Introduction
Statistical package for social science or SPSS is the data analysis software that is used for carrying out deep research as well as complex data analysis. It is a very useful data analysis tool that is used in terms of carrying out the statistical calculation and determining the difference between the different variables both dependent and independent. Many types of research agencies from around the globe use the SPSS to analyse the survey and the data. The SPSS data analysis is highly useful in utilising the diverse data sets as well as conducting different statistical analyses such as ANOVA, MANOVA and T-test. The SPSS data analysis also uses regression analysis in terms of analysing the diverse data set and determining the interrelation between the independent and the dependent variables.
- The SPSS data analysis carries out the in-depth critical evaluation of the statistical and theoretical database. The SPSS data analysis is strongly associated with determining how different variables impact the characters and the features of the other variables. Moreover, the SPSS data analysis uses revenant graphs, tables and charts such as bar and pie charts to present the data by using reliable variables and cases. Variables of any data presentation are the columns in which the dataset is presented. The rows of each data set presentation are termed as the cases.
- The major advantage of SPSS data analysis is that it helps the students to carry out the data evaluation in which not much effort is required to access this software. This software is highly user-friendly and assists students in understanding the process of using the SPSS data analysis tools and techniques in different data analysis processes. Most of the time, the SPSS data analysis is used for carrying out two types of data analysis such as qualitative and quantitative data. In the case of the quantitative data, the independent and dependent variables are calculated and compared by using the SPSS data analysis to determine the standard deviation and the compared values of these variables.
- Moreover, the SPSS data analysis assist students in using the graphs and charts to present the percentage of the database thereby presenting the percentage of the proportion and probability values of the variables. In the case of the quantitative data analysis, the SPSS data analysis uses the Likert scale in which there are four different types of variance levels such as strongly agree to strongly disagree. In this context, while carrying out the quantitative data analysis, the SPSS software is used to present the database in the table and then [resent the proportion and the percentage in the pie and the bar chart. The SPSS data analysis takes less time than that of the other data analysing software or tools.
- Especially in the case of carrying out the qualitative and quantitative data analysis, the time that is required for the data presentation and determination of the SD values and the means is less than the other tools. The data analysis with spss is a very reliable method that enables students to carry out the most convenient process of data evaluation by using time-saving and modernised tools such as the visualising designer, survey program, modeller programming and statistical programming. These data analysing tools and software are used while data analysis with spss is conducted in terms of improving the process of data analysis. The data analysis with spss allows students to carry out the systematic and in-depth evaluation of the dataset by conducting different processes such as data mining, data transformation and data presentation.
- The data analysis with spss is highly useful in carrying out qualitative data analysis, in which it analyses the source from which the data is securely collected thereby analysing the common differences and similarities among the different variables. The data analysis with spss is used to analyse, reduce and interpret the different forms of the qualitative dataset thereby analysing whether these databases present the same mean and the SD between the different variables. In terms of carrying out both the quantitative and the qualitative data analysis, the data analysis with spss uses the data transformation process to transform the database into the most suitable and convenient form that can easily be understood by the human. The data analysis with spss allows the researcher as well as students to carry out the critical evolution of the complex dataset thereby presenting the conclusion.
- Another most important type of data analysis is the regression analysis which the data analysis with spss is done. The regression analysis is the major part of the data analysis with spss. In this process, the SPSS software stores the data in a synchronised way to present a clear relationship between the dependent and independent variables. In this regressing analysis, the data analysis with spss uses the ANOVA and MANOVA tools in terms of determining the interconnection between the different variables and the influence of one variable on the other variable. Moreover, the MANOVA and the ANOVA are the most two useful process tools that the data analysis with spss uses in terms of carrying out the in-depth evaluation of the differences between the SD and the mean values of the different independent and dependent variables.
Conclusion
However, although the entire SPSS usage is very reliable and convenient, many students face issues in using this software appropriately. In this context, they can receive help with spss analysis tools that can assist them in knowing the SPSS clearly and getting a clear idea of this software. The data analysis with spss assists students to know the types of data collection that are carried out by the SPSS. The data analysis with spss is also useful in terms of analysing the systematic process and tools that SPSS software uses to carry out the critical data analysis and the data comparison. The data analysis with spss is also a high level of useful process in terms of preparing the data table and thereby assisting them in dealing with the values of the database.