Want to take the guesswork out of analyzing data? Let Excel do all the work for you! Data collection, management and analysis is the key to making effective business decisions, and if you are like most people, you probably don't take full advantage of Excel's data analysis tools. With Excel Data Analysis For Dummies, 3rd Edition, you'll learn how to leverage Microsoft Excel to take your data analysis to new heights by uncovering what is behind all of those mind-numbing numbers. The beauty of Excel lies in its functionality as a powerful data analysis tool. This easy-to-read guide will show you how to use Excel in conjunction with external databases, how to fully leverage PivotTables and PivotCharts, tips and tricks for using Excel's statistical and financial functions, how to visually present your data so it makes sense, and information about the fancier, more advanced tools for those who have mastered the basics! Once you're up to speed, you can stop worrying about how to make use of all that data you have on your hands and get down to the business of discovering meaningful, actionable insights for your business or organization. Excel is the most popular business intelligence tool in the world, and the newest update Microsoft Excel 2016 features even more powerful features for data analysis and visualization. Users can slice and dice their data and create visual presentations that turn otherwise indecipherable reports into easy-to-digest presentations that can quickly and effectively illustrate the key insights you are seeking. Fully updated to cover the latest updates and features of Excel 2016 Learn useful details about statistics, analysis, and visual presentations for your data Features coverage of database and statistics functions, descriptive statistics, inferential statistics, and optimization modeling with Solver Helps anyone who needs insight into how to get things done with data that is unwieldy and difficult to understand With Excel Data Analysis For Dummies, 3rd Edition, you'll soon be quickly and easily performing key analyses that can drive organizational decisions and create competitive advantages.

Autorentext

Stephen L. Nelson provides accounting, business advisory, tax planning, and tax preparation services to small businesses. He belongs to the American Institute of CPAs and teaches graduate tax courses. Among Steve's 100-plus books are all editions of QuickBooks For Dummies and Quicken For Dummies. Elizabeth C. Nelson is a CPA and specializes in multi-state and international taxation of S corporations and partnerships. She holds a Bachelor of Science in Accounting from Western Governors University and is the co-author of the popular monographs Preparing the 3115 Form for the New Tangible Property Regulations and Small Businesses and the Affordable Care Act.

Klappentext
Learn to:

Navigate and analyze complex data
Work with external databases, PivotTables, and PivotCharts
Use Excel for statistical and financial functions
Make the most of the latest features of Excel Put the power of Excel to work and excel at data analysis! Most businesses are drowning in data, and making sense of it all is critical. Excel is a powerful data analysis tool, and this book shows you how to use it and become a data deciphering expert. You'll learn to organize data in workbooks, create powerful magic with PivotTables and PivotCharts, and explore advanced statistical tools that take you to the next level.
Table your data learn to export data from a database, build a table, get data from external sources, and query databases
Keep it clean delete unnecessary columns and rows in an imported workbook and clean your data with text functions
This way and that see how to view your data from different angles using PivotTables
Fine-tune with formulas build PivotTable formulas to create custom calculations and retrieve data from a PivotTable
Chart your course create and customize PivotCharts to display data in various ways, even in a 3D chart
Dive deeper check out a dozen database functions you can use for more detailed analysis
Statistically speaking explore Excel's statistics functions for finding percentiles and standard deviations, doing regression analysis, and more Open the book and find:
Ways to use filters with tables
All about exporting and importing data
Essential text functions for cleaning data
How to use the PivotTable and PivotChart wizards
Tips on customizing a PivotTable
When to use Chart Commands
Different types of PivotCharts
What you can do with descriptive statistics

Leseprobe
Chapter 1
Introducing Excel Tables

In This Chapter

Figuring out tables

Building tables

Analyzing tables with simple statistics

Sorting tables

Discovering the difference between using AutoFilter and filtering

First things first. I need to start my discussion of using Excel for data analysis by introducing Excel tables, or what Excel used to call lists. Why? Because, except in the simplest of situations, when you want to analyze data with Excel, you want that data stored in a table. In this chapter, I discuss what defines an Excel table; how to build, analyze, and sort a table; and why using filters to create a subtable is useful.
What Is a Table and Why Do I Care?

A table is, well, a list. This definition sounds simplistic, I guess. But take a look at the simple table shown in Figure 1-1 . This table shows the items that you might shop for at a grocery store on the way home from work.

Figure 1-1: A table: Start out with the basics.

As I mention in the Introduction of this book, many of the Excel workbooks that you see in the figures of this book are available for download from this book's companion website. For more on how to access the companion website, see the Introduction.

Commonly, tables include more information than Figure 1-1 shows. For example, take a look at the table shown in Figure 1-2 . In column A, for example, the table names the store where you might purchase the item. In column C, this expanded table gives the quantity of some item that you need. In column D, this table provides a rough estimate of the price.

Figure 1-2: A grocery list for the more serious shopper ... like me.

An Excel table usually looks more like the list shown in Figure 1-2 . Typically, the table enumerates rather detailed descriptions of numerous items. But a table in Excel, after you strip away all the details, essentially resembles the expanded grocery-shopping list shown in Figure 1-2 .

Let me make a handful of observations about the table shown in Figure 1-2 . First, each column shows a particular sort of information. In the parlance of database design, each column represents a field. Each field stores the same sort of information. Column A, for example, shows the store where some item can be purchased. (You might also say that this is the Store field.) Each piece of information shown in column A - the Store field - names a store: Sams Grocery, Hughes Dairy, and Butchermans.

The first row in the Excel worksheet provides field names. For example, in Figure 1-2 , row 1 names the four fields that make up the list: Store, Item, Quantity, and Price. You always use the first row, called the header row, of an Excel list to name, or identify, the fields in the list.

Starting in row 2, each row represents a record, or item, in the table. A record is a collection of related fields. For example, the record in row 2 in Figure 1-2 shows that at Sams Grocery, you plan to buy two loaves of bread for a price of $1 each. (Bear with me if these sample prices are wildly off; I usually don't do the shopping in my household.)

Row 3 shows or describes another item, coffee, also at Sams Grocery, fo…