Описание: Newly revised to specifically address Microsoft Excel 2019, this book shows the capabilities of Excel in teaching engineering statistics effectively.
Описание: This book shows the capabilities of Microsoft Excel in teaching health services management statistics effectively. Similar to the previously published Excel 2016 for Health Services Management Statistics, this book is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical health services management problems. If understanding statistics isn’t your strongest suit, you are not especially mathematically inclined, or if you are wary of computers, this is the right book for you. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in health services courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2019 for Health Services Management Statistics: A Guide to Solving Practical Problems, 2nd Edition capitalizes on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand health services management problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full practice test (with answers in an appendix) that allows readers to test what they have learned.
Newly revised for Excel 2019, this text is a step-by-step guide for students taking a first course in statistics for advertising and for advertising managers and practitioners who want to learn how to use Excel to solve practical statistics problems in the workplace, whether or not they have taken a course in statistics.
Excel 2019 for Advertising Statistics explains statistical formulas and offers practical examples for how students can solve real-world advertising statistics problems. Each chapter offers a concise overview of a topic, and then demonstrates how to use Excel commands and formulas to solve specific advertising statistics problems. This book demonstrates how to use Excel 2019 in two different ways: (1) writing formulas (e.g., confidence interval about the mean, one-group t-test, two-group t-test, correlation) and (2) using Excel's drop-down formula menus (e.g., simple linear regression, multiple correlation and multiple regression, and one-way ANOVA). Three practice problems are provided at the end of each chapter, along with their solutions in an appendix. An additional practice test allows readers to test their understanding of each chapter by attempting to solve a specific practical advertising statistics problem using Excel; the solution to each of these problems is also given in an appendix. This latest edition features a wealth of new end-of-chapter problems and an update of the chapter content throughout.
Preface.- Acknowledgements.- 1 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean.- 2 Random Number Generator.- 3 Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing.- 4 One-Group t-Test for the Mean.- 5 Two-Group t-Test of the Difference of the Means for Independent Groups.- 6 Correlation and Simple Linear Regression.- 7 Multiple Correlation and Multiple Regression.- 8 One-Way Analysis of Variance (ANOVA).- Appendix A: Answers to End-of-Chapter Practice Problems.- Appendix B: Practice Test.- Appendix C: Answers to Practice Test.- Appendix D: Statistical Formulas.- Appendix E: t-table.- Index.
Описание: Excel 2019 for Social Work Statistics: A Guide to Solving Practical Problems capitalizes on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work.
Автор: Ravid, Ruth Название: Practical statistics for educators ISBN: 1475846827 ISBN-13(EAN): 9781475846829 Издательство: NBN International Рейтинг: Цена: 4106.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book introduces educational students and practitioners to the use of statistics in education.
Описание: Some probability problems are so difficult that they stump the smartest mathematicians. But even the hardest of these problems can often be solved with a computer and a Monte Carlo simulation, in which a random-number generator simulates a physical process, such as a million rolls of a pair of dice. This is what Digital Dice is all about: how to ge
Автор: Ellison Stephen Название: Practical Statistics for the Analytical Scientist ISBN: 0854041311 ISBN-13(EAN): 9780854041312 Издательство: Royal Society of Chemistry Рейтинг: Цена: 6325.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book will be welcomed by practising analytical chemists as an important reference for day to day statistics in analytical chemistry.
Описание: Practical Business Statistics, 5e was written in response to instructors not wanting a formula driven, mathematically encyclopedic book. The use of computer applications means some topics no longer require coverage in detail. This allows future managers to know how to use and understand statistics. The text does this by using examples with real data that relate to the functional areas of business such as finance, accounting, and marketing. It de-emphasizes the theoretical, and presents the material in a well-written, easy style designed to motivate students. The emphasis is on understanding and applications as opposed to mathematical precision and formula detail.
Автор: Fu Название: A Practical Guide To Age-Period Coh ISBN: 1466592656 ISBN-13(EAN): 9781466592650 Издательство: Taylor&Francis Рейтинг: Цена: 11789.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Age-Period-Cohort analysis has a wide range of applications, from chronic disease incidence and mortality data in public health and epidemiology, to many social events (birth, death, marriage, etc) in social sciences and demography, and most recently investment, healthcare and pension contribution in economics and finance. Although APC analysis has been studied for the past 40 years and a lot of methods have been developed, the identification problem has been a major hurdle in analyzing APC data, where the regression model has multiple estimators, leading to indetermination of parameters and temporal trends. A Practical Guide to Age-Period Cohort Analysis: The Identification Problem and Beyond provides practitioners a guide to using APC models as well as offers graduate students and researchers an overview of the current methods for APC analysis while clarifying the confusion of the identification problem by explaining why some methods address the problem well while others do not.
Features
- Gives a comprehensive and in-depth review of models and methods in APC analysis.
- Provides an in-depth explanation of the identification problem and statistical approaches to addressing the problem and clarifying the confusion.
- Utilizes real data sets to illustrate different data issues that have not been addressed in the literature, including unequal intervals in age and period groups, etc.
Contains step-by-step modeling instruction and R programs to demonstrate how to conduct APC analysis and how to conduct prediction for the future
Reflects the most recent development in APC modeling and analysis including the intrinsic estimator
Wenjiang Fu is a professor of statistics at the University of Houston. Professor Fu's research interests include modeling big data, applied statistics research in health and human genome studies, and analysis of complex economic and social science data.
Автор: Bailer-Jones Coryn A L Название: Practical Bayesian Inference ISBN: 1316642216 ISBN-13(EAN): 9781316642214 Издательство: Cambridge Academ Рейтинг: Цена: 6018.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume introduces the major concepts of probability and statistics and the computational tools students need to extract information from data in the presence of uncertainty. Using a simple and intuitive Bayesian approach, the emphasis throughout is on the principles and showing how these methods can be implemented in practice.
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