Regression Analysis: The statistical software helps the user understand which among the independent variables are related to the dependent variable and find out more about the forms of such relationships.Bayesian analysis: Built-in Bayesian modeling and inference for generalized linear models, accelerated failure time models, Cox regression models and finite mixture models.Analysis of variance: Features for Balanced and unbalanced designs, Multivariate analysis of variance and repeated measurements and Linear models.What are the Top Free Statistical Software: SAS University Edition, GNU PSPP, Statistical Lab, Develve, Shogun, DataMelt, GNU Octave, SOFA Statistics, Dataplot, SciPy, Zelig, Scilab, Gretl, OpenStat, Past, MacAnova, MaxStat Lite version, SageMath, Epi Info, NIMBLE, Arc, ADaMSoft, CumFreq, OpenMx, Salstat, Statcato, Stan, IDAMS, OpenEpi, BV4.1, pbdR, GNU Data Language, Dap, Simfit, First Bayes, MicrOsiris, Ploticus, NCAR Command Language, Perl Data Language, Yorick, EasyReg, IVEware, ViSta, StatCVS, WinBUGS, JAGS, WINPEPI, ADMB are some of the top free statistical analysis software. Statistics also helps the managers forecast as well as make correct predictions about what could occur to the industry in future.īusiness statistics also plays a massive role in measuring the financial position of the company. Business statistics help them discover patterns and trends of customers and other useful information that help them make decisions.īusiness statistics also help businesses managers measure the performance of the workers as well as improve the products and services produced.
In a world full of uncertainty, business statistics play a significant role in business and helps managers make an informed decision in disciplines such as quality assurance, production, and operations, financial analysis, auditing and econometrics among others.īusiness managers need to collect, analyze and make inferences from a vast amount of data. Statistical software are programs which are used for the statistical analysis of the collection, organization, analysis, interpretation and presentation of data.
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