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Excel 2019 for Advertising Statistics

A Guide to Solving Practical Problems

  • Thomas J. Quirk
  • Eric Rhiney
Textbook

Part of the Excel for Statistics book series (EXCELSTAT)

Table of contents

  1. Front Matter
    Pages i-xix
  2. Thomas J. Quirk, Eric Rhiney
    Pages 23-37
  3. Thomas J. Quirk, Eric Rhiney
    Pages 67-81
  4. Thomas J. Quirk, Eric Rhiney
    Pages 111-154
  5. Thomas J. Quirk, Eric Rhiney
    Pages 155-171
  6. Thomas J. Quirk, Eric Rhiney
    Pages 173-191
  7. Back Matter
    Pages 193-254

About this book

Introduction

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.

Keywords

Excel 2019 Standard Deviation Sample Size Standard Error of the Mean Random Number Generator Confidence Interval TINV Function t-Test for the Mean Linear Regression Analysis of Variance

Authors and affiliations

  • Thomas J. Quirk
    • 1
  • Eric Rhiney
    • 2
  1. 1.Professor of MarketingWebster UniversitySt. LouisUSA
  2. 2.Associate Professor of MarketingWebster UniversitySt. LouisUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-39254-3
  • Copyright Information Springer Nature Switzerland AG 2020
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-030-39253-6
  • Online ISBN 978-3-030-39254-3
  • Series Print ISSN 2570-4605
  • Series Online ISSN 2570-4613
  • Buy this book on publisher's site
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