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Titlebook: Excel 2013 for Social Sciences Statistics; A Guide to Solving P Thomas J. Quirk Textbook 2015 The Editor(s) (if applicable) and The Author(

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書目名稱Excel 2013 for Social Sciences Statistics
副標題A Guide to Solving P
編輯Thomas J. Quirk
視頻videohttp://file.papertrans.cn/319/318267/318267.mp4
概述Statistical theory and formulas are explained in clear language without bogging you down in mathematical fine points.You will be told each step of the way, not only how to use Excel, but also why you
叢書名稱Excel for Statistics
圖書封面Titlebook: Excel 2013 for Social Sciences Statistics; A Guide to Solving P Thomas J. Quirk Textbook 2015 The Editor(s) (if applicable) and The Author(
描述.This is the first book to show the capabilities of Microsoft Excel to teach social science statistics effectively. It is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical social science 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 social science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, .Excel 2013 for Social Science Statistics: A Guide to Solving Practical Problems. is the first book to capitalize 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 social science problems. Practice problems are provided at the end of each chapter with their solut
出版日期Textbook 2015
關鍵詞Applied Social Science Statistics; Applied Statistics; Basic Social Science Statistics; Excel 2013 Soci
版次1
doihttps://doi.org/10.1007/978-3-319-19177-5
isbn_softcover978-3-319-19176-8
isbn_ebook978-3-319-19177-5Series 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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https://doi.org/10.1007/978-3-642-23588-7nd 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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Finite and Locally Finite Groupsean. 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
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https://doi.org/10.1007/978-3-319-59495-8 and one measurement “number” on each of these people. This chapter asks you to change gears and deal with the situation in which you are measuring two groups of people instead of only one group of people. The nine steps for hypothesis-testing using the two-group t-test are presented, including the
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Inner-Product Spaces, Euclidean Spaces,on model 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 weighted differently in an equation, to predict Y. The job of multiple correlation
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https://doi.org/10.1007/978-3-658-42204-2ation mean for the data using either the 95?% confidence interval about the mean (Chap. 3 of this book) or the one-group t-test of the mean (Chap. 4 of this book). You have also learned how to test for the difference between the means for two groups of people to determine if this difference was a “s
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