How to find measures variability using SPSS

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Presentation transcript:

How to find measures variability using SPSS Lesson 3 in SPSS How to find measures variability using SPSS

The Dataset Here’s a nice dataset. We have one variable called Age. There are 1,514 observations in the dataset.

First Blush To get a quick picture of this dataset, let’s see a frequency distribution histogram (Lesson 1). Hmm, perhaps a bit skewed?

Selecting the Analysis From the SPSS menu bar, choose Analyze Descriptive statistics Frequencies

Select the Variable(s) In the Frequencies box, highlight the variable age, then click on the arrow to pop it into the Variables window.

Descriptives Box Notice that when you’ve done this, the OK box is now active. But let’s make sure we get the statistics we want.

Selecting the Statistics I’ve selected the mean, median and mode as my measures of central tendency. Plus, I asked for the sum. For my measures of spread, I’ve chosen standard deviation, variance, and range. Plus I asked for the minimum and maximum values.

The Interquartile Range To find the interquartile range in SPSS, select Quartiles. I’ve also asked it for a measure of the skewness of the distribution. Now click on Continue.

Running the Analysis Now we can click on OK.

The Output So what did we learn? The mode is 35, the median is 41.00, and the mean is 45.63. These measures appear to be the perfect definition of a positively skewed distribution. The range is 71 and goes from a minimum of 18 years to a maximum of 89 years old. The sample variance is 317.14 and taking the square root of that we have the sample standard deviation of 17.81

More Output To find the inter-quartile range, we take the 75th per-centile minus the 25th percentile. Here, it is 60 – 32 = 28. So the SIQ = 28/2 = 14. Also, we note our skewness value is .524 with a standard error of .063. Don’t worry about that now, we’ll look at this again in Lesson 4.

Visual Representation Median Mode Mean Mean Let’s mark these on our graph. SIQ = 14 s = 17.81 Range = 71