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Compressions Type: Winrar (rar files: 4 x100 mbx, 1 x 69 mbs, Patch 1 x77 mbs)
Language: English
Format: ISO
O/S: Windows
Official Release: Basic with Advanced and with Amos 7...
Reference: Read attached Install.txt first
Keygen: In Keygen Folder
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SPSS for Windows provides you with a broad range of capabilities for the entire analytical process. With SPSS, you can generate decision-making information quickly using powerful statistics, understand and effectively present your results with high-quality tabular and graphical output, and share your results with others using a variety of reporting methods, including secure Web publishing. Results from your data analysis enable you to make smarter decisions more quickly by uncovering key facts, patterns, and trends. An optional server version delivers enterprise-strength scalability, additional tools, security, and enhanced performance.
You can use SPSS for Windows in a variety of areas, including:
· Survey and market research and direct marketing
· Academia
· Administrative research, human resources, and resource planning
· Medical, scientific, clinical, and social science research
· Planning and forecasting
· Quality improvement
· Reporting and ad hoc decision making
· Enterprise-level analytic application development
In particular, apply SPSS statistics software to gain greater insight into the actions, attributes, and attitudes of people——your customers, employees, students, or citizens.
SPSS Amos v7.0
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 "satisfaction" 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.