Verlag: Cambridge University Press, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Verlag: Cambridge University Press CUP, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Sprache: Englisch
Anbieter: Books Puddle, New York, NY, USA
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Verlag: Cambridge University Press, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Sprache: Englisch
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Verlag: Cambridge University Press, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Sprache: Englisch
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Verlag: Cambridge University Press, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Sprache: Englisch
Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USA
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Verlag: Cambridge University Press, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Sprache: Englisch
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New.
Verlag: Cambridge University Press, 2019
ISBN 10: 110848252X ISBN 13: 9781108482523
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: Like New. First Edition. A bright, clean hardback, firm and square with strong joints, just a few minor rubs. Hence a non-text page is stamped 'damaged'. Despite such this book is actually nearly new condition. Thus it looks and feels unread with contents that are crisp, fresh and tight. Now offered for sale at a special bargain price.
Verlag: Cambridge University Press, Cambridge, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Sprache: Englisch
Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Paperback. Zustand: 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.
Verlag: Cambridge University Press, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Sprache: Englisch
Anbieter: PBShop.store US, Wood Dale, IL, USA
PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Verlag: Cambridge University Press, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Sprache: Englisch
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In den WarenkorbPAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Verlag: Cambridge University Press, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Sprache: Englisch
Anbieter: ALLBOOKS1, Direk, SA, Australien
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In den WarenkorbPaperback. Zustand: Brand New. 235 pages. 8.75x6.00x0.50 inches. In Stock.
Verlag: Cambridge University Press, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Sprache: Englisch
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In den WarenkorbPaperback / softback. Zustand: New. New copy - Usually dispatched within 4 working days.
Verlag: Cambridge University Press, Cambridge, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: 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.
Verlag: Cambridge University Press, Cambridge, 2019
ISBN 10: 110871059X ISBN 13: 9781108710596
Sprache: Englisch
Anbieter: AussieBookSeller, Truganina, VIC, Australien
Paperback. Zustand: 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.
Verlag: Cambridge University Press, Cambridge, 2019
ISBN 10: 110848252X ISBN 13: 9781108482523
Sprache: Englisch
Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Hardcover. Zustand: new. Hardcover. 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.
Verlag: Cambridge University Press, 2019
ISBN 10: 110848252X ISBN 13: 9781108482523
Sprache: Englisch
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
EUR 121,29
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In den WarenkorbHRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Verlag: Cambridge University Press, 2019
ISBN 10: 110848252X ISBN 13: 9781108482523
Sprache: Englisch
Anbieter: PBShop.store US, Wood Dale, IL, USA
HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Verlag: Cambridge University Press, 2019
ISBN 10: 110848252X ISBN 13: 9781108482523
Sprache: Englisch
Anbieter: THE SAINT BOOKSTORE, Southport, Vereinigtes Königreich
EUR 123,38
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In den WarenkorbHardback. Zustand: New. New copy - Usually dispatched within 4 working days. 529.
Verlag: Cambridge University Press, Cambridge, 2019
ISBN 10: 110848252X ISBN 13: 9781108482523
Sprache: Englisch
Anbieter: CitiRetail, Stevenage, Vereinigtes Königreich
EUR 109,80
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In den WarenkorbHardcover. Zustand: new. Hardcover. 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.
Verlag: Cambridge University Press, Cambridge, 2019
ISBN 10: 110848252X ISBN 13: 9781108482523
Sprache: Englisch
Anbieter: AussieBookSeller, Truganina, VIC, Australien
Hardcover. Zustand: new. Hardcover. 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.
Gebunden. Zustand: New. Über den AutorPaul Cairns is a reader in Human-Computer Interaction at the University of York and Scholar-in-Residence for The AbleGamers Charity that helps people with disabilities combat social isolation by making videogames more .
Verlag: Cambridge University Press Mär 2019, 2019
ISBN 10: 110848252X ISBN 13: 9781108482523
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Neuware - This book addresses common questions from HCI researchers when trying to do statistical analysis on their data.