Published by Cambridge University Press, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Language: English
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Published by Cambridge University Press CUP, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Language: English
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Published by Cambridge University Press, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Language: English
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Published by Cambridge University Press, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Language: English
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Published by Cambridge University Press, Cambridge, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Language: English
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Paperback. Condition: new. Paperback. Each chapter of this book covers specific topics in statistical analysis, such as robust alternatives to t-tests or how to develop a questionnaire. They also address particular questions on these topics, which are commonly asked by human-computer interaction (HCI) researchers when planning or completing the analysis of their data. The book presents the current best practice in statistics, drawing on the state-of-the-art literature that is rarely presented in HCI. This is achieved by providing strong arguments that support good statistical analysis without relying on mathematical explanations. It additionally offers some philosophical underpinnings for statistics, so that readers can see how statistics fit with experimental design and the fundamental goal of discovering new HCI knowledge. Written for human-computer interaction (HCI) researchers - whether undergraduates, professors, or UX professionals who need to analyse quantitative data - this book helps to improve readers' knowledge of the modern best practice in statistics and their understanding of how to do statistical analysis on their own data. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Cambridge University Press, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Language: English
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Published by Cambridge University Press, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Language: English
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Published by Cambridge University Press, Cambridge, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Language: English
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Add to basketPaperback. Condition: new. Paperback. Each chapter of this book covers specific topics in statistical analysis, such as robust alternatives to t-tests or how to develop a questionnaire. They also address particular questions on these topics, which are commonly asked by human-computer interaction (HCI) researchers when planning or completing the analysis of their data. The book presents the current best practice in statistics, drawing on the state-of-the-art literature that is rarely presented in HCI. This is achieved by providing strong arguments that support good statistical analysis without relying on mathematical explanations. It additionally offers some philosophical underpinnings for statistics, so that readers can see how statistics fit with experimental design and the fundamental goal of discovering new HCI knowledge. Written for human-computer interaction (HCI) researchers - whether undergraduates, professors, or UX professionals who need to analyse quantitative data - this book helps to improve readers' knowledge of the modern best practice in statistics and their understanding of how to do statistical analysis on their own data. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Published by Cambridge University Press, Cambridge, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Language: English
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Add to basketPaperback. Condition: new. Paperback. Each chapter of this book covers specific topics in statistical analysis, such as robust alternatives to t-tests or how to develop a questionnaire. They also address particular questions on these topics, which are commonly asked by human-computer interaction (HCI) researchers when planning or completing the analysis of their data. The book presents the current best practice in statistics, drawing on the state-of-the-art literature that is rarely presented in HCI. This is achieved by providing strong arguments that support good statistical analysis without relying on mathematical explanations. It additionally offers some philosophical underpinnings for statistics, so that readers can see how statistics fit with experimental design and the fundamental goal of discovering new HCI knowledge. Written for human-computer interaction (HCI) researchers - whether undergraduates, professors, or UX professionals who need to analyse quantitative data - this book helps to improve readers' knowledge of the modern best practice in statistics and their understanding of how to do statistical analysis on their own data. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.