IBM SPSS Amos / SPSS Statistics 24 Multilingual

IBM® SPSS® Amos gives you the power to easily perform structural equation modeling to build models with more accuracy than with standard multivariate statistics techniques. With SPSS Amos, you can specify, estimate, assess, and present your model in an intuitive interface to show hypothesized relationships among variables.

IBM SPSS Amos makes structural equation modeling (SEM) easy and accessible
IBM SPSS Amos builds models that more realistically reflect complex relationships because any numeric variable, whether observed (such as non-experimental data from a survey) or latent (such as satisfaction and loyalty) can be used to predict any other numeric variable.

Its rich, visual framework lets you to easily compare, confirm and refine models.
Quickly build graphical models using IBM SPSS Amos’ simple drag-and-drop drawing tools. Models that used to take days to create are just minutes away from completion. And once the model is finished, simply click your mouse and assess your model’s fit. Then make any modifications and print a presentation-quality graphic of your final model.

A non-graphical, programmatic approach, introduced with SPSS Amos 20, improves accessibility for those who can benefit by specifying models directly. Its scripting capabilities improve the productivity of users who need to run large, complicated models, and make it easy to generate many similar models that differ slightly.

Its approach to multivariate analysis encompasses and extends standard methods – including regression, factor analysis, correlation and analysis of variance. New capabilities include bootstrapping of user-defined functions of the model parameter for increased model stability.

Obtain Bayesian estimates of model parameters and other quantities
Bayesian analysis enables you to apply your subject-area expertise or business insight to improve estimates by specifying an informative prior distribution. Markov chain Monte Carlo (MCMC) is the underlying computational method for Bayesian estimation. The MCMC algorithm is fast and the MCMC tuning parameter can be adjusted automatically.
Perform estimation with ordered categorical and censored data Create a model based on non-numerical data without having to assign numerical scores to the data. Or work with censored data without having to make assumptions other than the assumption of normality. You can also impute numerical values for ordered-categorical and censored data. The resulting dataset can be used as input to programs that require complete numerical data.

Impute missing values or latent variable scores
Choose from three data imputation methods: regression, stochastic regression, or Bayesian. Use regression imputation to create a single completed dataset. Use stochastic regression imputation or Bayesian imputation to create multiple imputed datasets. You can also impute missing values or latent variable scores.

IBM SPSS Statistics :
Solve difficult business and research challenges with data analysis. IBM SPSS Statistics is an integrated family of products that helps to address the entire analytical process, from planning and data collection to analysis, reporting and deployment. With more than a dozen fully integrated modules to choose from, you can find the specialized capabilities you need to increase revenue, outperform competitors and make better decisions.

Analytics plays an increasingly important role in helping your organization achieve its objectives. The IBM SPSS Statistics family delivers the core capabilities needed for end-to-end analytics. To ensure that the most advanced techniques are available to a broader group of analysts and business users, we have made enhancements to the features and capabilities of IBM SPSS Statistics Base and its many specialized modules.

IBM SPSS Statistics Features:
SPSS Statistics is loaded with powerful analytic techniques and time-saving capabilities to help you quickly and easily find new insights in your data.
Here's a look at the newest features and enhancements designed to help you:
Gain deeper predictive insights from large and complex datasets.
Reveal relationships and trends hidden in geospatial data.
Speed deployment and return on investment.

IBM SPSS Statistics 24 continues to offer advanced analytics through new data analysis techniques, enhanced features and output, and improved accessibility. This release focuses on increasing the analytic capabilities of the software through:
- Extending the value of big data — Uncover hidden causal relationships among large numbers of time series using temporal causal modeling.
- Geospatial analytics — Explore the relationship between data elements that can be tied to a location to gain deeper insights.
- Embedding analytics into the enterprise — Apply the next generation of web reports, R programmability enhancements and improved accessibility.

IBM Business Analytics software delivers complete, consistent and accurate information that decision-makers trust to improve business performance. A comprehensive portfolio of business intelligence, predictive analytics, financial performance and strategy management, and analytic applications provides clear, immediate and actionable insights into current performance and the ability to predict future outcomes. Combined with rich industry solutions, proven practices and professional services, organizations of every size can drive the highest productivity, confidently automate decisions and deliver better results

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IBM SPSS Amos 24 Multilingual-RECOiL | 163.16 MB
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IBM SPSS Statistics 24(x86/x64) Multilingual-RECOiL

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