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Statistical Analysis: Microsoft Excel 2016

Statistical Analysis: Microsoft Excel 2016

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Description

  • Copyright 2018
  • Dimensions: 7" x 9-1/8"
  • Pages: 576
  • Edition: 1st
  • eBook (Watermarked)
  • ISBN-10: 0-13-484083-6
  • ISBN-13: 978-0-13-484083-3

USE EXCEL’S STATISTICAL TOOLS TO TRANSFORM YOUR DATA INTO KNOWLEDGE



Nationally recognized Excel expert Conrad Carlberg shows you how to use Excel 2016 to perform core statistical tasks every business professional, student, and researcher should master. Using real-world examples and downloadable workbooks, Carlberg helps you choose the right technique for each problem and get the most out of Excel’s statistical features. Along the way, he clarifies confusing statistical terminology and helps you avoid common mistakes.

You’ll learn how to use correlation and regression, analyze variance and covariance, and test statistical hypotheses using the normal, binomial, t, and F distributions. To help you make accurate inferences based on samples from a population, Carlberg offers insightful coverage of crucial topics ranging from experimental design to the statistical power of F tests. Updated for Excel 2016, this guide covers both modern consistency functions and legacy compatibility functions.


Becoming an expert with Excel statistics has never been easier! In this book, you’ll find crystal-clear instructions, insider insights, and complete step-by-step guidance.


  • Master Excel’s most useful descriptive and inferential statistical tools
  • Understand how values cluster together or disperse, and how variables move or classify jointly
  • Tell the truth with statistics—and recognize when others don’t
  • Infer a population’s characteristics from a sample’s frequency distribution
  • Explore correlation and regression to learn how variables move in tandem
  • Use Excel consistency functions such as STDEV.S( ) and STDEV.P( )
  • Test differences between two means using z tests, t tests, and Excel’s Data Analysis Add-in
  • Identify skewed distributions using Excel’s new built-in box-and-whisker plots and histograms
  • Evaluate statistical power and control risk
  • Explore how randomized block and split plot designs alter the derivation of F-ratios
  • Use coded multiple regression analysis to perform ANOVA with unbalanced factorial designs
  • Analyze covariance with ANCOVA, and properly use multiple covariance
  • Take advantage of Recommended PivotTables, Quick Analysis, and other Excel 2016 shortcuts

Sample Content

Table of Contents

2013 Table of Contents

Chapter 1: About Variables and Values
Chapter 2: How Values Cluster Together
Chapter 3: Variability: How Values Disperse
Chapter 4: How Variables Move Jointly: Correlation
Chapter 5: How Variables Classify Jointly: Contingency Tables
Chapter 6: Telling the Truth with Statistics
Chapter 7: Using Excel with the Normal Distribution
Chapter 8: Testing Differences between Means: The Basics
Chapter 9: Testing Differences between Means: Further Issues
Chapter 10: Testing Differences between Means: The Analysis of Variance
Chapter 11: Experimental Design and ANOVA
Chapter 12: Analysis of Variance: Further Issues
Chapter 13: Statistical Power
Chapter 14: Multiple Regression Analysis and Effect Coding: The Basics
Chapter 15: Multiple Regression Analysis: Further Issues
Chapter 16: Analysis of Covariance: The Basics
Chapter 17: Analysis of Covariance: Further Issues

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