﻿ Functional Flowchart System #5

Graziano & Raulin
Research Methods (8th edition)

## Describing the Sample Score Data

Score data has the properties of identity, magnitude, and equal intervals, but may or may not have a true zero. That means that all descriptive statistics are suitable for score data. To describe the sample on variables that produce score data, such as age, number of years of education, and IQ scores, one would normally compute a mean and a variance and standard deviation. Alternatively, one could compute a median or mode as a measure of central tendency and a range as the measure of variability. Links to the computational procedures for each of these statistics are given below.

### Measures of Central Tendency

The most appropriate measure of central tendency for score data is the mean, although both the median and mode could also be used. [Use the back arrow key on the browser to return to the flowchart after learning how to compute these measures of central tendency.]

 Mean Computed Manually Mean Computed with SPSS Median Computed Manually Median Computed with SPSS Mode Computed Manually Mode Computed With SPSS

### Measures of Variability

The most appropriate measures of variability for ordered data are the variance and standard deviation. The standard deviation is the square root of the variance. [Use the back arrow key on the browser to return to the flowchart after learning how to compute these measures of variability.]

 Computing Variability Measures Manually Computing Variability Measures Using SPSS
##### Are there other demographic variables that should be summarized and/or tested? If so, click the RETURN button. Otherwise, Click the PROCEED button.
 RETURN PROCEED