Microsoft Excel 2019 Data Analysis and Business Modeling

1 Basic worksheet modeling

2 Range names

3 Lookup functions

4 The INDEX function

5 The MATCH function

6 Text functions and Flash Fill

7 Dates and date functions

8 Evaluating investments by using net present value criteria

9 IRR, XIRR, and MIRR functions

10 More Excel financial functions

11 Circular references

12 IF, IFERROR, IFS, CHOOSE, and SWITCH functions

13 Time and time functions

14 The Paste Special command

15 Three-dimensional formulas and hyperlinks

16 The auditing tool and the Inquire add-in

17 Sensitivity analysis with data tables

18 The Goal Seek command

19 Using the Scenario Manager for sensitivity analysis

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

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

22 The OFFSET function

23 The INDIRECT function

24 Conditional formatting

25 Sorting in Excel

26 Excel tables and table slicers

27 Spin buttons, scrollbars, option buttons, check boxes, combo boxes, and group list boxes

28 The analytics revolution

29 An introduction to optimization with Excel Solver

30 Using Solver to determine the optimal product mix

31 Using Solver to schedule your workforce

32 Using Solver to solve transportation or distribution problems

33 Using Solver for capital budgeting

34 Using Solver for financial planning

35 Using Solver to rate sports teams

36 Warehouse location and the GRG Multistart and Evolutionary Solver engines

37 Penalties and the Evolutionary Solver

38 The traveling salesperson problem

39 Importing data from a text file or document

40 Get & Transform (or s/b Get & Transform?)

41 Geography and Stock data types

42 Validating data

43 Summarizing data by using histograms and Pareto charts

44 Summarizing data by using descriptive statistics

45 Using pivot tables and slicers to describe data

46 The Data Model

47 Power Pivot

48 Filled and 3D Power Maps

49 Sparklines

50 Summarizing data with database statistical functions

51 Filtering data and removing duplicates

52 Consolidating data

53 Creating subtotals

54 Charting tricks

55 Estimating straight-line relationships

56 Modeling exponential growth

57 The power curve

58 Using correlations to summarize relationships

59 Introduction to multiple regression

60 Incorporating qualitative factors into multiple regression

61 Modeling nonlinearities and interactions

62 Analysis of variance: One-way ANOVA

63 Randomized blocks and two-way ANOVA

64 Using moving averages to understand time series

65 Winters method and the Forecast Sheet

66 Ratio-to-moving-average forecast method

67 Forecasting in the presence of special events

68 Introduction to Probability

69 An introduction to random variables

70 The binomial, hypergeometric, and negative binomial random variables

71 The Poisson and exponential random variables

72 The normal random variable and Z-scores

73 Weibull and beta distributions: Modeling machine life and project duration

74 Making probability statements from forecasts

75 Using the lognormal random variable to model stock prices

76 Importing Historical stock data into Excel

77 Introduction to Monte Carlo simulation

78 Calculating an optimal bid

79 Simulating stock prices and asset-allocation modeling

80 Fun and games: Simulating gambling and sporting event probabilities

81 Using resampling to analyze data

82 Pricing stock options

83 Determining customer value

84 The economic order quantity inventory model

85 Inventory modeling with uncertain demand

86 Queueing theory: The mathematics of waiting in line

87 Estimating a demand curve

88 Pricing products by using tie-ins

89 Pricing products by using subjectively determined demand

90 Nonlinear pricing

91 Array formulas and functions

92 Recording macros



93 Advanced Sensitivity Analysis