Obtaining probabilities in SPSS.

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Title: Obtaining probabilities in SPSS.
Authors: Eisenhauer, Joseph G.1 (AUTHOR) eisenhjg@udmercy.edu
Source: Teaching Statistics. Summer2026, Vol. 48 Issue 2, p146-151. 6p.
Subject Terms: Logistic regression analysis, Probability theory, Approximation error, Statistical software
Reviews & Products: SPSS (Computer software)
Abstract: A recent article in this journal presented an approximation procedure for obtaining probabilities from logistic regression when using IBM SPSS Statistics. The present note provides a more direct approach with the same software. [ABSTRACT FROM AUTHOR]
Copyright of Teaching Statistics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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PubType: Academic Journal
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  Data: Obtaining probabilities in SPSS.
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  Data: A recent article in this journal presented an approximation procedure for obtaining probabilities from logistic regression when using IBM SPSS Statistics. The present note provides a more direct approach with the same software. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Teaching Statistics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1111/test.70023
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        Text: English
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        PageCount: 6
        StartPage: 146
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      – SubjectFull: Logistic regression analysis
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      – SubjectFull: Probability theory
        Type: general
      – SubjectFull: Approximation error
        Type: general
      – SubjectFull: Statistical software
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              Text: Summer2026
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              Y: 2026
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