Data coding is of paramount importance if a proper analysis of this data is to be carried out. In particular, data coding plays a critical role when it is needed to use statistical software in order to process the data. Because of this, it is crucial to properly code the data which is to be entered into IBM SPSS.

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In particular, it is necessary to use the ways of coding information which can be recognized by the statistical software. Any user of SPSS should be aware of the fact that this package is not capable of telling apart the pieces of data which are entered in different styles. That is, SPSS will not differentiate between symbols written in italics, those which are bold, or those which are underlined; it will also not tell the difference between symbols written in different fonts, colors, and so on. Therefore, the symbols 2, 2, 2, *2*, 2, 2, 2, 2, 2, etc. will be read by the package as the same symbol 2. Thus, it is necessary to employ symbolically different units for coding if SPSS is to differentiate the data properly (George & Mallery, 2016).

It is also noteworthy that SPSS will differentiate between capital and lowercase letters (for instance, A and a), but employing such coding might be confusing for the user, which is why the use of numbers is advised. In addition, the SPSS will work better with numerical than with alphanumerical data; for instance, it is possible to calculate statistics (the mean, standard deviation, etc.) and run tests for a variable measured in Likert scale if it is coded using numbers, but it is impossible to do so if letters are employed for coding (Field, 2013).

Therefore, it is recommended to utilize numbers for coding variables, for this type of data will not be confused by the user, and will be properly processed by the statistical software.

## References

Field, A. (2013). *Discovering statistics using IBM SPSS statistics *(4th ed.). Thousand Oaks, CA: Sage Publications.

George, D., & Mallery, P. (2016). *IBM SPSS Statistics 23 step by step: A simple guide and reference* (14th ed.). New York, NY: Routledge.