Book description
Harness the power of Excel to discover what your numbers are hiding
Excel Data Analysis For Dummies, 2nd Edition is the ultimate guide to getting the most out of your data. Veteran Dummies author Stephen L. Nelson guides you through the basic and not-so-basic features of Excel to help you discover the gems hidden in your rough data. From input, to analysis, to visualization, the book walks you through the steps that lead to superior data analysis.
Excel is the number-one spreadsheet application, with ever-expanding capabilities. If you're only using it to balance the books, you're missing out on a host of functions that can benefit your business or personal finances by uncovering trends and other important information hidden within the numbers. Excel Data Analysis For Dummies, 2nd Edition eliminates the need for advanced statistics or analysis courses by allowing you to harness the full power of Excel to do the heavy lifting for you. This 2nd Edition is fully updated to include information about Excel's latest features, making it a your go-to Excel guide for data analysis. Topics include:
Working with external databases
PivotTables and PivotCharts
Excel for statistical and financial functions
Solver, Small Business Finance Manager, and more
The book also includes a guide to chart types and formatting, and advice on effective visual data presentation. You already have the data, so you might as well get something great out of it. Excel Data Analysis For Dummies, 2nd Edition is the key to discovering what your numbers are hiding.
Table of contents
-
- Introduction
-
Part I: Where's the Beef?
- Chapter 1: Introducing Excel Tables
- Chapter 2: Grabbing Data from External Sources
-
Chapter 3: Scrub-a-Dub-Dub: Cleaning Data
- Editing Your Imported Workbook
-
Cleaning Data with Text Functions
- What’s the big deal, Steve?
- The answer to some of your problems
- The CLEAN function
- The CONCATENATE function
- The EXACT function
- The FIND function
- The FIXED function
- The LEFT function
- The LEN function
- The LOWER function
- The MID function
- The PROPER function
- The REPLACE function
- The REPT function
- The RIGHT function
- The SEARCH function
- The SUBSTITUTE function
- The T function
- The TEXT function
- The TRIM function
- The UPPER function
- The VALUE function
- Converting text function formulas to text
- Using Validation to Keep Data Clean
-
Part II: PivotTables and PivotCharts
- Chapter 4: Working with PivotTables
- Chapter 5: Building PivotTable Formulas
- Chapter 6: Working with PivotCharts
- Chapter 7: Customizing PivotCharts
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Part III: Advanced Tools
- Chapter 8: Using the Database Functions
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Chapter 9: Using the Statistics Functions
- Counting Items in a Data Set
- Means, Modes, and Medians
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Finding Values, Ranks, and Percentiles
- MAX: Maximum value
- MAXA: Alternate maximum value
- MIN: Minimum value
- MINA: Alternate minimum value
- LARGE: Finding the kth largest value
- SMALL: Finding the kth smallest value
- RANK: Ranking an array value
- PERCENTRANK: Finding a percentile ranking
- PERCENTILE: Finding a percentile ranking
- FREQUENCY: Frequency of values in a range
- PROB: Probability of values
-
Standard Deviations and Variances
- STDEV: Standard deviation of a sample
- STDEVA: Alternate standard deviation of a sample
- STDEVP: Standard deviation of a population
- STDEVPA: Alternate standard deviation of a population
- VAR: Variance of a sample
- VARA: Alternate variance of a sample
- VARP: Variance of a population
- VARPA: Alternate variance of a population
- COVARIANCE.P and COVARIANCE.S: Covariances
- DEVSQ: Sum of the squared deviations
-
Normal Distributions
- NORM.DIST: Probability X falls at or below a given value
- NORM.INV: X that gives specified probability
- NORM.S.DIST: Probability variable within z-standard deviations
- NORM.S.INV: z-value equivalent to a probability
- STANDARDIZE: z-value for a specified value
- CONFIDENCE: Confidence interval for a population mean
- KURT: Kurtosis
- SKEW and SKEW.P: Skewness of a distribution
- t-distributions
- f-distributions
- Binomial Distributions
- Chi-Square Distributions
- Regression Analysis
- Correlation
-
Some Really Esoteric Probability Distributions
- BETA.DIST: Cumulative beta probability density
- BETA.INV: Inverse cumulative beta probability density
- EXPON.DIST: Exponential probability distribution
- GAMMA.DIST: Gamma distribution probability
- GAMMAINV: X for a given gamma distribution probability
- GAMMALN: Natural logarithm of a gamma distribution
- LOGNORMDIST: Probability of lognormal distribution
- LOGINV: Value associated with lognormal distribution probability
- POISSON: Poisson distribution probabilities
- WEIBULL: Weibull distribution
- ZTEST: Probability of a z-test
- Chapter 10: Descriptive Statistics
- Chapter 11: Inferential Statistics
-
Chapter 12: Optimization Modeling with Solver
- Understanding Optimization Modeling
- Setting Up a Solver Worksheet
- Solving an Optimization Modeling Problem
- Reviewing the Solver Reports
- Working with the Solver Options
-
Understanding the Solver Error Messages
- Solver has found a solution
- Solver has converged to the current solution
- Solver cannot improve the current solution
- Stop chosen when maximum time limit was reached
- Solver stopped at user’s request
- Stop chosen when maximum iteration limit was reached
- Objective Cell values do not converge
- Solver could not find a feasible solution
- Linearity conditions required by this LP Solver are not satisfied
- The problem is too large for Solver to handle
- Solver encountered an error value in a target or constraint cell
- There is not enough memory available to solve the problem
- Error in model. Please verify that all cells and constraints are valid
-
Part IV: The Part of Tens
-
Chapter 13: Ten Things You Ought to Know about Statistics
- Descriptive Statistics Are Straightforward
- Averages Aren’t So Simple Sometimes
- Standard Deviations Describe Dispersion
- An Observation Is an Observation
- A Sample Is a Subset of Values
- Inferential Statistics Are Cool but Complicated
- Probability Distribution Functions Aren't Always Confusing
- Parameters Aren't So Complicated
- Skewness and Kurtosis Describe a Probability Distribution’s Shape
- Confidence Intervals Seem Complicated at First, but Are Useful
- Chapter 14: Almost Ten Tips for Presenting Table Results and Analyzing Data
- Chapter 15: Ten Tips for Visually Analyzing and Presenting Data
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Chapter 13: Ten Things You Ought to Know about Statistics
- Appendix: Glossary of Data Analysis and Excel Terms
- About the Authors
- Cheat Sheet
- More Dummies Products
Product information
- Title: Excel Data Analysis For Dummies, 2nd Edition
- Author(s):
- Release date: May 2014
- Publisher(s): For Dummies
- ISBN: 9781118898093
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