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IBM SPSS Statistics
Was ist IBM SPSS Statistics?
Dein Unternehmen hat mehr Daten als je zuvor, aber Kalkulationstabellen und grundlegende statistische Analysewerkzeuge schränken seine Nützlichkeit ein? Mithilfe der IBM SPSS Statistics-Software kannst Du neue Beziehungen in den Daten finden und vorhersagen, was als nächstes passieren wird. Sieh dir das kostenlose Demo-Video von IBM an, um zu lernen, wie du einfach auf Datensätze zugreifen, diese verwalten und analysieren kannst - ohne vorherige statistische Erfahrung. Eliminiere praktisch jede zeitaufwändige Datenvorbereitung und erstelle schnell, manipuliere und verteile Erkenntnisse für die Entscheidungsfindung.
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IBM SPSS Statistics
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Bewertungen über IBM SPSS Statistics
IBM SPSS TOOL : A great statistical tool for all statisticians and scholars to have
In Betracht gezogene Alternativen:
Easy to use Statistical analysis software
Kommentare: Overall, using SPSS with other statistical software like SAS JMP and Excel provides great value. The software is great but surely there is room for improvement
Vorteile:
I Return to mostly because of its data cleaning capability and the ability to save chart templates and reuse. It is flexible for basic statistical analysis though requires an good statistical background to perform sophisticated statistical analysis with it.
Nachteile:
The fact that the software has no algorithms that can help you decide on the right statistical test seems problematic to novices in statistical data analysis. You must know the exact test to perform, the software cannot help you decide
Spss statistics software
Kommentare: The first contact with the software as at the level of the University. Collecting data 'to draft the report, I've been introduced to a person handling SPSS stat. I there for took contact with the software to do some minimum Data introduction, Data cleaning end grafting some results.
Vorteile:
Used in both academic and professional purpose Good quality of data monitoring and cleaning. The ceriousness of the tool mekes it usage very cellective and precoded
Nachteile:
The ease of use: to handle the software we should follow a minimum hours of training cession
Researcher's opinion about SPSS
Kommentare: Since my training, I have used other software packages (JASP, R, Stata), and although I would mostly pick those over SPSS, I would still heartily recommend this software package to others. Especially to people who are less experienced with statistical reporting.
Vorteile:
I learnt statistics using SPSS, and for that it will always be a product that has personal significance for me. It is very user friendly and the UI and ribbon, although dated, allows inexperienced users to quickly understand and navigate its functionality. For simple statistical operations, SPSS is great.
Nachteile:
For statisticians who are more experienced, SPSS will likely feel sluggish. It does not have the kind of customisation that other packages or programming languages have, e.g. R, and it can feel slow.
In Betracht gezogene Alternativen:
Good program to educate.
Kommentare: It is a very powerful software, which is very good to use it in educational centers for students. It has a good price, so it is a good option for independent statistical studies.
Vorteile:
It has a simple and uncomplicated platform when learning to use it. It handles terms that were handled at my university and data can be exported from Excel.
Nachteile:
Visually it leaves a lot to be desired, as in its graphics and its graphics edits are very slow. It should be more compatible with Micrsoft programs.
SPSS for Strong Stellar Statistical Analyses that tell Stories
Kommentare: Elated with product. Began simply using it for market research and surveys but now will run through it given its ease of use with all sorts of analyses and data.
Vorteile:
The massiveness and extent of value it can unravel from data in processes that are "easy", intuitive, and "make sense". LOVE using product for complexly designed survey analyses - they are lots of fun
Nachteile:
I like least that not everybody uses the software and thus miss out on these collaborative discovery sessions that leave all participants with a firmer grasp on what data story telling REALLY is
