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Lesson 4 in SPSS

Lesson 4 in SPSS. How to find measures of 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).

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Lesson 4 in SPSS

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  1. Lesson 4 in SPSS How to find measures of variability using SPSS

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

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

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

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

  6. 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.

  7. 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.

  8. 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.

  9. Running the Analysis • Now we can click on OK.

  10. 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

  11. 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. By dividing the skewness by its standard error, we get 0.524/0.063 = 8.317. What does this mean? You’ll learn more about this in the next lesson. For now, know that any value greater than 3.3 or less than -3.3 indicates a high degree of skewness. Yep, we’re skewed!

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

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