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Analysing Data with Excel

  • Importing and Cleaning Data

    Data is everywhere. For example, if you run a website, you’re collecting data continually and you may not even know it. Every visit to your site generates information that is stored in a file on your server. This file contains lots of useful information, if you take the time to examine it. That’s just one example of data collection. Virtually every automated system collects data and stores it. Most of the time, the system that collects the data is also equipped to verify and analyze the data — but not always. And, of course, data is also collected manually. A telephone survey is a good example. Excel is good tool for analyzing data, and it’s often used to summarize the information and display it in the form of tables and charts. But often, the data that’s collected isn’t perfect. For one reason or another, it needs to be cleaned up before it can be analyzed. One very common use for Excel is as a tool to clean up data. Cleaning up data involves getting raw data into a worksheet, and then manipulating it so it conforms to various requirements. In the process, the data will be made consistent so it can be properly analyzed. This chapter describes various ways to get data into a worksheet and provides some tips to help you clean it up.

  • Introducing Pivot Tables

    The PivotTable feature is perhaps the most technologically sophisticated component in Excel. With only a few mouse clicks, you can slice and dice a data table in dozens of different ways and produce just about any type of summary you can think of. If you haven’t yet discovered the power of pivot tables, this chapter provides an introduction, and Chapter 34 continues with many examples that demonstrate how easy it is to create powerful data summaries using pivot tables.

  • Analyzing Data with Pivot Tables

    The previous chapter introduces pivot tables. There, I present several examples to demonstrate the types of pivot table summaries that you can generate from a set of data. This chapter continues the discussion and explores the details of creating effective pivot tables. Creating a basic pivot table is very easy, and the examples in this chapter demonstrate additional pivot table features that you may find helpful. I urge you to try these techniques with your own data. If you don’t have suitable data, use the files available on this book’s website.

  • Performing Spreadsheet What-If Analysis

    One of the most appealing aspects of Excel is its ability to create dynamic models. A dynamic model uses formulas that instantly recalculate when you change values in cells that are used by the formulas. When you change values in cells in a systematic manner and observe the effects on specific formula cells, you’re performing a type of what-if analysis. What-if analysis is the process of asking such questions as “What if the interest rate on the loan changes to 7.5% rather than 7.0%?” or “What if we raise our product prices by 5%?” If you set up your worksheet properly, answering such questions is simply a matter of plugging in new values and observing the results of the recalculation. Excel provides useful tools to assist you in your what-if endeavors.

  • Analyzing Data Using Goal Seeking and Solver

    The preceding chapter discusses what-if analysis — the process of changing input cells to observe the results on other dependent cells. This chapter looks at that process from the opposite perspective: finding the value of one or more input cells that produces a desired result in a formula cell.

  • Analyzing Data with the Analysis ToolPak

    Although Excel was designed primarily for business users, people in other disciplines, including education, research, statistics, and engineering, also use the software. One way Excel addresses these nonbusiness users is with its Analysis ToolPak add-in. However, many features in the Analysis ToolPak are valuable for business applications as well.

Analysing Data with Excel

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