This textbook is designed for teaching quantitative research in the scientific, health and engineering disciplines at first-year undergraduate level, with an emphasis on statistics. Almost every dataset used is a real dataset, and is available online or in an associated R package SRMData.
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Peter K. Dunn is Associate Professor of Biostatistics in the School of Science, Technology and Engineering at the University of the Sunshine Coast. He has published in the areas of generalized linear models, Tweedie distributions and statistical education, and has authored numerous R packages. He is an award-winning statistical educator who has been teaching statistics for over 30 years.
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Hardcover. Etat : new. Hardcover. This textbook is designed for teaching quantitative research in the scientific, health and engineering disciplines at first-year undergraduate level, with an emphasis on statistics. It covers the research process, including asking research questions, research design, data collection, summarising data, analysis and communication. Many real journal articles are used throughout the text as examples that demonstrate the use of the techniques.Students are introduced to statistics as a method for answering questions. Descriptive research questions lead to analysis of single proportions and means. Repeated-measures research questions are answered using paired quantitative data. Relational research questions compare proportions, odds and means in different groups. Correlational research questions are studied using correlation and regression techniques.Statistical topics include numerical summary methods (such as means, odds ratios and identification of outliers), graphing (such as histograms, case-profile plots and scatterplots), confidence intervals and hypothesis testing. Emphasis is placed on understanding and concepts; while calculations are shown in simple situations, they are deferred to software when the computations become tedious and disruptive to understanding.Almost every dataset used is a real dataset, and is available online or in an associated R package SRMData. Software output is often used when calculations become onerous. The output is sufficiently generic that the book can be used in conjunction with any statistical software. This textbook is designed for teaching quantitative research in the scientific, health and engineering disciplines at first-year undergraduate level, with an emphasis on statistics. Almost every dataset used is a real dataset, and is available online or in an associated R package SRMData. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781032496726
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This textbook is designed for teaching quantitative research in the scientific, health and engineering disciplines at first-year undergraduate level, with an emphasis on statistics. It covers the research process, including asking research questions, research design, data collection, summarising data, analysis and communication. Many real journal articles are used throughout the text as examples that demonstrate the use of the techniques.Students are introduced to statistics as a method for answering questions. Descriptive research questions lead to analysis of single proportions and means. Repeated-measures research questions are answered using paired quantitative data. Relational research questions compare proportions, odds and means in different groups. Correlational research questions are studied using correlation and regression techniques.Statistical topics include numerical summary methods (such as means, odds ratios and identification of outliers), graphing (such as histograms, case-profile plots and scatterplots), confidence intervals and hypothesis testing. Emphasis is placed on understanding and concepts; while calculations are shown in simple situations, they are deferred to software when the computations become tedious and disruptive to understanding.Almost every dataset used is a real dataset, and is available online or in an associated R package SRMData. Software output is often used when calculations become onerous. The output is sufficiently generic that the book can be used in conjunction with any statistical software. 554 pp. Englisch. N° de réf. du vendeur 9781032496726
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