The package is available for Windows, Mac, and Linux.

Calc will open Excel files and can save files in Excel format. Calc does almost everything that Excel does, with just enough exceptions to be annoying. So for the statistical tests I describe in this handbook, I feel confident that you can use Excel and get accurate results.Ī free alternative to Excel is Calc, part of the free, open-source package. After years of complaining, Microsoft finally fixed many of the problems in Excel 2010 (Keeling and Pavur 2011). Most of these problems were with procedures more advanced than those covered in this handbook, such as exponential smoothing, or were errors in how Excel analyzes very unusual data sets that you're unlikely to get from a real experiment. The more serious complaint about Excel is that some of the procedures gave incorrect results (McCullough and Heiser 2008, Yalta 2008). But if you are doing well designed, simple laboratory experiments, you may be able to analyze all of your data with the kinds of tests you can do in spreadsheets.

If you are in a field that requires complicated multivariate analyses, such as epidemiology or ecology, you will definitely have to use something more advanced than spreadsheets.

While it is true that you can't do advanced statistics with Excel, that doesn't make it wrong to use it for simple statistics that Excel can't do principal components analysis doesn't make its answer for a two-sample t–test incorrect. One of their main complaints is that it can't do more sophisticated tests. Some statisticians are contemptuous of Excel for statistics. Even if you're going to use something like SAS or SPSS or R, there will be many times when it's easier to enter your data into a spreadsheet first, inspect it for errors, sort and arrange it, then export it into a format suitable for your fancy-schmancy statistics package.

The graphing abilities of spreadsheets make it easy to inspect data for errors and outliers, look for non-linear relationships and non-normal distributions, and display your final results. You may spend months getting the most technologically sophisticated new biological techniques to work, but in the end you'll be able to analyze your data with a simple chi-squared test, t–test, one-way anova or linear regression. If you're like most biologists, you can do all of your statistics with spreadsheets such as Excel. You can do most, maybe all of your statistics using a spreadsheet such as Excel.

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