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Microsoft Excel Data Analysis and Business Modeling (Office 2021 and Microsoft 365), 7th Edition

Microsoft Excel Data Analysis and Business Modeling (Office 2021 and Microsoft 365), 7th Edition

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About

Features

  • Hands-on, scenario-focused, and 100% practical
  • Updated for Excel's newest functionality
  • New spreadsheet models help beginner-to-intermediate Excel users move to more advanced techniques
  • Adds new problems with solutions

Description

  • Copyright 2022
  • Pages: 1168
  • Edition: 7th
  • eBook (Watermarked)
  • ISBN-10: 0-13-761376-8
  • ISBN-13: 978-0-13-761376-2

Master business modeling and analysis techniques with Microsoft Excel and transform data into bottom-line results. Award-winning educator Wayne Winstons hands-on, scenario-focused guide helps you use todays Excel to ask the right questions and get accurate, actionable answers. More extensively updated than any previous edition, new coverage ranges from one-click data analysis to STOCKHISTORY, dynamic arrays to Power Query, and includes six new chapters. Practice with over 900 problems, many based on real challenges faced by working analysts.

Solve real problems with Microsoft Exceland build your competitive advantage

  • Quickly transition from Excel basics to sophisticated analytics
  • Use recent Power Query enhancements to connect, combine, and transform data sources more effectively
  • Use the LAMBDA and LAMBDA helper functions to create Custom Functions without VBA
  • Use New Data Types to import data including stock prices, weather, information on geographic areas, universities, movies, and music
  • Build more sophisticated and compelling charts
  • Use the new XLOOKUP function to revolutionize your lookup formulas
  • Master new Dynamic Array formulas that allow you to sort and filter data with formulas and find all UNIQUE entries
  • Illuminate insights from geographic and temporal data with 3D Maps
  • Improve decision-making with probability, Bayes theorem, and Monte Carlo simulation and scenarios
  • Use Excel trend curves, multiple regression, and exponential smoothing for predictive analytics
  • Use Data Model and Power Pivot to effectively build and use relational data sources inside an Excel workbook

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Table of Contents

CHAPTER 1 Basic worksheet modeling

CHAPTER 2 Range names

CHAPTER 3 Lookup functions

CHAPTER 4 The INDEX function

CHAPTER 5 The MATCH function

CHAPTER 6 Text functions and Flash Fill

CHAPTER 7 Dates and date functions

CHAPTER 8 The net present value functions: NPV and XNPV

CHAPTER 9 The internal rate of return: IRR, XIRR, and MIRR functions

CHAPTER 10 More Excel financial functions

CHAPTER 11 Circular references

CHAPTER 12 IF, IFERROR, IFS, CHOOSE, SWITCH, and the IS functions

CHAPTER 13 Time and time functions

CHAPTER 14 The Paste Special command

CHAPTER 15 Three-dimensional formulas and hyperlinks

CHAPTER 16 The auditing tool and the Inquire add-in

CHAPTER 17 Sensitivity analysis with data tables

CHAPTER 18 The Goal Seek command

CHAPTER 19 Using the Scenario Manager for sensitivity analysis

CHAPTER 20 The COUNTIF, COUNTIFS, COUNT, COUNTA, and COUNTBLANK functions

CHAPTER 21 The SUMIF, AVERAGEIF, SUMIFS, AVERAGEIFS, MAXIFS, and MINIFS functions

CHAPTER 22 The OFFSET function

CHAPTER 23 The INDIRECT function

CHAPTER 24 Conditional formatting

CHAPTER 25 Excel tables and table slicers

CHAPTER 26 Spin buttons, scrollbars, option buttons, check boxes, combo boxes, and group list boxes

CHAPTER 27 Importing data from a text file or document

CHAPTER 28 The Power Query Editor

CHAPTER 29 Excels new data types

CHAPTER 30 Summarizing data with histograms and Pareto charts

CHAPTER 31 Summarizing data with descriptive statistics

CHAPTER 32 Sorting in Excel

CHAPTER 33 Filtering data and removing duplicates

CHAPTER 34 Summarizing data with database statistical functions

CHAPTER 35 Array formulas and functions

CHAPTER 36 Excels new dynamic array functions

CHAPTER 37 Validating data

CHAPTER 38 Using PivotTables and slicers to describe data

CHAPTER 39 The Data Model

CHAPTER 40 Power Pivot

CHAPTER 41 Consolidating data

CHAPTER 42 Creating subtotals

CHAPTER 43 Basic charting

CHAPTER 44 Advanced charting

CHAPTER 45 Filled and 3D Maps

CHAPTER 46 Sparklines

CHAPTER 47 Estimating straight-line relationships

CHAPTER 48 Modeling exponential growth

CHAPTER 49 The power curve

CHAPTER 50 Using correlations to summarize relationships

CHAPTER 51 Introduction to multiple regression

CHAPTER 52 Incorporating qualitative factors into multiple regression

CHAPTER 53 Modeling nonlinearities and interactions

CHAPTER 54 Analysis of variance: One-way ANOVA

CHAPTER 55 Randomized blocks and two-way ANOVA

CHAPTER 56 Using moving averages to understand time series

CHAPTER 57 Ratio-to-moving-average forecast method

CHAPTER 58 An introduction to probability

CHAPTER 59 An introduction to random variables

CHAPTER 60 The binomial, hypergeometric, and negative binomial random variables

CHAPTER 61 The Poisson and exponential random variable

CHAPTER 62 The normal random variable and Z-scores

CHAPTER 63 Making probability statements from forecasts

CHAPTER 64 Using the lognormal random variable to model stock prices

CHAPTER 65 Importing past stock prices, exchange rates, and cryptocurrency prices with the STOCKHISTORY function

CHAPTER 66 An introduction to optimization with Excel Solver

CHAPTER 67 Using Solver to determine the optimal product mix

CHAPTER 68 Using Solver to schedule your workforce

CHAPTER 69 Using Solver to solve transportation or distribution problems

CHAPTER 70 Using Solver for capital budgeting

CHAPTER 71 Using Solver for financial planning

CHAPTER 72 Using Solver to rate sports teams

CHAPTER 73 The Winters method and the Forecast Sheet tool

CHAPTER 74 Forecasting in the presence of special events

CHAPTER 75 Warehouse location and the GRG Multistart and Evolutionary Solver engines

CHAPTER 76 Penalties and the Evolutionary Solver

CHAPTER 77 The traveling salesperson problem

CHAPTER 78 Weibull and beta distributions: Modeling machine life and duration of a project

CHAPTER 79 Introduction to Monte Carlo simulation

CHAPTER 80 Calculating an optimal bid

CHAPTER 81 Simulating stock prices and asset-allocation modeling

CHAPTER 82 Fun and games: Simulating gambling and sporting-event probabilities

CHAPTER 83 Using resampling to analyze data

CHAPTER 84 Pricing stock options

CHAPTER 85 Determining customer value

CHAPTER 86 The economic order quantity inventory model

CHAPTER 87 Inventory modeling with uncertain demand

CHAPTER 88 Queuing theory: The mathematics of waiting in line

CHAPTER 89 Estimating a demand curve

CHAPTER 90 Pricing products by using tie-ins

CHAPTER 91 Pricing products by using subjectively determined demand

CHAPTER 92 Nonlinear pricing

CHAPTER 93 Use Analyze Data to find patterns in your data

CHAPTER 94 Recording macros

CHAPTER 95 The LET and LAMBDA functions and the LAMBDA helper functions

CHAPTER 96 Advanced sensitivity analysis

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