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2/4/2021
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IBM SPSS Amos is a powerful software from IBM for accurate statistical analysis. This software is provided for structural equation modeling (Structural Equation Modeling or SEM for short) which is used to create and examine the relationship between several variables in a model. Using this product, you can evaluate, estimate and predict statistical models and data. Using IBM SPSS Amos, users will be able to design relatively accurate models of standard multivariate statistical techniques, and more accurate models will certainly yield more accurate results.
Using this powerful product will make analyzing complex data models such as attitudinal and behavioral models that reflect complex relationships much easier than before, and researchers and students can access the final results more quickly. Structural equation modeling or SEM is possible in IBM SPSS Amos and you can easily compare or modify different models in this category.
Also, using Bayesian classification algorithms, the various parameters of the model are very accurately improved and estimated. In addition, different methods for assigning data are proposed, which leads to the creation of different datasets for assigning to different models. With its extensive capabilities, this program provides all the necessary facilities for statistical data analysis.
High accuracy in making statistical models and data analysis
Ability to assign data in different ways
Ability to predict the growth or decline of data based on Bayesian algorithms
Two-variable census of data such as correlation tests, distribution tests, t-test and many non-parametric tests
Convenient user interface
High speed in data processing
And
Operating System: Windows XP SP3 / Windows Vista SP2 / Windows 7 SP1 / Windows 8 / Windows 8.1 CPU: Not mentioned RAM: 4 GB (8 GB recommended for x64) HDD: 2 GB
After installation, copy the license file in the Crack folder to the program installation location.
This version was installed on October 20, 1996 in 64-bit Windows 10 and was successfully activated.
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