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There are a few reviews of free statistical software. There were two reviews in journals (but not peer reviewed), one by Zhu and Kuljaca [26] and another article by Grant that included mainly a brief review of R. [27] Zhu and Kuljaca outlined some useful characteristics of software, such as ease of use, having a number of statistical procedures and ability to develop new procedures.
JASP (Jeffreys’s Amazing Statistics Program [2]) is a free and open-source program for statistical analysis supported by the University of Amsterdam. It is designed to be easy to use, and familiar to users of SPSS. It offers standard analysis procedures in both their classical and Bayesian form.
gretl is an example of an open-source statistical package. ADaMSoft – a generalized statistical software with data mining algorithms and methods for data management; ADMB – a software suite for non-linear statistical modeling based on C++ which uses automatic differentiation; Chronux – for neurobiological time series data; DAP – free ...
Free Bayesian statistics software (9 P) E. Free econometrics software (3 P) F. Free R (programming language) software (24 P) P. Free plotting software (30 P) W.
Ooms, Marius (2009). "Trends in Applied Econometrics Software Development 1985–2008: An Analysis of Journal of Applied Econometrics Research Articles, Software Reviews, Data and Code". Palgrave Handbook of Econometrics. Vol. 2: Applied Econometrics. Palgrave Macmillan. pp. 1321– 1348. ISBN 978-1-4039-1800-0. Renfro, Charles G. (2004).
OpenEpi is a free, web-based, open source, operating system-independent series of programs for use in epidemiology, biostatistics, public health, and medicine, providing a number of epidemiologic and statistical tools for summary data.
The Statistics Online Computational Resource (SOCR) [1] is an online multi-institutional research and education organization. SOCR designs, validates and broadly shares a suite of online tools for statistical computing, and interactive materials for hands-on learning and teaching concepts in data science, statistical analysis and probability theory.
The ASEBA was created by Thomas Achenbach in 1966 as a response to the Diagnostic and Statistical Manual of Mental Disorders (DSM-I). [3] This first edition of the DSM contained information on only 60 disorders; the only two childhood disorders considered were Adjustment Reaction of Childhood and Schizophrenic Reaction, Childhood Type.