Microsoft Excel Data Analysis and Business Modeling (Office 2021 and Microsoft 365)
(Sprache: Englisch)
Master business modeling and analysis techniques with Microsoft Excel and Office 365 and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands-on, scenario-focused guide helps you use Excel to ask the right...
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Klappentext zu „Microsoft Excel Data Analysis and Business Modeling (Office 2021 and Microsoft 365) “
Master business modeling and analysis techniques with Microsoft Excel and Office 365 and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands-on, scenario-focused guide helps you use Excel to ask the right questions and get accurate, actionable answers. A lot has changed in Office 365 since the previous edition. This new edition covers new functions (STOCKHISTORY, LET, LAMBDA, XLOOKUP) and new array functions. It also covers the new Data types that have been added. Finally, we've increased the coverage of Power Pivot , Macros, and Power Query. Practice with more than 800 problems, many based on actual challenges faced by working analysts. Solve real business problems with ExcelGÇöand build your competitive advantage:
- Quickly transition from Excel basics to sophisticated analytics
- Use PowerQuery or Get & Transform to connect, combine, and refine data sources
- Leverage Office 365's new Geography and Stock data types and six new functions
- Illuminate insights from geographic and temporal data with 3D Maps
- Summarize data with pivot tables, descriptive statistics, histograms, and Pareto charts
- Use Excel trend curves, multiple regression, and exponential smoothing
- Delve into key financial, statistical, and time functions
- Master all of Excel's great charts
- Quickly create forecasts from historical time-based data
- Use Solver to optimize product mix, logistics, work schedules, and investmentsGÇöand even rate sports teams
- Run Monte Carlo simulations on stock prices and bidding models
- Learn about basic probability and Bayes' Theorem
- Use the Data Model and Power Pivot to effectively build and use relational data sources inside an Excel workbook
- Automate repetitive analytics tasks by using macros
Inhaltsverzeichnis zu „Microsoft Excel Data Analysis and Business Modeling (Office 2021 and Microsoft 365) “
CHAPTER 1 Basic worksheet modelingCHAPTER 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 Excel's 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 Excel's new dynamic array functions
CHAPTER
... mehr
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
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
... weniger
Autoren-Porträt von Wayne Winston
Wayne L. Winston is Professor Emeritus of Decision Sciences at the Indiana University School of Business. He has also taught at the University of Houston and Wake Forest. He has won more than 40 teaching awards and taught Excel modeling and analytics at many Fortune 500 companies, accounting firms, the U.S. Army, and the U.S. Navy. He is a two-time Jeopardy! champion, and also is a co-developer of a player tracking system utilized by Mark Cuban and the Dallas Mavericks.
Bibliographische Angaben
- Autor: Wayne Winston
- 2021, 7. Auflage, 1168 Seiten, Masse: 18,7 x 23,2 cm, Kartoniert (TB), Englisch
- Verlag: Pearson
- ISBN-10: 0137613660
- ISBN-13: 9780137613663
- Erscheinungsdatum: 16.12.2021
Sprache:
Englisch
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