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Titlebook: Excel 2019 for Biological and Life Sciences Statistics; A Guide to Solving P Thomas J. Quirk,Meghan H. Quirk,Howard F. Horton Textbook 2020

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發(fā)表于 2025-3-21 19:29:42 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Excel 2019 for Biological and Life Sciences Statistics
副標(biāo)題A Guide to Solving P
編輯Thomas J. Quirk,Meghan H. Quirk,Howard F. Horton
視頻videohttp://file.papertrans.cn/319/318282/318282.mp4
概述Written in a step-by-step, instructional format, using the Excel steps with their accompanying color screenshot figures to show the reader what should be happening on the reader‘s computer monitor, en
叢書(shū)名稱Excel for Statistics
圖書(shū)封面Titlebook: Excel 2019 for Biological and Life Sciences Statistics; A Guide to Solving P Thomas J. Quirk,Meghan H. Quirk,Howard F. Horton Textbook 2020
描述Newly revised to specifically address Microsoft Excel 2019, this book is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical biological and life science problems. Excel is an effective learning tool for quantitative analyses in biological and life sciences courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. .Excel 2019 for Biological and Life Sciences Statistics. capitalizes on these improvements by teaching students and professionals how to apply Excel 2019 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 biological and life science 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. This new edition offers a wealth of new practice problems and solutions, as well as updated chapter content throughout..
出版日期Textbook 2020Latest edition
關(guān)鍵詞Applied Biological Statistics; Applied Life Sciences Statistics; Applied Statistics; Biological Statist
版次2
doihttps://doi.org/10.1007/978-3-030-39281-9
isbn_softcover978-3-030-39280-2
isbn_ebook978-3-030-39281-9Series ISSN 2570-4605 Series E-ISSN 2570-4613
issn_series 2570-4605
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Excel for Statisticshttp://image.papertrans.cn/e/image/318282.jpg
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Fiscal Decentralization and Developmentnd the standard error of the mean (s.e.) of these scores. All three of these statistics are basic to the study of statistics and are used frequently within many additional statistical tests. The formulas are presented, explained, and a practical example is given for each formula that shows how the f
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Fiscal Decentralization in India of people (objects, plants, or animals) from which you want to take a random sample. You will learn how to use Excel to create frame numbers for generating random numbers, why a set of duplicate frame numbers is important, and the Excel commands needed to sort the frame numbers into a random sequen
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Dennis C. Mueller,Emil Uddhammaris test compares the mean of your data set against the hypothesized population mean for your data to determine if the difference between these two values is “l(fā)arge enough” to be considered a “significant difference.” The formula is presented, explained, and a practical example is given using your ca
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Fiscal Adjustment in High-Debt Countries, your research study and one measurement “number” on each of these. This chapter asks you to change gears and deal with the situation in which you are measuring two groups of instead of only one group. The nine steps for hypothesis-testing using the two-group t-test are presented, including the deci
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Formulation of the General Modell by using . to predict Y instead of a single predictor as we discussed in Chap. . of this book. The resulting statistical procedure is called “multiple correlation” because it uses two or more predictors, each weighed differently in an equation, to predict Y. The job of multiple correlation is to d
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