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Paperback. Condition: new. Paperback. FeaturesWorked examples from psychologyClearly written, without mathematical formulaeWell-structured, for beginners and intermediate readersComprehensive chapter on categorical analysis- not just 'Chi squared'Effect sizes and confidence intervalsClear explanation of factor analysisCovers MANOVA, logistic regression and survival analysisIntroduces Bayesian statisticsReproduces a well-received short chapter on making presentationsData sets and case studies on the website Statistics for psychology students at university, at beginners and intermediate level, using open source statistical software. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Published by Vor Press, United Kingdom, 2019
ISBN 10: 1916477925 ISBN 13: 9781916477926
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Published by Engineering Science Reference, 2020
ISBN 10: 1799827682 ISBN 13: 9781799827689
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Hardcover. Condition: new. Hardcover. With the development of computing technologies in today's modernized world, software packages have become easily accessible. Open source software, specifically, is a popular method for solving certain issues in the field of computer science. One key challenge is analyzing big data due to the high amounts that organizations are processing. Researchers and professionals need research on the foundations of open source software programs and how they can successfully analyze statistical data.Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. Featuring coverage on a broad range of topics such as cluster analysis, time series forecasting, and machine learning, this book is ideally designed for researchers, developers, practitioners, engineers, academicians, scholars, and students who want to more fully understand in a brief and concise format the realm and technologies of open source software for big data and how it has been used to solve large-scale research problems in a multitude of disciplines. Presents research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. The book features coverage on a broad range of topics, including cluster analysis, time series forecasting, and machine learning. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Language: English
Published by Engineering Science Reference, 2020
ISBN 10: 1799827682 ISBN 13: 9781799827689
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Published by Engineering Science Reference, 2020
ISBN 10: 1799827682 ISBN 13: 9781799827689
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Published by Engineering Science Reference, 2020
ISBN 10: 1799827682 ISBN 13: 9781799827689
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Published by Business Science Reference 2020-02-28, 2020
ISBN 10: 1799827682 ISBN 13: 9781799827689
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Published by Engineering Science Reference, 2020
ISBN 10: 1799827682 ISBN 13: 9781799827689
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Paperback. Condition: new. Paperback. FeaturesWorked examples from psychologyClearly written, without mathematical formulaeWell-structured, for beginners and intermediate readersComprehensive chapter on categorical analysis- not just 'Chi squared'Effect sizes and confidence intervalsClear explanation of factor analysisCovers MANOVA, logistic regression and survival analysisIntroduces Bayesian statisticsReproduces a well-received short chapter on making presentationsData sets and case studies on the website Statistics for psychology students at university, at beginners and intermediate level, using open source statistical software. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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First Edition
Hardback. Condition: New. 1st. With the development of computing technologies in today's modernized world, software packages have become easily accessible. Open source software, specifically, is a popular method for solving certain issues in the field of computer science. One key challenge is analyzing big data due to the high amounts that organizations are processing. Researchers and professionals need research on the foundations of open source software programs and how they can successfully analyze statistical data.Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. Featuring coverage on a broad range of topics such as cluster analysis, time series forecasting, and machine learning, this book is ideally designed for researchers, developers, practitioners, engineers, academicians, scholars, and students who want to more fully understand in a brief and concise format the realm and technologies of open source software for big data and how it has been used to solve large-scale research problems in a multitude of disciplines.
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Hardcover. Condition: new. Hardcover. With the development of computing technologies in today's modernized world, software packages have become easily accessible. Open source software, specifically, is a popular method for solving certain issues in the field of computer science. One key challenge is analyzing big data due to the high amounts that organizations are processing. Researchers and professionals need research on the foundations of open source software programs and how they can successfully analyze statistical data.Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. Featuring coverage on a broad range of topics such as cluster analysis, time series forecasting, and machine learning, this book is ideally designed for researchers, developers, practitioners, engineers, academicians, scholars, and students who want to more fully understand in a brief and concise format the realm and technologies of open source software for big data and how it has been used to solve large-scale research problems in a multitude of disciplines. Presents research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. The book features coverage on a broad range of topics, including cluster analysis, time series forecasting, and machine learning. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Language: English
Published by Engineering Science Reference, 2020
ISBN 10: 1799827682 ISBN 13: 9781799827689
Seller: moluna, Greven, Germany
Condition: New. Presents research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. The book features coverage on a broad range of topics, includin.
Language: English
Published by Engineering Science Reference, 2020
ISBN 10: 1799827682 ISBN 13: 9781799827689
Seller: preigu, Osnabrück, Germany
Buch. Condition: Neu. Open Source Software for Statistical Analysis of Big Data | Emerging Research and Opportunities | Richard S. Segall (u. a.) | Buch | Gebunden | Englisch | 2020 | Engineering Science Reference | EAN 9781799827689 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Language: English
Published by Engineering Science Reference, 2020
ISBN 10: 1799827690 ISBN 13: 9781799827696
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Language: English
Published by Engineering Science Reference, 2020
ISBN 10: 1799827690 ISBN 13: 9781799827696
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First Edition
Hardback. Condition: New. 1st. With the development of computing technologies in today's modernized world, software packages have become easily accessible. Open source software, specifically, is a popular method for solving certain issues in the field of computer science. One key challenge is analyzing big data due to the high amounts that organizations are processing. Researchers and professionals need research on the foundations of open source software programs and how they can successfully analyze statistical data.Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. Featuring coverage on a broad range of topics such as cluster analysis, time series forecasting, and machine learning, this book is ideally designed for researchers, developers, practitioners, engineers, academicians, scholars, and students who want to more fully understand in a brief and concise format the realm and technologies of open source software for big data and how it has been used to solve large-scale research problems in a multitude of disciplines.
Language: English
Published by Engineering Science Reference, 2020
ISBN 10: 1799827690 ISBN 13: 9781799827696
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