Descriptive statistic is an information that being used to describe the datasets. there are many type of description being used such as the normality test and also measures of distributions. As for the measures of distribution there is two indicators being highlighted as an important information that must be seen in analysing a datasets.
Skewness
- Is a measure of symmetry, or more precisely the lack of symmetry. A distribution or data set is symmetry if it looks the same to the left and right of the centre point. If the skewness value are close to zero point its indicates that the distribution are symmetrical. While if the values are large and positive, it shows that the distribution is 'positively skewed distribution' and vice versa.
Kurtosis
- Is a measure of whether the data are heavy-tailed or light-tailed relative to be a normal distribution. In kurtosis, the data considered as normal distribution if the value are much closer to zero point. If the value is large and positive the distribution are leptokurtic while if the value is large and negative the distribution indicates as platykurtic.
How to analyze it?
In order to see the value of skewness and kurtosis, it is important to run a descriptive statistics test. Firstly, all you should do is checking for a distribution and normality.
Click on 'Analyze' in the toolbar and click 'Descriptive Statistics' and also 'Descriptive'.
There will be a 'pop-up' of descriptive box, make sure you double click the variable being measured in the test and drag it to the 'Variable(s)' box. As for this example let's assume that the 'AGE OF RESPOND' as the variable to be test. It's followed by clicking the 'Option' button.
In the 'Options' box, click only the 'Kurtosis' and 'Skewness' box as the objective is to find both of it. You might as well click on the 'Variable List'. Then, click 'Continue' before it's back to the 'Descriptive Statistic' box and you can proceed with 'OK'.
The data will be process and you will get one table of 'Descriptive Statistic' with the output. The table will show the measure of distribution and also normality of the data by using skewness and kurtosis to identify it.
It is simple in order for you to understand how to analyze and read the data once you are familiar with the steps. The example of graph above can be used as a guidelines to indicates the normality of the data.
by : Hanis Jefry
References
- https://www.researchgate.net/post/What_is_the_acceptable_range_of_skewness_and_kurtosis_for_normal_distribution_of_data
- http://libguides.library.kent.edu/SPSS/Explore
- http://stats.idre.ucla.edu/spss/output/descriptive-statistics/
- http://www.itl.nist.gov/div898/handbook/eda/section3/eda35b.htm
- https://www.graphpad.com/guides/prism/6/statistics/index.htm?stat_skewness_and_kurtosis.htm
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