the book.


Python for Data Analysis

Python for Data Analysis
Author: Wes McKinney
Publisher: "O'Reilly Media, Inc."
Total Pages: 676
Release: 2017-09-25
Genre: Computers
ISBN: 1491957611

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Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples


Analyzing and Interpreting Qualitative Research

Analyzing and Interpreting Qualitative Research
Author: Charles Vanover
Publisher: SAGE Publications
Total Pages: 505
Release: 2021-04-08
Genre: Education
ISBN: 1544395884

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Drawing on the expertise of major names in the field, this text provides comprehensive coverage of the key methods for analyzing, interpreting, and writing up qualitative research in a single volume.


A Hands-On Introduction to Data Science

A Hands-On Introduction to Data Science
Author: Chirag Shah
Publisher: Cambridge University Press
Total Pages: 459
Release: 2020-04-02
Genre: Business & Economics
ISBN: 1108472443

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An introductory textbook offering a low barrier entry to data science; the hands-on approach will appeal to students from a range of disciplines.


Analysis of Categorical Data with R

Analysis of Categorical Data with R
Author: Christopher R. Bilder
Publisher: CRC Press
Total Pages: 549
Release: 2014-08-11
Genre: Mathematics
ISBN: 1439855676

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Learn How to Properly Analyze Categorical Data Analysis of Categorical Data with R presents a modern account of categorical data analysis using the popular R software. It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses fundamentals, such as odds ratio and probability estimation. The authors give detailed advice and guidelines on which procedures to use and why to use them. The Use of R as Both a Data Analysis Method and a Learning Tool Requiring no prior experience with R, the text offers an introduction to the essential features and functions of R. It incorporates numerous examples from medicine, psychology, sports, ecology, and other areas, along with extensive R code and output. The authors use data simulation in R to help readers understand the underlying assumptions of a procedure and then to evaluate the procedure’s performance. They also present many graphical demonstrations of the features and properties of various analysis methods. Web Resource The data sets and R programs from each example are available at www.chrisbilder.com/categorical. The programs include code used to create every plot and piece of output. Many of these programs contain code to demonstrate additional features or to perform more detailed analyses than what is in the text. Designed to be used in tandem with the book, the website also uniquely provides videos of the authors teaching a course on the subject. These videos include live, in-class recordings, which instructors may find useful in a blended or flipped classroom setting. The videos are also suitable as a substitute for a short course.


Qualitative Data Analysis with ATLAS.ti

Qualitative Data Analysis with ATLAS.ti
Author: Susanne Friese
Publisher: SAGE
Total Pages: 333
Release: 2014-01-30
Genre: Social Science
ISBN: 1473904080

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Are you struggling to get to grips with qualitative data analysis? Do you need help getting started using ATLAS.ti? Do you find software manuals difficult to relate to? Written by a leading expert on ATLAS.ti, this book will guide you step-by-step through using the software to support your research project. In this updated second edition, you will find clear, practical advice on preparing your data, setting up a new project in ATLAS.ti, developing a coding system, asking questions, finding answers and preparing your results. The new edition features: methodological as well as technical advice numerous practical exercises and examples screenshots showing you each stage of analysis in version 7 of ATLAS.ti increased coverage of transcription new sections on analysing video and multimedia data a companion website with online tutorials and data sets. Susanne Friese teaches qualitative methods at the University of Hanover and at various PhD schools, provides training and consultancy for ATLAS.ti at the intersection between developers and users.


Analysis Techniques for Racecar Data Acquisition

Analysis Techniques for Racecar Data Acquisition
Author: Jorge Sergers
Publisher: SAE International
Total Pages: 537
Release: 2014-02-24
Genre: Computers
ISBN: 0768064597

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Racecar data acquisition used to be limited to well-funded teams in high-profile championships. Today, the cost of electronics has decreased dramatically, making them available to everyone. But the cost of any data acquisition system is a waste of money if the recorded data is not interpreted correctly. This book, updated from the best-selling 2008 edition, contains techniques for analyzing data recorded by any vehicle's data acquisition system. It details how to measure the performance of the vehicle and driver, what can be learned from it, and how this information can be used to advantage next time the vehicle hits the track. Such information is invaluable to racing engineers and managers, race teams, and racing data analysts in all motorsports. Whether measuring the performance of a Formula One racecar or that of a road-legal street car on the local drag strip, the dynamics of vehicles and their drivers remain the same. Identical analysis techniques apply. Some race series have restricted data logging to decrease the team’s running budgets. In these cases it is extremely important that a maximum of information is extracted and interpreted from the hardware at hand. A team that uses data more efficiently will have an edge over the competition. However, the ever-decreasing cost of electronics makes advanced sensors and logging capabilities more accessible for everybody. With this comes the risk of information overload. Techniques are needed to help draw the right conclusions quickly from very large data sets. In addition to updates throughout, this new edition contains three new chapters: one on techniques for analyzing tire performance, one that provides an introduction to metric-driven analysis, a technique that is used throughout the book, and another that explains what kind of information the data contains about the track.


Storytelling with Data

Storytelling with Data
Author: Cole Nussbaumer Knaflic
Publisher: John Wiley & Sons
Total Pages: 284
Release: 2015-10-09
Genre: Mathematics
ISBN: 1119002265

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Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!


A Practical Guide to Race Car Data Analysis

A Practical Guide to Race Car Data Analysis
Author: Bob Knox
Publisher: Createspace Independent Publishing Platform
Total Pages: 0
Release: 2011-03-05
Genre: Automobiles, Racing
ISBN: 9781456587918

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A Practical Guide to Race Car Data Analysis was written for the amateur and lower-level professional racers who either have a data system in their cars or who may be thinking about installing one but who do not have access to an experienced data engineer. Many of the data systems available today at reasonable prices offer capabilities that only professional race teams could afford just a few years ago. Unfortunately, most of these racers do not know how to use more than a small part of those capabilities. Using real track data, numerous real-world examples, and more than 200 illustrations, the Guide gives them the knowledge and skills they need to select, configure and use their data systems efficiently and effectively.Beginning with a detailed discussion of the things racers need to know about the hardware and software necessary for a an effective data system, the Guide continues with chapters on basic data analysis tools, more sophisticated data analysis tools like x-y plots and math channels, damper potentiometers and the wealth of important data they produce, brake and clutch pressure sensors, and creative use of math channels. The Guide concludes with a comprehensive scheme for analyzing data, examples of the data views used with the scheme, and detailed information on how to create and configure the data views.


Analyzing Qualitative Data with MAXQDA

Analyzing Qualitative Data with MAXQDA
Author: Udo Kuckartz
Publisher: Springer
Total Pages: 293
Release: 2019-05-31
Genre: Social Science
ISBN: 3030156710

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This book presents strategies for analyzing qualitative and mixed methods data with MAXQDA software, and provides guidance on implementing a variety of research methods and approaches, e.g. grounded theory, discourse analysis and qualitative content analysis, using the software. In addition, it explains specific topics, such as transcription, building a coding frame, visualization, analysis of videos, concept maps, group comparisons and the creation of literature reviews. The book is intended for masters and PhD students as well as researchers and practitioners dealing with qualitative data in various disciplines, including the educational and social sciences, psychology, public health, business or economics.