Microsoft Excel 2013: Data Analysis and Business Modeling

Overview

Master business modeling and analysis techniques with Microsoft Excel 2013, and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands-on, scenario-focused guide shows you how to use the latest Excel tools to integrate data from multiple tables—and how to effectively build a relational data source inside an Excel workbook.

Solve real business problems with ...

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Microsoft Excel 2013: Data Analysis and Business Modeling

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Overview

Master business modeling and analysis techniques with Microsoft Excel 2013, and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands-on, scenario-focused guide shows you how to use the latest Excel tools to integrate data from multiple tables—and how to effectively build a relational data source inside an Excel workbook.

Solve real business problems with Excel—and sharpen your edge

  • Summarize data with PivotTables and Descriptive Statistics
  • Explore new trends in predictive and prescriptive analytics
  • Use Excel Trend Curves, multiple regression, and exponential smoothing
  • Master advanced Excel functions such as OFFSET and INDIRECT
  • Delve into key financial, statistical, and time functions
  • Make your charts more effective with the Power View tool
  • Tame complex optimization problems with Excel Solver
  • Run Monte Carlo simulations on stock prices and bidding models
  • Apply important modeling tools such as the Inquire add-in
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Product Details

  • ISBN-13: 9780735669130
  • Publisher: Microsoft Press
  • Publication date: 1/31/2014
  • Pages: 888
  • Sales rank: 101,422
  • Product dimensions: 7.40 (w) x 9.00 (h) x 1.80 (d)

Meet the Author

Wayne L. Winston is a professor of Decision Sciences at Indiana University's Kelley School of Business and has earned numerous MBA teaching awards. For 20+ years, he has taught clients at Fortune 500 companies how to use Excel to make smarter business decisions. Wayne and his business partner Jeff Sagarin developed the player-statistics tracking and rating system used by the Dallas Mavericks professional basketball team. He is also a two time Jeopardy! Champion.

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Table of Contents

  • Introduction
  • Chapter 1: Range names
  • Chapter 2: Lookup functions
  • Chapter 3: INDEX function
  • Chapter 4: MATCH function
  • Chapter 5: Text functions
  • Chapter 6: Dates and date functions
  • Chapter 7: Evaluating investments by using net present value criteria
  • Chapter 8: Internal rate of return
  • Chapter 9: More Excel financial functions
  • Chapter 10: Circular references
  • Chapter 11: IF statements
  • Chapter 12: Time and time functions
  • Chapter 13: The Paste Special command
  • Chapter 14: Three-dimensional formulas
  • Chapter 15: The Auditing tool and Inquire add-in
  • Chapter 16: Sensitivity analysis with data tables
  • Chapter 17: The Goal Seek command
  • Chapter 18: Using the Scenario Manager for sensitivity analysis
  • Chapter 19: The COUNTIF, COUNTIFS, COUNT, COUNTA, and COUNTBLANK functions
  • Chapter 20: The SUMIF, AVERAGEIF, SUMIFS, and AVERAGEIFS functions
  • Chapter 21: The OFFSET function
  • Chapter 22: The INDIRECT function
  • Chapter 23: Conditional formatting
  • Chapter 24: Sorting in Excel
  • Chapter 25: Tables
  • Chapter 26: Spinner buttons, scroll bars, option buttons, check boxes, combo boxes, and group list boxes
  • Chapter 27: The analytics revolution
  • Chapter 28: Introducing optimization with Excel Solver
  • Chapter 29: Using Solver to determine the optimal product mix
  • Chapter 30: Using Solver to schedule your workforce
  • Chapter 31: Using Solver to solve transportation or distribution problems
  • Chapter 32: Using Solver for capital budgeting
  • Chapter 33: Using Solver for financial planning
  • Chapter 34: Using Solver to rate sports teams
  • Chapter 35: Warehouse location and the GRG Multistart and Evolutionary Solver engines
  • Chapter 36: Penalties and the Evolutionary Solver
  • Chapter 37: The traveling salesperson problem
  • Chapter 38: Importing data from a text file or document
  • Chapter 39: Importing data from the Internet
  • Chapter 40: Validating data
  • Chapter 41: Summarizing data by using histograms
  • Chapter 42: Summarizing data by using descriptive statistics
  • Chapter 43: Using PivotTables and slicers to describe data
  • Chapter 44: The Data Model
  • Chapter 45: PowerPivot
  • Chapter 46: Power View
  • Chapter 47: Sparklines
  • Chapter 48: Summarizing data with database statistical functions
  • Chapter 49: Filtering data and removing duplicates
  • Chapter 50: Consolidating data
  • Chapter 51: Creating subtotals
  • Chapter 52: Charting tricks
  • Chapter 53: Estimating straight-line relationships
  • Chapter 54: Modeling exponential growth
  • Chapter 55: The power curve
  • Chapter 56: Using correlations to summarize relationships
  • Chapter 57: Introduction to multiple regression
  • Chapter 58: Incorporating qualitative factors into multiple regression
  • Chapter 59: Modeling nonlinearities and interactions
  • Chapter 60: Analysis of variance: one-way ANOVA
  • Chapter 61: Randomized blocks and two-way ANOVA
  • Chapter 62: Using moving averages to understand time series
  • Chapter 63: Winters's method
  • Chapter 64: Ratio-to-moving-average forecast method
  • Chapter 65: Forecasting in the presence of special events
  • Chapter 66: An introduction to random variables
  • Chapter 67: The binomial, hypergeometric, and negative binomial random variables
  • Chapter 68: The Poisson and exponential random variable
  • Chapter 69: The normal random variable
  • Chapter 70: Weibull and beta distributions: modeling machine life and duration of a project
  • Chapter 71: Making probability statements from forecasts
  • Chapter 72: Using the lognormal random variable to model stock prices
  • Chapter 73: Introduction to Monte Carlo simulation
  • Chapter 74: Calculating an optimal bid
  • Chapter 75: Simulating stock prices and asset allocation modeling
  • Chapter 76: Fun and games: simulating gambling and sporting event probabilities
  • Chapter 77: Using resampling to analyze data
  • Chapter 78: Pricing stock options
  • Chapter 79: Determining customer value
  • Chapter 80: The economic order quantity inventory model
  • Chapter 81: Inventory modeling with uncertain demand
  • Chapter 82: Queuing theory: the mathematics of waiting in line
  • Chapter 83: Estimating a demand curve
  • Chapter 84: Pricing products by using tie-ins
  • Chapter 85: Pricing products by using subjectively determined demand
  • Chapter 86: Nonlinear pricing
  • Chapter 87: Array formulas and functions
  • About the Author
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