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- System Requirements
- License
- full key activtae
- OS
- Windows 10,8.1,7,Vista
- Version
- 21
- File Size
- 1,014 GM RAR x 64, 992 MB RAR x 32
- Developer
- 27/7/2017
Click Here x 64
Click Here x 32
IBM SPSS Statistics 21 Student Version
The IBM® SPSS® Statistics 21 Student Version is a limited but still powerful version of SPSS
Statistics.
Capability
The Student Version contains many of the important data analysis tools contained in IBM®
SPSS® Statistics, including:
Ibm Spss Statistics 22 Serial Number
- Spreadsheet-like Data Editor for entering, modifying, and viewing data files.
- Statistical procedures, including t tests, analysis of variance, and crosstabulations.
- Interactive graphics that allow you to change or add chart elements and variables dynamically;
the changes appear as soon as they are specified. - Standard high-resolution graphics for an extensive array of analytical and presentation charts
and tables.
Limitations
Created for classroom instruction, the Student Version is limited to use by students and instructors
for educational purposes only. The following limitations apply to the IBM® SPSS® Statistics 21
Student Version:
- Data files cannot contain more than 50 variables.
- Data files cannot contain more than 1,500 cases. SPSS Statistics add-on modules (such as
Regression or Advanced Statistics) cannot be used with the Student Version. - SPSS Statistics command syntax is not available to the user. This means that it is not possible
to repeat an analysis by saving a series of commands in a syntax or “job” file, as can be done
in the full version of IBM® SPSS® Statistics. - Scripting and automation are not available to the user. This means that you cannot create
scripts that automate tasks that you repeat often, as can be done in the full version of SPSS
Statistics.
Abstract
IBM SPSS Statistics V21.0 helps improve decision making and productivity through simulation modeling and augmented integration with other tools
Content
Spss 22 Serial
IBM SPSS Statistics 21.0 focuses on increasing the analytic capabilities through:
- Building better models from uncertain inputs while assessing risk using Monte Carlo simulation techniques
- Providing faster performance with more accurate results, increased productivity and effectiveness using a range of specialized techniques
- Integrating with other technologies and tools making it easy to access common data types, external programming languages, and file types