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In this course, author Barton Poulson takes a practical, visual, and non-mathematical approach to the basics of statistical concepts and data analysis in SPSS, the statistical package for business, government, research, and academic organization. From importing spreadsheets to creating regression models to exporting presentation graphics, this course covers all the basics, with an emphasis on clarity, interpretation, communicability, and application.
In the last movie we looked at a way of showing three scaled variables and maybe even a fourth categorical variable on top using the 3D scatterplot. Well, that seems like an intuitive approach and while they certainly are a lot of fun to play with while rotating the display, they can get confusing and also once they stop rotating, they're just another static 2D display that's poorly labeled. Nevertheless, it's important to be able to see the relationships between groups or variables. Fortunately, a slightly lower tech, but more effective solution is available by taking advantage of what the data visualization people call small multiples.
That is we can make an entire collection of 2D scatterplots that are connected to each other in the matrix, which makes it easier to see how the relationships between about as many variables as you have screen space for. Let's see how this works. I'm going to again use the Google Search data in Searches.sav. I need to go up to Graphs, then to Chart Builder. From there I come down on the gallery on the left to Scatter, and the third on the bottom is called Scatterplot Matrix.
I am going to click that and drag it up to the canvas. Now it looks a little funny here and on the bottom it just says Scatter Matrix. You'll see there's only one place to add variables. That's because I can add more than one variable to that list. In this particular case what I am going to do is I am going to choose let's say five variables. I am going to take SPSS. I am going to take Business Intelligence and I just drag it down. You see how it turns into a red plus there. I'll get Totally Lost.
I will also get Facebook. And finally, I think I'll give an indication of level of education. So what I've done is I've dragged five variables into this box at the bottom. Just in case I need it I'm going to come to Groups and Point ID and I am going to add a point ID label. I will use the state code and drag that hear to the Point Label variable and then I can click OK.
I get an extremely complicated looking chart, but this can be fixed. We need to edit it a little bit. I am going to double-click on it. The first thing I am going to do is I am going to remove this day labels. I may need those later, but for right now I can take them out. Then the next thing I am going to do is I am going to make the chart bigger. Right now the chart size is 375x468. I am just going to make it say for instance 500 and that gets it to 625.
When I do that and I maximize this window, I can actually read all of the labels. I can see things more clearly. Next I am going to make these dots smaller. I'll click on those. Let's go to 3 point and I will make them solid. And now it's a little easier to see them distinguished from each other. The next I will do is I am going to add a regression line and I'll go through all of them. Let me click on this and there we have it.
I can close this all now. Now I'm going to change the color of that regression line. I will make it a dark red instead of red so it doesn't jump out quite so much. What you have is each variable paired with the others by going across. So for instance on the top row where it says SPSS on the side, this is the relative importance of SPSS as a Google Search term. That's SPSS on the Y axis for all of the other ones. So, for instance, on the top row in the second column that's Business Intelligence across the bottom and SPSS up the side.
The one next to it is Totally Lost across the bottom of the X axis and SPSS on the Y axis. What you can see is when the regression lines are sloped that you can see their associations. So for instance there's a very strong association in the top row between SPSS and Totally Lost. That's the one in the middle on the top. On the other hand there's a little bit less of an association between SPSS and Facebook, the one right next to it. That line is relatively flat.
On the other hand we do have outliers showing on some of these and it might be interesting to see who that is. So I am going to double-click on the chart. I am going to turn on the Data Label mode by clicking in the menu bar here. I am going to find our little outlier here and just click on it and it will label it in all of the charts. And as is frequently the case it's Washington D.C. So we can see Washington D.C. is an outlier in most of these charts.
A scatterplot matrix in SPSS is a great way to see the connections between multiple variables all at once. It's easier to read than a 3D scatterplot and it lets you include more variables than you might otherwise be able to do. It's also a great tool to get a lot of visual detail from your data all at once, which is after all the purpose of data graphics. Now that we've covered several different combinations of variables and chart we will turn next to the descriptive and inferential statistics that can be used when looking at the associations of three or more variables.
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