Game Data Analysis - Tools and Methods:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham
Packt Publishing
2013
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| Schlagworte: | |
| Online-Zugang: | FAW01 FAW02 |
| Beschreibung: | This book features an introduction to the basic theoretical tenets of data analysis from a game developer's point of view, as well as a practical guide to performing gameplay analysis on a real-world game. This book is ideal for video game developers who want to try and experiment with the game analytics approach for their own productions. It will provide a good overview of the themes you need to pay attention to, and will pave the way for success. Furthermore, the book also provides a wide range of concrete examples that will be useful for any game data analysts or scientists who want to impro Cover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Context and Themes in Games; The rise of game analytics; Themes in games; The desire for reward; Ownership; Reputation; Achievement and collection; The desire for challenge; Complexity and difficulty; Competition between players; Desire for imagination; Discovery; Emotions and sensations; Immersion, story, and universe; Desire for entertainment; Distraction; Romping; From themes to engagement; Video game as a service; Free-to-play and engagement; References; Summary Chapter 2: Common Key Performance Indicators of Game Data AnalysisDefinition and framework of Key Performance Indicators; Criteria; Structure; Acquisition of new players; Retention of players; Monetization of players; Working regularly with KPIs; Summary; Chapter 3: Environment and Tools for Data Analysis; Typical programming environment for data mining and storage; MySQL; NoSQL; Hadoop and Hive; Tools available on the market for quick data mining; Available free tools; Facebook Insights; Google Analytics; Commercial solutions; Kontagent; Honey Tracks; Flurry Analytics Tools available for analysisOpen source tools; R-Project; Summary; Chapter 4: Game Analytics and Generation of Content; The A/B testing; The multivariate testing; Recommendations for good practices; Case study -- monetization pop up; Inventory of each feature; Concrete examples of versioning; First example; Second example; Summary; Chapter 5: Advanced Analysis and Statistical Methods; General statistical description; Central tendencies; Dispersion tendencies; Statistical distribution and laws; Correlation and regression between variables; Types of variables; Chi-squared test; Linear regression Logistic regressionMachine learning; Definition; Supervised learning; Unsupervised learning; Summary; Chapter 6: Data Visualization; Recommendations for good practices; Basic recommendations; Typical data visualization tools; Line chart; Bar chart; Round chart; Heatmap; Graphic semiology; Typical traps of data visualization; The choice of the scale -- values on axis; The choice of the scale -- equivalence and units between variables; Summary; Chapter 7: Limits of Game Data Analysis; Which game analytics should be used; Game analytics as a tool; Game analytics must serve your team When starting, focus your attention on simple practicesWhat game analytics should be not used for; Keep away from numbers; Practices that need to be avoided; Summary; Index |
| ISBN: | 9781849697910 1849697914 1306157749 9781306157742 1849697906 9781849697903 |
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| 500 | |a This book features an introduction to the basic theoretical tenets of data analysis from a game developer's point of view, as well as a practical guide to performing gameplay analysis on a real-world game. This book is ideal for video game developers who want to try and experiment with the game analytics approach for their own productions. It will provide a good overview of the themes you need to pay attention to, and will pave the way for success. Furthermore, the book also provides a wide range of concrete examples that will be useful for any game data analysts or scientists who want to impro | ||
| 500 | |a Cover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Context and Themes in Games; The rise of game analytics; Themes in games; The desire for reward; Ownership; Reputation; Achievement and collection; The desire for challenge; Complexity and difficulty; Competition between players; Desire for imagination; Discovery; Emotions and sensations; Immersion, story, and universe; Desire for entertainment; Distraction; Romping; From themes to engagement; Video game as a service; Free-to-play and engagement; References; Summary | ||
| 500 | |a Chapter 2: Common Key Performance Indicators of Game Data AnalysisDefinition and framework of Key Performance Indicators; Criteria; Structure; Acquisition of new players; Retention of players; Monetization of players; Working regularly with KPIs; Summary; Chapter 3: Environment and Tools for Data Analysis; Typical programming environment for data mining and storage; MySQL; NoSQL; Hadoop and Hive; Tools available on the market for quick data mining; Available free tools; Facebook Insights; Google Analytics; Commercial solutions; Kontagent; Honey Tracks; Flurry Analytics | ||
| 500 | |a Tools available for analysisOpen source tools; R-Project; Summary; Chapter 4: Game Analytics and Generation of Content; The A/B testing; The multivariate testing; Recommendations for good practices; Case study -- monetization pop up; Inventory of each feature; Concrete examples of versioning; First example; Second example; Summary; Chapter 5: Advanced Analysis and Statistical Methods; General statistical description; Central tendencies; Dispersion tendencies; Statistical distribution and laws; Correlation and regression between variables; Types of variables; Chi-squared test; Linear regression | ||
| 500 | |a Logistic regressionMachine learning; Definition; Supervised learning; Unsupervised learning; Summary; Chapter 6: Data Visualization; Recommendations for good practices; Basic recommendations; Typical data visualization tools; Line chart; Bar chart; Round chart; Heatmap; Graphic semiology; Typical traps of data visualization; The choice of the scale -- values on axis; The choice of the scale -- equivalence and units between variables; Summary; Chapter 7: Limits of Game Data Analysis; Which game analytics should be used; Game analytics as a tool; Game analytics must serve your team | ||
| 500 | |a When starting, focus your attention on simple practicesWhat game analytics should be not used for; Keep away from numbers; Practices that need to be avoided; Summary; Index | ||
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Datensatz im Suchindex
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| author | Thibault, Coupart |
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| bvnumber | BV043777433 |
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| dewey-full | 006.3 006.312 |
| dewey-hundreds | 000 - Computer science, information, general works |
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| dewey-search | 006.3 006.312 |
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| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
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| id | DE-604.BV043777433 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:34:50Z |
| institution | BVB |
| isbn | 9781849697910 1849697914 1306157749 9781306157742 1849697906 9781849697903 |
| language | English |
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| spelling | Thibault, Coupart Verfasser aut Game Data Analysis - Tools and Methods Birmingham Packt Publishing 2013 txt rdacontent c rdamedia cr rdacarrier This book features an introduction to the basic theoretical tenets of data analysis from a game developer's point of view, as well as a practical guide to performing gameplay analysis on a real-world game. This book is ideal for video game developers who want to try and experiment with the game analytics approach for their own productions. It will provide a good overview of the themes you need to pay attention to, and will pave the way for success. Furthermore, the book also provides a wide range of concrete examples that will be useful for any game data analysts or scientists who want to impro Cover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Context and Themes in Games; The rise of game analytics; Themes in games; The desire for reward; Ownership; Reputation; Achievement and collection; The desire for challenge; Complexity and difficulty; Competition between players; Desire for imagination; Discovery; Emotions and sensations; Immersion, story, and universe; Desire for entertainment; Distraction; Romping; From themes to engagement; Video game as a service; Free-to-play and engagement; References; Summary Chapter 2: Common Key Performance Indicators of Game Data AnalysisDefinition and framework of Key Performance Indicators; Criteria; Structure; Acquisition of new players; Retention of players; Monetization of players; Working regularly with KPIs; Summary; Chapter 3: Environment and Tools for Data Analysis; Typical programming environment for data mining and storage; MySQL; NoSQL; Hadoop and Hive; Tools available on the market for quick data mining; Available free tools; Facebook Insights; Google Analytics; Commercial solutions; Kontagent; Honey Tracks; Flurry Analytics Tools available for analysisOpen source tools; R-Project; Summary; Chapter 4: Game Analytics and Generation of Content; The A/B testing; The multivariate testing; Recommendations for good practices; Case study -- monetization pop up; Inventory of each feature; Concrete examples of versioning; First example; Second example; Summary; Chapter 5: Advanced Analysis and Statistical Methods; General statistical description; Central tendencies; Dispersion tendencies; Statistical distribution and laws; Correlation and regression between variables; Types of variables; Chi-squared test; Linear regression Logistic regressionMachine learning; Definition; Supervised learning; Unsupervised learning; Summary; Chapter 6: Data Visualization; Recommendations for good practices; Basic recommendations; Typical data visualization tools; Line chart; Bar chart; Round chart; Heatmap; Graphic semiology; Typical traps of data visualization; The choice of the scale -- values on axis; The choice of the scale -- equivalence and units between variables; Summary; Chapter 7: Limits of Game Data Analysis; Which game analytics should be used; Game analytics as a tool; Game analytics must serve your team When starting, focus your attention on simple practicesWhat game analytics should be not used for; Keep away from numbers; Practices that need to be avoided; Summary; Index Video games Data mining COMPUTERS / General bisacsh Data mining fast Video games fast |
| spellingShingle | Thibault, Coupart Game Data Analysis - Tools and Methods Video games Data mining COMPUTERS / General bisacsh Data mining fast Video games fast |
| title | Game Data Analysis - Tools and Methods |
| title_auth | Game Data Analysis - Tools and Methods |
| title_exact_search | Game Data Analysis - Tools and Methods |
| title_full | Game Data Analysis - Tools and Methods |
| title_fullStr | Game Data Analysis - Tools and Methods |
| title_full_unstemmed | Game Data Analysis - Tools and Methods |
| title_short | Game Data Analysis - Tools and Methods |
| title_sort | game data analysis tools and methods |
| topic | Video games Data mining COMPUTERS / General bisacsh Data mining fast Video games fast |
| topic_facet | Video games Data mining COMPUTERS / General |
| work_keys_str_mv | AT thibaultcoupart gamedataanalysistoolsandmethods |