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派博传思国际中心 »期刊书目

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Titlebook: Excel 2019 for Advertising Statistics; A Guide to Solving P Thomas J. Quirk,Eric Rhiney Textbook 2020Latest edition The Editor(s) (if appli

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书目名称Excel 2019 for Advertising Statistics
副标题A Guide to Solving P
编辑Thomas J. Quirk,Eric Rhiney
视频video
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
丛书名称Excel for Statistics
图书封面Titlebook: Excel 2019 for Advertising Statistics; A Guide to Solving P Thomas J. Quirk,Eric Rhiney Textbook 2020Latest edition The Editor(s) (if appli
描述.Newly revised for Excel 2019, this text is a step-by-step guide for students taking a first coursein statistics for advertising and for advertising managers andpractitioners who want to learn how to use Excel to solve practicalstatistics problems in the workplace, whether or not they have taken acourse in statistics..Excel 2019 for Advertising Statistics .explainsstatistical formulas and offers practical examples for how students cansolve real-world advertising statistics problems. Eachchapter offers a concise overview of a topic, and then demonstrates how to use Excelcommands and formulas to solve specific advertising statisticsproblems. This book demonstrates how to use Excel 2019 in two differentways:  (1) writing formulas (e.g., confidence interval about the mean,one-group t-test, two-group t-test, correlation) and (2) using Excel’sdrop-down formula menus (e.g., simple linear regression, multiplecorrelation and multiple regression, andone-way ANOVA). Three practiceproblems are provided at the end of each chapter, along with theirsolutions in an appendix. An additional practice test allows readers totest their understanding of each chapter by attempting to solve aspecific pract
出版日期Textbook 2020Latest edition
关键词Excel 2019; Standard Deviation; Sample Size; Standard Error of the Mean; Random Number Generator; Confide
版次2
doihttps://doi.org/10.1007/978-3-030-39254-3
isbn_softcover978-3-030-39253-6
isbn_ebook978-3-030-39254-3Series 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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Correlation and Simple Linear Regression,search study and only one measurement (i.e., variable) “number” on each of these. This chapter asks you to change gears again and to deal with the situation in which you are measuring two variables instead of only one variable, and you are trying to discover the “relationship” between these variable
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Multiple Correlation and Multiple Regression,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 weighed differently in an equation, to predict Y. The job of multiple correlation is
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One-Way Analysis of Variance (ANOVA),ation mean for the data using either the 95% confidence interval about the mean (Chap. . of this book) or the one-group t-test of the mean (Chap. . of this book). You have also learned how to test for the difference between the means for two groups of to determine if this difference was a “significa
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Conclusion And Recommendations,ter to test your Excel skills, and the answers to these problems appear in Appendix A of this book. An additional practice problem is presented in the Practice Test given in Appendix B along with its answer in Appendix C of this book.
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