SPSS

SPSS is a computer program used for survey authoring and deployment (IBM SPSS Data Collection), data mining (IBM SPSS Modeler), text analytics, statistical analysis, and collaboration and deployment (batch and automated scoring services).

This software is also referenced in ORMS.


References in zbMATH (referenced in 434 articles , 11 standard articles )

Showing results 1 to 20 of 434.
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  1. Janczyk, Markus; Pfister, Roland: Understanding inference statistics. From A for significance test to Z for confidence interval (2020)
  2. Christine Harvey; R. S. Weigel: Transplant2Mongo: Python Scripts that Insert Organ Procurement and Transplantation Network (OPTN) Data in MongoDB (2019) not zbMATH
  3. Cleff, Thomas: Applied statistics and multivariate data analysis for business and economics. A modern approach using SPSS, Stata, and Excel (2019)
  4. Devaud, Denis; Tillé, Yves: Deville and Särndal’s calibration: revisiting a 25-years-old successful optimization problem (2019)
  5. Jonathon Love; Ravi Selker; Maarten Marsman; Tahira Jamil; Damian Dropmann; Josine Verhagen; Alexander Ly; Quentin Gronau; Martin Šmíra; Sacha Epskamp; Dora Matzke; Anneliese Wild; Patrick Knight; Jeffrey Rouder; Richard Morey; Eric-Jan Wagenmakers: JASP: Graphical Statistical Software for Common Statistical Designs (2019) not zbMATH
  6. Ma, Wenchao: A diagnostic tree model for polytomous responses with multiple strategies (2019)
  7. Noh, Maengseok; Lee, Youngjo; Oud, Johan H. L.; Toharudin, Toni: Hierarchical likelihood approach to non-Gaussian factor analysis (2019)
  8. Rising Odegua: DataSist: A Python-based library for easy data analysis, visualization and modeling (2019) arXiv
  9. Sergio Venturini, Mehmet Mehmetoglu: plssem: A Stata Package for Structural Equation Modeling with Partial Least Squares (2019) not zbMATH
  10. Stockemer, Daniel: Quantitative methods for the social sciences. A practical introduction with examples in SPSS and Stata (2019)
  11. Theodor Balan; Hein Putter: frailtyEM: An R Package for Estimating Semiparametric Shared Frailty Models (2019) not zbMATH
  12. Verma, J. P.; Abdel-Salam, Abdel-Salam G.: Testing statistical assumptions in research (2019)
  13. Weigand, Christoph: Statistics with and without randomness. An application oriented introduction (2019)
  14. Agresti, Alan: An introduction to categorical data analysis (2018)
  15. Al Wadi, S.: Modification of accuracy estimation using stock market data (2018)
  16. Bokhari, Ehsan; Hubert, Lawrence: The lack of cross-validation can lead to inflated results and spurious conclusions: a re-analysis of the MacArthur violence risk assessment study (2018)
  17. Borg, Ingwer; Groenen, Patrick J. F.; Mair, Patrick: Applied multidimensional scaling and unfolding (2018)
  18. Delia Voronca; Mulugeta Gebregziabher; Valerie Durkalski-Mauldin; Lei Liu; Leonard Egede: MTPmle: A SAS Macro and Stata Programs for Marginalized Inference in Semi-Continuous Data (2018) not zbMATH
  19. Duller, Christine: Introduction to nonparametric statistics with SAS, R and SPSS. An application-oriented text and working book (2018)
  20. Elalouf, Hadas; Kaspi, Moshe; Elalouf, Amir; Halachmi, Ilan: Optimal operation policy for a sustainable recirculation aquaculture system for ornamental fish: simulation and response surface methodology (2018)

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