Abstract
In study of the statistical packages, simulation from probability distributions is one of the important aspects. This paper is based on simulation study from Bernoulli distribution conducted by various popular statistical packages like R, SAS, Minitab, MS Excel and PASW. The accuracy of generated random data is tested through Chi-Square goodness of fit test. This simulation study based on 8685000 random numbers and 27000 tests of significance shows that ability to simulate random data from Bernoulli distribution is best in SAS and is closely followed by R Language, while Minitab showed the worst performance among compared packages.
Highlights
Use of Statistical software is increasing day by day in scientific research, market surveys and educational research
This study focuses a comparison of random data generation from Bernoulli distribution among five softwares R, Statistical Analysis System (SAS), Minitab, MS Excel and Predictive Analytical Software (PASW) (Formerly SPSS)
In this paper R 2.11.1, SAS 9.1.3, Minitab 15, MS Excel 2007 and PASW 18 are explored in term of their accuracy of generating random data from Bernoulli distribution
Summary
Use of Statistical software is increasing day by day in scientific research, market surveys and educational research. This study focuses a comparison of random data generation from Bernoulli distribution among five softwares R, SAS, Minitab, MS Excel and PASW (Formerly SPSS). In this paper R 2.11.1, SAS 9.1.3, Minitab 15, MS Excel 2007 and PASW 18 are explored in term of their accuracy of generating random data from Bernoulli distribution. Following steps are used for comparison (i) Random samples are generated for different sizes (n=30, 50, 100, 250, 500 and 1000), for different values of the parameter p in range of 0.1(0.1)0.9 form the Bernoulli distribution using above mentioned softwares. (iv) Chi-Square goodness of fit test is conducted for a given sample size and a given value of p for each package, and number of poor fits are recorded in hundred replications (iii) The procedure is replicated one hundred times. (iv) Chi-Square goodness of fit test is conducted for a given sample size and a given value of p for each package, and number of poor fits are recorded in hundred replications
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Pakistan Journal of Statistics and Operation Research
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
