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  ▒  ░█▄ ▄█▓   ▓███▌ ░ ·                                                       
     ▄ ■ █▀ ■   ░▀                  SPSS Amos                
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   ·▀▀▄ ■.░▓▓▀  ▄▄▄  │··cracker·│ Team EQUiNOX  │release·date·│ 01 / 2008     :
 ░▓ ░█▌▄█▓▄· ▄▓▓██▓▒ │·supplier·│ Team EQUiNOX  │···OS·type···│ WinALL        :
      ■·▀ ░▄▓▓▓██▓▓▒░│··packer··│ Team EQUiNOX  │·#·of·disks··│ 15 x 4.76MB   :
   ▓█▄  ▄██▓████▓▒▒░ │··tester··│ Team EQUiNOX  │software·type│ Utility       :
    █▌░▐▓██████▓▓▒░  │protection│ Crap          │····rating···│ You decide!   :
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    ■ ▀██▀ ▄       Amos provides you with powerful and easy-to-use structural    
           ▀▀      equation modeling (SEM) software. Create more realistic models
   ·▀ ▒▀  ▓▒       than if you used standard multivariate statistics or multiple 
 ░   ■  ░ ·  ░     regression models alone. Using Amos, you specify, estimate,   
                   assess, and present your model in an intuitive path diagram to
                   show hypothesized relationships among variables. This enables 
                   you to test and confirm the validity of claims such as "value 
                   drives loyalty" in minutes, not hours.                        
                                                                                 
                   Amos enables you to build models that more realistically      
                   reflect complex relationships with the ability to use observed
                   variables such as survey data or latent variables like        
                   ôsatisfactionö to predict any other numeric variable.         
                   Structural equation modeling, sometimes called path analysis, 
                   helps you gain additional insight into causal models and the  
                   strength of variable relationships.                           
                                                                                 
                   You can also impute numerical values for ordered-categorical  
                   data or censored data, so you can create a complete numerical 
                   dataset when one is required. Or, impute values for missing   
                   values in the new dataset. You also have the option of        
                   estimating posterior predictive distributions to determine    
                   probable values for missing or partially missing data in a    
                   latent variable model.                                        
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  ▒  ░█▄ ▄█▓                                                                   
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   ·▀▀▄ ■ ▀█▓▀ ░                                                               
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    ▄   ▀▀  ▐▓░     -check readme.txt in \EQX                                     
   ·▀ ▒▀  ▓▒                                                                      
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·    ░█▄ ▄█▓                                                                   
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  · ▀ ▒▀  ▓▒      We're in great need of new talented people, such as:
·    ■  ░    ░    
 ▒          ·     - Suppliers, can you supply unreleased and new software? 
     ▀   ■  ▀     - Crackers, able to break apps with today's protections?
   ░   ·   ▒      - Shells, host shells on a fast eu/us connection?
                  - Dumps, 100mbit+, with atleast 500Gb of storage?
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░    ░█▄ ▄█▓                                                                   
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    ░█▌▄█▒▄  ░                                                                 
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    ▀ ▒▀  ▓▒                
     ■  ░    ░               
 ·    .     .        BLiZZARD, DFS, DW2K, DYNASTY, ENFUSiA                     
                       
   ·     . ■               MYTH, SSG, TYPO, ViRiLiTY
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   ░     ·  ■ ▄ ■    .                                                         
    ·  ▀   ░   · ▀.■                              /TEAM EQUiNOX               
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     ░█▄ ▄█▓ ▀ ▄▓ ■▓▄                                                          
     ▄ ■ █▀▄▄ ▄██▌▐█▓▌                                                         
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     ■  ░    ░    arfer(DFS)                                                   
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EQUiNOX's keygen for SPSS Amos v16.01