Microsoft Excel 2019 Data Analysis And Business Modeling – A book that has been read but is in good condition. Very minor damage to the cover, including tear marks, but no holes or tears. The dust jacket for hard covers may not be included. The binding has minimal wear. The majority of pages are intact with minimal creasing or tearing, minimal pencil underlining of text, no highlighting of text, no writing in margins. No pages are missing. See the seller’s listing for full details and a description of the imperfection. See all state definitions opens in a new window or tab
Master business modeling and analytical techniques with Microsoft Excel 2019 and Office 365 and transform data into results. Written by award-winning teacher Wayne Winston, this hands-on, scenario-based guide helps you use Excel to ask the right questions and get accurate, actionable answers. New coverage extends from Power Query/Get & Transform to Office 365 Geography and Stock data types. Practice with more than 800 problems, many based on real challenges faced by working professionals. Solve real business problems with Excel – and build your competitive advantage: Quickly move from the basics of Excel to advanced analysis. Use PowerQuery or Get & Transform to connect, merge, 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 lines, multiple regression and exponential smoothing Access basic financial, statistical and time functions Cover all great Excel charts Quickly generate forecasts from historical time-based data Use Solver to optimizing product mix, logistics, work schedules and investments – and even rating sports teams. Run Monte Carlo simulations of stock price and quote models Learn about basic probability and using Bayes theorem data modeling and Power Pivot to build and use relational data sources in an Excel workbook Automate repetitive analysis tasks using macros
Microsoft Excel 2019 Data Analysis And Business Modeling
Chapter 1 Basic Spreadsheet Design Chapter 2 Field Names Chapter 3 Lookup Functions Chapter 4 The INDEX Function Chapter 5 The MATCH Function Chapter 6 Text Functions Chapter 7 Dates and Date Functions Chapter 8 Evaluating an Investment Using the Net Present Value Approach Chapter 9 Internal Rate of Return Chapter 10 More financial functions in Excel Chapter 11 Circular References Chapter 12 IF Statements Chapter 13 Time and Time Functions Chapter 14 The Paste Special Command Chapter 15 Three-Dimensional Formulas and Links Chapter 16 The Review Tool Chapter 17 Sensitivity Analysis with Data Tables Chapter 18 The Target Search Command Chapter 19 Using Event Management for Sensitivity Analysis Chapter 20 The COUNTIF, COUNTIFS, COUNT, COUNTA, and COUNTBLANK Functions Chapter 21 The SUMIF, AVERAGEIF, SUMIFS, and AVERAGEIFS Functions Chapter 22 The OFFSET Function Chapter 23 The INDIRECT Function Chapter 24 . Chapter 25 Sorting in Excel Chapter 26 Tables Chapter 27 Q in Buttons, Scrollbars, Option Buttons, Checkboxes, Combo Boxes, and Group Lists Chapter 28 The Analytics Revolution Chapter 29 Introduction to Optimization with Excel Solver Chapter 30 Using Solver to Determine the Best Product Mix. Chapter 31 Using Solver to Schedule Labor Chapter 32 Using Solver to Solve Transportation or Distribution Problems. Chapter 33 Using Solver for Budgeting. Chapter 34 Using Solver for Budgeting. Chapter 35 Using Solver to Rate Sports Teams. Chapter 36 Warehouse Location and the GRG Multistart and Evolutionary Solver Engines 37. Evolutionary Solver Chapter 38. The Traveling Salesman Problem Chapter 39 Importing Data from a Text File or Document Chapter 40 Data Validation Chapter 41 Summarizing Data Using Histograms and Pareto tables Chapter 42 Summarizing data using descriptive statistics Chapter 43 Using pivot tables and slices to describe data Chapter 44 The data model Chapter 45 Power Pivot Chapter 46 Power View and 3D maps Chapter 47 Sparklines Chapter 48 Summarizing data using statistical database functions Chapter 49 Filtering Data and Removing Duplicates Chapter 50 Combining Data Chapter 51 Creating Subtotals Chapter 52 Graphics Chapter 53 Estimating Linear Relationships Exponential Growth Chapter 54 Modeling Chapter 55 The Power Curve Chapter 56 Using Correlations to Summarize Relationships Chapter 57 Introduction to Multiple Regression . Chapter 58. Introduction of Qualitative Factors in Multiple Regression. Chapter 59. Modeling Nonlinearity and Interaction 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. Winter’s Method Chapter 64. Proportion and Moving Average Forecasting Method Chapter 65. Forecasting in the presence of special events Chapter 66 Introduction to Probability Chapter 67 Introduction to Random Variables.
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