SPSS as a Tool for Scientific Analysis in the Field of Social Science

 

IBM Statistical Package for Social Science or SPSS as we call it in short it is the most widely used statistical analysis software that is used by social scientists around the world. Its inception goes back to more than five decades ago by Norman H. Nye, a social scientist, along with two of his colleagues, Dale H. Bent and C. Hadleigh Hull in the year 1968 with the aid from Stanford University. Over the years, it has undergone many updates to accommodate the research requirements of the social scientists.

Quantitative date analysis not just needs accuracy in data analysis but also effective data representation. The creators of SPSS have ensured to accommodate these needs and make the software not just feature-rich but also user friendly.

The field of Social Sciences is data driven and researchers are required to deal with large amount of data which is from online as well as offline surveys, interviews or observations. The biggest advantage that SPSS offers to social sciences researchers is that it has been so designed to handle an extensive data set with many variables along with the scope for graphical representation as well as multiple analysis of data.

Unique Features of SPSS

  • The most useful and unique feature of SPSS is that it has been developed for people with no technical background and knowledge of programming language. This is usually the case with social sciences researchers. This makes the software extremely user friendly and ready to be used for any kind of quantitative analysis.

  • The report generating and data management capabilities of SPSS are humungous and this makes the software the top choice for the researchers worldwide.

  • SPSS requires the researcher to define the variables at the time of doing data input. The SPSS data sheet, primarily has four kinds of variables, namely, independent, dependent, intermediate and moderating. For a novice in research, the independent variable is the cause variable and independent of the other variables in the study. The second kind of variable is the dependent variable which is the effect variable and its value changes with any change in the independent variable. The case of an intermediate variable which can also be named as the mediating variable refers to a hypothetical variable typically used within research to explain causal links between other variables. The last comes the moderating variable that change the association between the independent and dependent variables. Before using SPSS, it is imperative for a researcher to identify these variables in their data set and know the implications.

To conclude, we can say that it is the fastest tool available that can handle data manipulation and statistical procedures as compared to other non-statistical programs, And the cherry on the cake is that SPSS is not just dependable for statistical analysis but also data management and documentation. This undoubtedly makes it the most vital and at the same time, influential tool for quantitative data analysis in social sciences.


 

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