Titlebook: Illustrating Statistical Procedures: Finding Meaning in Quantitative Data; Ray W. Cooksey Book 2020Latest edition Springer Nature Singapor

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Measurement Issues in Quantitative Research,fied. This is the domain of measurement and this chapter reviews several important considerations, including operational definition of constructs (and their links to theory), construct validity and measurement scales. In any behavioural research application where observations must be quantified thro

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Example Research Context & Quantitative Data Set,er. As you read, the variables used in the illustrations will remain familiar to you. The research context has been constructed to resonate not only with readers from a business background, but also with readers from social science, psychological, educational and health-related backgrounds. The rese

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Descriptive Statistics for Summarising Data, facilitate the description and summarisation of data. By ‘describe’ we generally mean either the use of some pictorial or graphical representation of the data (e.g. a histogram, box plot, radar plot, stem-and-leaf display, icon plot or line graph) or the computation of an index or number designed t

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Correlational Statistics for Characterising Relationships,apter are quite varied ranging from providing a simple summary of the relationship between two variables to facilitating an understanding of complex relationships among many variables. A statistical relationship is a pattern or an association which exists between two or more variables. We employ the

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Specialised Statistical Procedures,e discuss and illustrate include: Rasch models and item response theory (alternative approaches for assessing measurement quality); survival/failure analysis (useful for predicting how long a particular outcome event will take to be observed); quality control charts (useful for tracing, measuring an

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Recent Developments in the Study of Hormone Effects and Metabolism in Prostate Tissuely choice of topics for this morning’s discussion. Recent developments in the study of hormone effects and metabolism in prostate tissue hold the promise of bridging the large gap in biochemical knowledge between the developmental, histologic and clinical contributions of Lacassagne (1933 a, b), Hug

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Experiment and simulationting the lack of experiments. It is argued that there are principally two approaches to simulation: a conservative and a constructive one, and that both approaches cannot successfully be applied to the sciences this inquiry deals with. Last but not least, the methodological framework is used to unma