Top Statistical Tools You Need to Make Your Data Shine

Introduction

In the globalisation era, researchers and entrepreneurs use the best statistical software for data analysis, predicting the future and identifying risks and upcoming business opportunities. It is important for the business to choose the best statistical tools in order to make the data effective for the business, where the experts can analyse the data and develop report for further strategic planning. Through this article, it is possible to demonstrate different statistical tools, through which the researchers can conduct social science research by inclusion of statistical data and information. The major statistical tools are such as SPSS, STATA, R, Survey Development and Analysis through which it would be possible to conduct social science research and gather vast range of data and information for in depth analysis.

Statistical Softwares

SPSS

SPSS is an IBM product that is used for quantitative data analysis, where the statistical and mainly numeric data are included for critical analysis. With the help of Microsoft excel, the researchers try to include the vast range of data in the system for better data mining and representation. It is very quick and easy to learn as well as it can handle large amount of data with great user interface. Though there are some disadvantages of using SPSS such as expensive, limited functionality and very similar to excel, the researchers are utilising the SPSS software widely in order to ensure data mining and conduct in depth critical analysis for further future prediction. The report format of SPSS with graphical representation is also beneficial for the users to understand the data and analyse the final report successfully. SPSS has several features like statistical operations, charting, forecasting and others. These features are beneficial for data analysts as they have to perform a critical analysis of a vast range of data. SPSS has advanced features including robust and standard error handling, random effects with solution results, and profile plots with error bars.

STATA

STATA is mainly utilised for normal analysis, not for complex and critical data analysis. It is mainly utilised in econometrics, where the economists and researchers try to conduct economic data analysis and future predications. The program has command lien and good documentation features which are useful for the users to understand the report after data analysis. STATA has different add-on packages including Spatial AR models, latent class analysis, markdown, finite mixture models, threshold regression, nonlinear multi-level models etc. STATA discovers and understands the unobserved data groups on the basis of Latent Class Analysis.

R

R and its graphical user interface companion R Studio are incredibly popular software as it is free open source software with strong online user community. It is programmable with more functions and it is also widely utilised for data analysis. It has the same features as STATA such as a command line, a point-and-click user interface, salvable files and strong data analysis and visualization capabilities. The technical experts can program the new functions with R to use it for different types of data and projects. Hence, diverse data range with different domain can be stored in the system for critical analysis. The decision tree does not offer many algorithms with different packages of R. it is also available for providing GUI supports for the R programming. The technical experts are efficient to utilise the programming software for analysing vast range of data so that the data can be utilised proficiently for developing final report.

Method To Represent

Survey Development and Analysis

Survey development and analysis is also another main method where the researchers try to represent the survey data in the SPSS software, where the data mining and sorting the information can be conducted proficiently. The non-technical head of the organisations can also utilise SPSS as it is easier as compared to other statistical tools, where the data analysts and researchers can evaluate the findings from the survey. For primary and secondary data analysis and developing final report, the survey data analytics through SPSS is hereby beneficial for the researchers to utilise the gathered data and information and make it useful by utilising it for decision making behaviour. The researchers try to conduct survey in order to gather vast range of data and information directly from the participants so that the actual data set can be collected. In this context, choosing the statistical tool is important for data mining and sorting, so that the diverse range of data and information can be analysed through different features of SPSS including regression model, correlation, mean, median and mode functions as well as T test and ANOVA.

Summary

It can be stated that, the researchers and scientists use SPSS widely where the latest version executes new Bayesian Statistics functions containing regression, t-tests and ANOVA. Interrelation of the data and information by correlation and regression can also be performed well in order to analyse the diverse range of data efficiently. SPSS can make these things easier by creating publication standard charts with formal report representation. Hence, as compared to STATA and R, SPSS is very useful for the researchers to perform data analysis and survey analysis efficiently in order to make data effective and create final report successfully. SPSS provides the scope of editing, writing and formatting the syntaxes with editor shortcut tools with a simple keyboard shortcut to join duplicate lines, delete lines and new lines, to move lines up and down, to remove empty lines and to trim trailing or leading spaces effectively. These are effective features of SPSS, through which the data analytics can be easier to handle and it would also be beneficial for the researchers to make the data effective for developing the final reports after critical evaluation and data analysis