Data pattern

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I have a question about data pattern. Normally we assume that data will be distributed normally but many times it could not be happened. Is their any theory which describe the various kind of data pattern?

1 comment to Data pattern

• Jack

Very nice question. It is true that if you can draw sample properly, the character of data will be distributed normally. But you can see other types of distribution in your SPSS research.

However, the pattern of data can be clearly identified by graphical display and there are mainly four kinds of pattern such as center, spread, shape and unusual features. On the other hand, you can find some other distribution like as symmetric, bell-shaped, skewed etc.

Center: In this distribution, median of the data will be found in the center of the distribution.

Spread: If the data range is high in your SPSS research, you will find a spread distribution or pattern.

Shape: Four kinds of data pattern are found under shape pattern such as symmetry, modal, skewness and uniform. In symmetry, data is patterned in a way that you will always find a mirror image of the other side. On the other hand, if you find the data with one peak, you will find unimodal pattern, if more than one peak is found, bimodal distribution or patter will be found in SPSS research. If the peak is placed in central, bell-shaped distribution will be found. In skewness, distribution is found with the peak in only one side. If the observations found in the left, then it will be skewed left and for right, it will be called as skewed right. And lastly, if the data without any variation, uniform model will be found.

Unusual: There are mainly two common unusual pattern found in SPSS research such as Gaps and Outliers. If you do not find any observation in the middle of the distribution, then it is called as Gaps. On the contrary, if you find some extreme value, you will find an outlier pattern. Sometimes SPSS researchers delete the outliers to get normally distributed data set.