Excel is probably the most commonly used spreadsheet for PCs. Newly purchased computers often arrive with Excel already loaded. It is easily used to do a variety of calculations and includes a collection of statistical functions and a Data Analysis ToolPak.
As a result, if you suddenly find you need to do some statistical analysis, you may turn to it as the obvious choice. We decided to do some testing to see how well Excel would serve as a Data Analysis application.
To present the results, we will use a small example. The data for this example is fictitious. It was chosen to have two categorical and two continuous variables so that we could test a variety of basic statistical techniques.
The quickest way to get means and standard deviations for a entire group is using Descriptives in the Data Analysis tools. You can choose several adjacent columns for the Input Range (in this case the X and Y columns), and each column is analyzed separately. The labels in the first row are used to label the output, and the empty cells are ignored. If you have more, non-adjacent columns you need to analyze, you will have to repeat the process for each group of contiguous columns. The procedure is straightforward, can manage many columns reasonably efficiently, and empty cells are treated properly.
A statistical package lets you choose as many variables as you wish for descriptive statistics, whether or not they are contiguous. You can get the descriptive statistics for all the subjects together, or broken down by a categorical variable such as treatment. You can select the statistics you want to see once, and it will apply to all variables chosen.
If you had a variety of different statistical procedures that you wanted to perform on your data, you would almost certainly find yourself doing a lot of sorting, rearranging, copying, and pasting of your data.
This is because each procedure requires that the data be arranged in a particular way, often different from the way another procedure wants the data arranged. In our small test, we had to sort the rows in order to do the t-test and copy some cells in order to get labels for the output.
We had to clear the contents of some cells in order to get the correct paired t-test but did not want those cells cleared for some other test. And we were only doing five tasks. It does not get better when you try to do more.
There is no single arrangement of the data that would allow you to do many different analyses without making many different copies of it. The need to manipulate the data in many ways greatly increases the chance of introducing errors.
Output location. The output from each analysis can go to a new sheet within your current Excel file (this is the default), or you can place it within the current sheet by specifying the upper left corner cell where you want it placed. Either way is a bit of a nuisance. If each output is in a new sheet, you end up with lots of sheets, each with a small bit of output.
If you place them in the current sheet, you need to place them appropriately; leave room for adding comments and labels; changes you need to make to format one output properly may affect another output adversely. Example: Output from Descriptives has a column of labels such as Standard Deviation, Standard Error, etc. You will want to make this column wide in order to be able to read the labels. But if a simple Frequency output is right underneath, then the column displaying the values being counted, which may just contain small integers, will also be wide.
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