![]() ![]() If you're not sure about some command, you can inspect its result in data view if you run EXECUTE right after it. Let's now run these steps on transportation.sav with the syntax below. This method saves more effort insofar as you stack more variables: placing the IF command in step in a DO REPEAT loop does the trick. #Using graph builder in spss how to#The screenshots below illustrate how to mimic VARSTOCASES without needing its syntax. We'll replace it with a trick that creates nicer results and requires less syntax too. Now, we could use VARSTOCASES for our data but we find this rather tedious for 8 variables. The usual way to do so is with VARSTOCASES as illustrated below. ![]() For creating our chart, we need to stack these 2 sets vertically. Note that our data consist of 2 sets (work and leisure) of 8 dichotomous variables (transportation options). The data thus obtained are in transportation.sav, partly shown below. ![]() Respondents could select one or more means of transportation for both work and leisure related travelling. “which means of transportation do you use on a regular basis?” Example DataĪ sample of N = 259 respondents were asked As this requires restructuring our data, we'll first do so with a seriously cool trick. This tutorial shows how to create the clustered bar chart shown below in SPSS. The distance between the top of the box and top of the whisker shows the range of the top 25% of scores (approximately), similarly the distance between the bottom of the box and the end of the bottom whisker shows the range of the lowest 25% of scores (approximately).Clustered Bar Chart over Multiple Variables By Ruben Geert van den Berg under Charts in SPSS The top and bottom of the tinted box represents the upper and lower quartile respectively. The workers had a higher median than the wishers, indicating greater success overall. Within the box, there is a thick horizontal line, which shows the median. It is clear that the middle 50% of scores are more spread out for the hard-work group than for those who wished on a star because the box is much longer. Notice that there is a tinted box, which represents the IQR (i.e. The above figure shows the boxplots for the success data. To make a boxplot of the post-intervention success scores for our two groups, double click on the simple boxplot icon, then from the variable list select the Success_Post variable and drag it into y-axis and select the variable Strategy and drag it to x-axis. In the data file of success scores we have information about whether people worked hard or wished upon a star. This differs from the simple boxplot in that no categorical variable is selected for the x-axis.
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