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Elementary Statistics: A step by step approach 9e
This book presents the breadth and diversity of empirical and practical work done on statistics education around the world. A wide range of methods are used to respond to the research questions that form it's base. Case studies of single students or teachers aimed at understanding reasoning processes, large-scale experimental studies attempting to generalize trends in the teaching and learning of statistics are both employed. Various epistemological stances are described and utilized. The teaching and learning of statistics is presented in multiple contexts in the book. These include designed settings for young children, students in formal schooling, tertiary level students, vocational schools, and teacher professional development. A diversity is evident also in the choices of what to teach (curriculum), when to teach (learning trajectory), how to teach (pedagogy), how to demonstrate evidence of learning (assessment) and what challenges teachers and students face when they solve statistical problems (reasoning and thinking).
With 'Thinking from A to Z', Nigel Warburton presents an alphabetically arranged guide to help readers understand the art of arguing. This fully updated edition has many new entries including lawyer's answer, least worst option, stonewalling, sunk-cost fallacy and tautology.
A friendly and accessible approach to applying statistics in the real world With an emphasis on critical thinking, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics presents fun and unique examples, guides readers through the entire data collection and analysis process, and introduces basic statistical concepts along the way. Leaving proofs and complicated mathematics behind, the author portrays the more engaging side of statistics and emphasizes its role as a problem-solving tool. In addition, light-hearted case studies illustrate the application of statistics to real data analyses, highlighting the strengths and weaknesses of commonly used techniques. Written for the growing academic and industrial population that uses statistics in everyday life, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics highlights important issues that often arise when collecting and sifting through data. Featured concepts include: • Descriptive statistics • Analysis of variance • Probability and sample distributions • Confidence intervals • Hypothesis tests • Regression • Statistical correlation • Data collection • Statistical analysis with graphs Fun and inviting from beginning to end, The Art of Data Analysis is an ideal book for students as well as managers and researchers in industry, medicine, or government who face statistical questions and are in need of an intuitive understanding of basic statistical reasoning.
Elementary Statistics,Seventh Edition,is appropriate for someone learning introductory statistics who has experience with algebra. Elementary Statisticsis thorough and precise, and uses real data extensively. Readers find the book readable and clear, and they appreciate that the math level is right for a diverse population. The book thoroughly explains then illustrates concepts through an abundance of worked-out examples. The Nature of Statistics; Descriptive Statistics; Organizing Data; Descriptive Measures; Descriptive Methods in Regression and Correlation; Probability and Random Variables; The Normal Distribution; The Sampling Distribution of the Sample Mean; Inferential Statistics; Confidence Intervals for One Population Mean; Hypothesis Tests for One Population Mean; Inferences for Two Population Means; Inferences for Population Proportions; Chi-Square Procedures; Analysis of Variance (ANOVA); Inferential Methods in Regression and Correlation For all readers interested in Elementary Statistics
Increased attention is being paid to the need for statistically educated citizens: statistics is now included in the K-12 mathematics curriculum, increasing numbers of students are taking courses in high school, and introductory statistics courses are required in college. However, increasing the amount of instruction is not sufficient to prepare statistically literate citizens. A major change is needed in how statistics is taught. To bring about this change, three dimensions of teacher knowledge need to be addressed: their knowledge of statistical content, their pedagogical knowledge, and their statistical-pedagogical knowledge, i.e., their specific knowledge about how to teach statistics. This book is written for mathematics and statistics educators and researchers. It summarizes the research and highlights the important concepts for teachers to emphasize, and shows the interrelationships among concepts. It makes specific suggestions regarding how to build classroom activities, integrate technological tools, and assess students’ learning. This is a unique book. While providing a wealth of examples through lessons and data sets, it is also the best attempt by members of our profession to integrate suggestions from research findings with statistics concepts and pedagogy. The book’s message about the importance of listening to research is loud and clear, as is its message about alternative ways of teaching statistics. This book will impact instructors, giving them pause to consider: "Is what I’m doing now really the best thing for my students? What could I do better?" J. Michael Shaughnessy, Professor, Dept of Mathematical Sciences, Portland State University, USA This is a much-needed text for linking research and practice in teaching statistics. The authors have provided a comprehensive overview of the current state-of-the-art in statistics education research. The insights they have gleaned from the literature should be tremendously helpful for those involved in teaching and researching introductory courses. Randall E. Groth, Assistant Professor of Mathematics Education, Salisbury University, USA
Unique in that it collects, presents, and synthesizes cutting edge research on different aspects of statistical reasoning and applies this research to the teaching of statistics to students at all educational levels, this volume will prove of great value to mathematics and statistics education researchers, statistics educators, statisticians, cognitive psychologists, mathematics teachers, mathematics and statistics curriculum developers, and quantitative literacy experts in education and government.
Have you ever heard a Bible interpretation or a scientifically-based argument that just didn't seem correct? Did you wish you knew how to show that it wasn't true? In a postmodern society, Christians are increasingly confronted with assertions that contradict the principles they believe. They need to be able to critically analyze arguments and know how to refute, in a gentle way, those assertions that are not true. In order to do this Christians need three sets of skills: -hermeneutical skills -- to know how to accurately interpret God's Word and be able to correct misinterpretations of Scripture; -research design and statistical skills -- to be able to examine statements about God's world and evaluate whether or not they represent valid conclusions from the data; -knowledge of logical fallacies -- in order to be able to identify when invalid inductive or deductive conclusions were being drawn, either from God's Word or from research studies about God's world. This book will help you be able to do the following: -know and use valid hermeneutical skills; -understand research design and statistical analysis techniques; -recognize logical fallacies and replace them with accurate analyses. An excellent resource for pastors, Sunday school teachers, and group leaders, this book is as practical as it is valuable for persons who want to discern truth and refute error in a spirit of love.
Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.