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https://www.wiley.com/Excel+Data+Analysis+For+Dummies%2C+5th+Edition-p-9781119844426
Paul McFedries
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Published:
February 15, 2022

Excel Data Analysis For Dummies

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Overview

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.

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About The Author

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.

excel data analysis for dummies

CHEAT SHEET

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Data analysis, by definition, requires some data to analyze. However, after you’ve imported or entered that data and cleaned it up as best you can. what’s your next move? Ah, that’s where the “analysis” part raises its hand in the air and says, “Pick me, pick me!”Excel is bursting at its digital seams with tools for analyzing data, but there are some that you’ll turn to most often.
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All kinds of people use Excel, including scientists, engineers, mathematicians, statisticians, and pollsters. But if you could somehow survey all the world’s Excel users, the typical user would probably have something to do with the financial industry. Whether they’re accountants or adjusters, bankers or borrowers, or money managers or money lenders, financial types rely on Excel every day to analyze budgets, loans, investments, and other monetary minutiae.
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Excel comes with so many powerful data-analysis tools and features that you might be wondering why you need to learn yet another: the PivotTable. The short answer is that the PivotTable is a useful weapon to add to your data-analysis arsenal. The long answer is that PivotTables are worth learning because they come with not just one or two but a long list of benefits.
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Data analysis, by definition, requires some data to analyze. However, after you’ve imported or entered that data and cleaned it up as best you can. what’s your next move? Ah, that’s where the “analysis” part raises its hand in the air and says, “Pick me, pick me!”Excel is bursting at its digital seams with tools for analyzing data, but there are some that you’ll turn to most often.
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You set up your Excel Solver model by using the Solver Parameters dialog box. You use the Set Objective box to specify the objective cell, and you use the To group to tell Excel Solver what you want from the objective cell: the maximum possible value; the minimum possible value; or a specific value. Finally, you use the By Changing Variable Cells box to specify the cells that Solver can use to plug in values to optimize the result.
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Excel spreadsheet tools such as Goal Seek that change a single variable are useful, but unfortunately most problems in business are not so easy. You’ll usually face formulas with at least two and sometimes dozens of variables. Often, a problem will have more than one solution, and your challenge will be using Excel to find the optimal solution (that is, the one that maximizes profit, or minimizes costs, or matches other criteria).
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To help you analyze data that’s stored in a table or range, you can turn to Excel’s powerful database functions, which enable you to apply calculations such as sum, average, and standard deviation.The database functions all use the same three arguments: database: The range of cells that make up the table you want to work with.
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When it’s time to get down to analyzing your data, a good place to start is with some basic statistics, such as counting items, calculating sums and averages, finding the largest and smallest values, working out the standard deviation, and so on. These measures fall under the general rubric of descriptive statistics, and Excel offers a fistful of functions that help you get the job done.
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To make an Excel PivotTable with a large number of row or column items easier to work with, you can group the items. For example, you can group months into quarters, thus reducing the number of items from twelve to four. Similarly, a report that lists dozens of countries can group those countries by continent, thus reducing the number of items to four or five, depending on where the countries are located.
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A comparison expression — also known as a logical expression or a Boolean expression — is an expression in which you compare the items in a range or table column with a value you specify. In Excel, you use comparison expressions to create advanced filters for a table, as well as in functions that require criteria, such as COUNTIF, SUMIF, and AVERAGEIF.
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The Data Analysis command provides a tool for calculating moving and exponentially smoothed averages in Excel. Suppose, for sake of illustration, that you’ve collected daily temperature information. You want to calculate the three-day moving average — the average of the last three days — as part of some simple weather forecasting.
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Perhaps the most common data analysis tool that you'll use in Excel is the one for calculating descriptive statistics. To see how this works, take a look at this worksheet. It summarizes sales data for a book publisher.In column A, the worksheet shows the suggested retail price (SRP). In column B, the worksheet shows the units sold of each book through one popular bookselling outlet.
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Excel provides a robust toolset for illustrating trends. You can do this by plotting trendlines in your Excel charts to offer a visual of your data. Here, you discover how to plot logarithmic trendlines, power trend lines, and polynomial trend lines in Excel. Plotting a logarithmic trend line in Excel A logarithmic trend is one in which the data rises or falls very quickly at the beginning but then slows down and levels off over time.
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In a general sense, Excel PivotTables take a large amount of information and condense that data into a report that tells you something useful or interesting. For example, take a look at the following table. Some great data, but how do you make sense of it? This table contains well over 100 records, each of which is an order from a sales promotion.
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When you add a second field to the row or column area, Excel displays subtotals for the items in the outer field. Having these outer field subtotals available is a useful component of Excel data analysis because it shows you not only how the data breaks down according to the items in the second (inner) field, but also the total of those items for each item in the first (outer) field.
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