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Titlebook: Excel 2016 for Social Work Statistics; A Guide to Solving P Thomas J.‘Quirk,Simone Cummings Textbook 20171st edition Springer International

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發(fā)表于 2025-3-21 16:11:24 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Excel 2016 for Social Work Statistics
副標(biāo)題A Guide to Solving P
編輯Thomas J.‘Quirk,Simone Cummings
視頻videohttp://file.papertrans.cn/319/318279/318279.mp4
概述Presents key steps and examples to solve practical, easy-to-understand social work problems using Excel.Contains 163 illustrations in color.Suitable for undergraduate and graduate students.No backgrou
叢書(shū)名稱(chēng)Excel for Statistics
圖書(shū)封面Titlebook: Excel 2016 for Social Work Statistics; A Guide to Solving P Thomas J.‘Quirk,Simone Cummings Textbook 20171st edition Springer International
描述.This text is a step-by-step guide for students taking a first course in statistics for social work and for social work managers and practitioners who want to learn how to use Excel to solve practical statistics problems in in the workplace, whether or not they have taken a course in statistics..There is no other text for a first course in social work statistics that teaches students, step-by-step, how to use Excel to solve interesting social work statistics problems. Excel 2016 for Social Work Statistics explains statistical formulas and offers practical examples for how students can solve real-world social work statistics problems. This book leaves detailed explanations of statistical theory to other statistics textbooks and focuses entirely on practical, real-world problem solving..Each chapter briefly explains a topic and then demonstrates how to use Excel commands and formulas to solve specific social work statistics problems. ?This book gives practice in using Excel 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 so as not to have to write for
出版日期Textbook 20171st edition
關(guān)鍵詞Excel 2016; sample size; standard deviation; standard error of the mean; random number generator; confide
版次1
doihttps://doi.org/10.1007/978-3-319-66221-3
isbn_ebook978-3-319-66221-3Series ISSN 2570-4605 Series E-ISSN 2570-4613
issn_series 2570-4605
copyrightSpringer International Publishing AG 2017
The information of publication is updating

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Excel for Statisticshttp://image.papertrans.cn/e/image/318279.jpg
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Lattice Transformations in 2D Crystals,nd 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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Wellness, Resilience, and Mindfulnessconfidence interval. You will learn how to estimate the population mean (average) for a group of events or objects at a 95% confidence level so that you are 95% confident that the population mean is between a lower limit of the data and an upper limit of the data. The formula for computing this conf
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William I. Dorfman,Lenore E. A. Walker. This 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 you
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Efficiency Correction and Flux Division,nd 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 decision rule for either a
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Teaching Psychotherapy to Medical Students,model by using . to predict Y instead of a single predictor as we discussed in Chap. 6 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
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