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In the last several dozens movies, we have talked about ways that you could explore your data with graphics and descriptive statistics and inferential procedures. And while that's a great way for you as the analyst to get a thorough understanding of your data, if you really want your analysis to accomplish something useful you will have to communicate it to others. Now we've already discussed ways to modify charts as we have covered these charts; however tables can be an important part of communicating information. In fact, when I'm writing a research report I try to put all of the results and graphs and tables and then use the text to simply describe the patterns without including the numbers there.
In this movie, we will look at a way to format your tables to make them easier to follow and easier to communicate to others. In the next one, we will talk about ways to show correlation matrices and the results from regression analysis, and then finally we will have a movie that talks about how to export tables for use in other programs like word processors and spreadsheets and presentation software and webpages. For this example, I am going to be using the Google searches information, searches.sav that I have used in several others. I am going to start by getting some descriptive statistics here.
I am just going to come up to Analyze, to Descriptive Statistics to Frequencies, and what I am going to do is I am going to get the information about several variables that I could use, for instance, try to predict people's interest in SPSS as a search term in Google. I find it helpful to begin with the outcome variables. We will take SPSS and move that over. I might want to include Business Intelligence and Data Visualization. I might also want to include my Education Variable, the Percentage of each State's Population with a Bachelor's Degree or Higher, and then I might want to include the Age.
Now you see these are all scale variables. We got a little measuring stick right next to each one. I would also want to use these three region variables, but because those are dichotomous indicator variables I don't need the same kinds of statistics for them. So I am going to skip them for right now. Then what I am going to do is I am going to choose the statistics that I want, I want the Mean and the Standard Deviation and then I want what's called the Five number summary. That's the five quartile scores, the Minimum, the Maximum, the first quartile, the second quartile, which is also the median or the 50th percentile, and the third quartile.
I get those by clicking on the Minimum, the Maximum and Quartiles, and now I am ready. I can press Continue. And I don't want the frequency tables and I don't need any charts right now, so I am just going to press OK. And there we go. I have a short table. This is pretty easy to follow; however, there are too many decimal places and some of the statistics are out of order and I don't like the way the labels are. The easiest way to take this as to simply right-click on the table and copy it, and once that's copied I can go into Microsoft Excel and I'm going to go to the second column and I'll paste the table there.
The reason I used the second column is because I find it very helpful to have one column that can maintain the original order of things. I just type in a couple of numbers and then I can drag down and propagate the list. Then I can start deleting information that I don't need. I don't need this title. This is statistics. I do want to rearrange and use different names for the statistics that are in columns B and C. However, you'll see that SPSS has merged some of the cells which makes it harder to deal with. So what I'm going to do is I'm going to insert a new column and I will just call it Statistics, and then I'll put the names of the statistics.
You may want to call them different things. I have a particular set of abbreviations I frequently use. N is common for the sample size, and Missing I'm going to delete in a moment so I am not even going to add that. M for Mean, SD for Standard Deviation. Then the next five numbers are quartiles. Now I have a personal preference. This is not a common way of doing it but I like it. I refer to them as Q0 through 4. So the Minimum is Q0 because it's the 0th quartile. There's nothing below it. The Maximum is Q4 because everybody is below it, and the other ones are Q1, Q2, and Q3.
And once I have got those, I can actually take these two columns right here and I can delete them. Now the only problem is that these statistics are out of order. We have 2, 3, 4, 5, 6, 7, but then these ones need to be slightly different. I can get that if I just change this one to a 12, and then I select this column and sort, and now the Q4 goes to the bottom. I don't need this column anymore. I can delete it. Then I can delete the outlines around here. I can center everything.
I can make these columns slightly wider and now I am going to deal with the issue of decimal places. I don't need this many decimal places for the Percentage of the Population with the Bachelor's Degree or Higher and the Median Age. I think it's okay to have these two statistics, the Mean and Standard Deviation, go down to two decimal places. That's usually adequate for most purposes. And then for quartile statistics I actually prefer to take them down to no decimal places, and then over here for the three Google search terms we do have a separation issue in that.
These are numbers that inherently have a lot of decimal places. So what I'm going to do is I'm going to bring all of these down to two decimal places as well. I am going to delete this column for the missing variables. You can arrange things slightly differently, but what I want you to see is by copy and pasting from SPSS into Excel, it gives me a lot more flexibility in terms of rearranging things, changing the decimal places, renaming, and I can take the information and put it manually into a form that I feel is going to be easier to communicate to others.
Now in the next video, I am going show you how to deal with the table of results from a correlation and then from regression, and you can combine these to make a overall presentation of your data.
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