How SPSS Better than STATA, R, SAS?

Introduction

SPSS is a short-form for Statistical Package for Social Science. It is software that was developed in 1968 by IBM. STATA is a general-purpose tool for statistical analysis. STATA corp developed it in 1985. Through this article, it is possible to compare and contrast SPSS, STATA, R and SAS for identifying a better system of data analysis.

SPSS and STATA

On the other hand, the operating system supported by STATA is Windows, Linux and Mac OS. SPSS is suitable for complex data analysis, where STATA cannot be suitable for modelling complex data and information. SPSS is utilising in medical and social science areas, and on the other hand, STATA is utilised mostly for the econometrics. STATA is basically a normal analysis procedure, whereas SPSS is used to perform multi variant analysis procedure for the large amount of data and information. Hence, it can be stated that, SPSS is more useful as compared to STATA in the statically field and also in the business analysis and research context. Though STATA has command line and documentation features which is highly useful, SPSS can directly generate the output into the reports, which will be beneficial for the researcher to draw final conclusion after in-depth analysis and evaluation. SPSS is mainly utilised for the complex data management by using excel spread sheet, where STATA is useful or cutting edge research and ideal for the developers and researchers. For statistical analysis, SPSS is stronger in these areas as compared to the STATA which is relatively weak. SPSS is also useful for improving agile development life cycle, and thus SPSS is considered as stronger system for data analysis and evaluation as compared to STATA and SPSS is utilised in diverse field to analyse the complex data and information.

R and SPSS

R and SPSS are the major two industry-leading technologies for the statistical data analysis. SPSS is known as Statistical Package for the social science owned by IBM and on the other hand, R is an open-source programming language, which is widely utilised as the preferred option for analytics. R is mainly the scripting language that supports limited Graphical User Interface features as compared to IBM SPSS which has built-in features for quality data processing and analysis. SPSS data analysis is fully handled by IBM for supporting the data analysis and also for features enhancement, whereas R has several package supported from the community user. R is known for its customization visualization support, whereas SPSS is limited with the visualisation features. For most of the business analytics and other researcher, SPSS is utilised highly in order to its simplicity and direct reporting after critical data analysis. For decision making practice, SPSS is considered as better than R, because R does not offer many tree algorithms. In this context, for making rationale decision, the tree algorithms are mandatory where the decision trees under SPSS is very user friendly and understandable for making good decision. Hence, it can be considered that, SPSS is better than R for the business and research purpose to make rationale decision. The data management and handling the data in a synchronised way is good in SPSS as compared to R, where the data management functions under SPSS such as sorting, aggregation, transposition and merging the tables are useful to handle the huge range of data set successfully. Under SPSS, the graphical super interface is written in Java and it is utilised for interactive and statistical analysis mainly. On the other hand, R is written in the different language including C and FORTRAN as well as R is considered as stronger object-oriented programming than SPSS. R has a less interactive analytical tool than SPSS for which SPSS is utilised widely to handle diverse data set and develop multivariate statistical model for further data analysis and evaluation.

SPSS and SAS

In the recent technological advancement, both SPSS and SAS are tools that help statistical analysis easier and it further give us value and help us predict and provide data trends. SPSS software system is also utilised for diverse statistical analysis where it is an abbreviation for the statistical package for the social science. It is utilised in diverse field including market research, health and social care researches education, marketing orientations, data miners and others, and hence social science can be conducted with critical data analysis and evaluation. On the other hand, SAS is mainly a programming language that is developed for the advanced analytics of the business intelligence, data management and reductive analysis, where it stands for Statistical Analysis System. SPSS is utilised for the non-technicians and statisticians also, where to utilise SAS, programming language is required. SPSS plays a crucial role in social science and it helps the individuals to conduct in-depth research on diverse field. For predictive analysis, SAS can be useful, but SPSS is successful to propose final decision after data analysis and evaluation through reporting, where multivariate analysis can be conducted effectively. SPSS has an easy interface where the users do not need to learn coding and it has paste functions that creates syntax for steps executed in the user interface as well as graphical representations are also useful under SPSS to represent the data and evaluate the final report easily. Good interface, data management and complete documentations are the major advantages of SPSS, for which many university, researchers and decision makers utilise SPSS for analysing multivariate model to under regression and correlation for developing final rationale decision.

Summary

Hence, it can be stated that, SPSS is better than other programs such as STATA, R and SAS, where it is easier for the users to utilise SPSS and represent the data efficiently through excel spread sheet. The multivariate model and final, reporting and documentation under SPSS further male it useful for the users to analyse the data and develop final report successfully. For social science and conducting diverse researchers, the users prefer to utilise SPSS Expert for better outcome and analysing vast range of data in a synchronise way to create the best decision.