Statistical discrete and continuaous Probability Distribution table re-producing using R

Nur Hazeema Abdul Rahman

QR Code Link :
Type :	final_year_project
Subject :	QA Mathematics
Main Author :	Nur Hazeema Abdul Rahman
Title :	Statistical discrete and continuaous Probability Distribution table re-producing using R

Place of Production :	Tanjong Malim
Publisher :	Fakulti Sains dan Matematik
Year of Publication :	2023
Corporate Name :	Universiti Pendidikan Sultan Idris
PDF Guest :	Click to view PDF file

Abstract : Universiti Pendidikan Sultan Idris

The aim of this research is to implement the statistical software which is R, in one of the Elementary Statistics topics called Probability Distribution. This study has explored the use of R and figured out that R is one of the statistical software that has its own utility to allow R user to create the function. Regarding to the objectives, R software is implemented in the topic of Probability Distribution which is Binomial distribution, Poisson distribution and Normal distribution. The researcher has been asked to explore R software and create as well as apply new functions. These functions are applied in R to produce Binomial distribution table, Poisson distribution table and Standard Normal Distribution table. The finding shows that these probability distribution tables can be produced using created functions where it shows the similar values when it compared to the actual tables of Binomial, Poisson and Standard Normal distribution. It can be clarified that the researcher managed to create functions with regard to reproduce these probability distribution tables by using R software. This research can be the usage to the other researcher or readers where they can learn on how to use R software since it is easy to learn and it does not require high programming skills. For the future research, it can be extended where other distribution tables can be produced by creating own functions in R software.

References

Alto, V. (2019, August 19). Understanding Bernouli and Binomial Distributions. Towards Data Science. https://towardsdatascience.com/understanding-bernoulli-andbinomial-distributions-a1eef4e0da8f

Barone, A. (2022, November 22). Binomial Distribution: Definition, Formula, Analysis and Example. Investopedia. https://www.investopedia.com/terms/b/binomialdistribution.asp#:~:text=Binomial %20distribution%20summarizes%20the%20number,1

Bhandari, P. (2023, February 6). The Standard Normal Distribution: Calculator, Example &Uses. Scribbr.https://www.scribbr.com/statistics/standard-normal-distribution/

Brereton, R. G. (2014). The Normal Distribution. Journal of Chemometrics Columnist, 24, 789-792. https://doi.org/10.1002/cem.2655

Borovenik, M., & Kapadia, R. (2010). Research and Developments in Probability Education Internationally. In M. Joubert & P. Andrews (Eds.). Proceedings of the British Congress for Mathematics Education April 2010 (pp. 41-48). https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.475.3549&rep=rep1&ty pe=pdf

Darnius, O., Maulida, Y., Enita D. B. T., & Israil, S. (2019). A simulation based teaching method to explain the concept of probabilitytheory; an alternative learning method [Paper Presentation]. Journal of Physics: Conference Series 5th ICMSE2018. https://iopscience.iop.org/article/10.1088/1742-6596/1321/2/022076/pdf

Dooley, K. (2002). Simulation Research Methods. Arizona State University. In J. Baum (Ed.), Companion to organizations (pp. 829-848). Blackwell. https://www.researchgate.net/publication/228986412_Simulation_research_method s

Education Services Australia. (2013). Discrete Probability Distribution: A guide for teachers (Year 11 and 12). https://www.amsi.org.au/ESA_Senior_Years/PDF/DiscreteProbability4c.pdf

Ferreira, R. D. S., Kataoka, V. Y., & Karker, M. (2014). Teaching Probability with The Support of The R Statistical Software. Statistics Education Research Journal, 13(2), 132-147. https://iaseweb.org/documents/SERJ/SERJ13(2)_Ferreira.pdf?1417993588

Frost, J. (n.d.). Normal Distribution in Statistics. Statistics By Jim: Making statistics intuitive. https://statisticsbyjim.com/basics/normal-distribution/

Glen, S. (2022). Binomial Distribution: Formula, What it is, How to use it. Statistics How To. https://www.statisticshowto.com/probability-andstatistics/binomial-theorem/binomial-distribution-formula/

Glen, S. (2022). Continuous Probability Distribution. Statistics How To. https://www.statisticshowto.com/continuous-probability-distribution/

Glen, S. (2022). Normal Distributions (Bell Curve): Definition, Word Problems. Statistics How To. https://www.statisticshowto.com/probability-andstatistics/normal-distributions/

Gordon, J. (2022, April 16). Discrete Distribution – Explained. The Business Professor. https://thebusinessprofessor.com/en_US/research-analysisdecision-science/discrete-distribution-definition

Gordon, S. (2006). The Normal Distribution. Mathematics Learning Centre, University of Sydney. https://www.sydney.edu.au/

Hackenberger, B. K. (2020). R Software: Unfriendly but Probably the Best. Croatian Medical Journal, 61(1), 66-68. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7063554/pdf/CroatMedJ_61_0066 .pdf

Hallgren, K. (2013). Conducting Simulation Studies in the R Programming Environment. Tutorials in Quantitative Methods for Psychology, 9(2), 43-60. https://www.researchgate.net/publication/264390632_Conducting_Simulation_Stu dies_in_the_R_Programming_Environment

Hayes, A. (2022, March 19). Probability Distribution Explained: Types and Uses in Investing. Investopedia. https://www.investopedia.com/terms/p/probabilitydistribution.asp#:~:text=The%20 most%20commonly%20used%20distribution,skewed%20and%20does%20exhibit %20kurtosis.

Ihaka, R. (n.d.). R: Past and Future History [Paper Presentation]. University of Auckland. https://www.stat.auckland.ac.nz/~ihaka/downloads/Interface98.pdf

Kelley, K., Lai, K., & Wu, P. J. (2008). Using R for Data Analysis: A Best Practice for Research. In J. W. Osborne (Ed), Best Practices in Quantitative Method (pp. 535-572). SAGE Publications Inc. https://www3.nd.edu/~kkelley/publications/chapters/Kelley_Lai_Wu_Using_R_20 08.pdf

Koparan, T., & Yilmaz, G. K. (2015). The Effect of Simulation-based Learning on Prospective Teachers’ Inference Skills in Teaching Probability. Universal Journal of Educational Research, 3(11), 775-786. https://www.researchgate.net/publication/283353267_The_Effect_of_Simulationbased_Learning_on_Prospective_Teachers'_Inference_Skills_in_Teaching_Probabi lity

Krithikadatta, J. (2014). Normal Distribution. Journal of Conservative Dentistry, 17(1), 96-97.https://www.researchgate.net/publication/260272346_Normal_Distribution

Letkowski, J. (2014). Developing Poisson probability distribution applications in a cloud. Journal of Case Research in Business and Economics, 1-11. https://www.aabri.com/manuscripts/121246.pdf

Loredo, D. I. R., & Rojas, A. L., Chavarria, S. L., & Elizondo, M. M. (2017). A Different Solution for the Binomial Distribution with Application to Accounting. ICIC Express Letters, 11(9), 1385-1392. https://www.researchgate.net/publication/319523187_A_different_solution_for_the _binomial_distribution_with_application_to_accounting

McLeod, S. (2019, May 28). Introduction to the Normal Distribution (Bell Curve). Simply Psychology. https://www.simplypsychology.org/normal-distribution.html

Mendoza, D. J., & Mendoza, D. I. (2018). Information and Communication Technologies as a Didactic Tool for the Construction of Meaningful Learning in the Area of Mathematics. International Electronic Journal of Mathematics Education, 13(3), 261-271. https://www.iejme.com/download/information-and-communicationtechnologies-as-a-didactic-tool-for-the-construction-of-meaningful-3907.pdf

Morton, G., & Robert, K. (2014). Chapter 2 A Primer on Risk Mathematics. In G. Morton & K. Robert (Eds.), Multi-Asset Risk Modeling (pp. 21-61). Academic Press. https://doi.org/10.1016/B978-0-12-401690-3.00002-0

Musselwhite, D. J., & Wesolowski, B. C. (2018). NormalDistribution. In B. B. Frey(Ed.). The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation (pp. 1155-1157). SAGE Publications, Inc. https://www.researchgate.net/publication/327273083_Normal_Distribution

Owen, D. B. (1962). Handbook of Statistical Tables. Addison-Wesley Publishing Company, Inc.. https://archive.org/details/handbookofstatis00owen/page/n6/mode/1up?view=theat er

Raffle, H., & Brooks, G. P. (2005). Using Monte Carlo Software to Teach Abstract Statistical Concepts: A Case Study. Teaching of Psychology, 32(3), 192-195. https://www.researchgate.net/publication/234713548_Using_Monte_Carlo_Softwa re_to_Teach_Abstract_Statistical_Concepts_A_Case_Study

Ramaekers, K., & Janssens, G. K. (2008). On the choice of a demand distribution for inventory management models. European Jurnal of Industrial Engineering, 2(4), 479-491. https://www.researchgate.net/publication/5171339_On_the_choice_of_a_demand_ distribution_for_inventory_management_models

Robert, D. (2020, July 5). Demystifying the Binomial Distribution. Towards Data Science. https://towardsdatascience.com/demystifying-the-binomial distribution-580475b2bb2a

R Development Core. (1999). An Introduction to R. Notes on R: A Programming Environment for Data Analysis anf Graphics Version 4.2.1 (2022-06-23). https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf

Singh, B. P., Das, U. D., Singh, S., & Singh, G. (2021). Development of a Discrete Probability Distribution and its application to the Pattern of Child Deaths. Journal of Scientific Research, 65(5), 186-190. https://www.bhu.ac.in/research_pub/jsr/Volumes/JSR_65_05_2021/21.pdf

Turney, S. (2022, June 9). Probability Distribution: Formula, Types, & Example. Scribbr. https://www.scribbr.com/statistics/probability-distributions/

Ugoni, A., & Walker, B. F. (1995). An Introduction to Probability Distributions. COMSIG Review, 4(1), 16-23. https://www.researchgate.net/publication/25752718_AN_INTRODUCTION_TO_ PROBABILITY_DISTRIBUTIONS

Viti, A., Terzi, A., & Bertolaccini, L. (2014). A practical overview on probability distributions. Journal of Thoracic Disease, 7(3), 7-10. https://www.researchgate.net/publication/274891985_A_practical_overview_on_probability_distributions

Walck, C. (2007). Hand-book on Statistical Distributions for experimentalists. University of Stockholm. http://www.stat.rice.edu/~dobelman/textfiles/DistributionsHandbook.pdf

Zelterman, D. (2002). Discrete Distribution. In D. Zelterman (Ed.), Advanced Log-Linear Models Using SAS (pp. 1-18). SAS Institute. https://www.sas.com/

Zhang, X., & Maas, Z. (2019). Using R as a Simulation Tool in Teaching Introductory Statistics. International Electronic Journal of Mathematics Education, 14(3), 599-610. https://www.iejme.com/download/using-r-as-a-simulation-tool-inteaching-introductory-statistics-5773.pdf

Zhao, J., Zhang, F., Zhao, C., Wu, G., Wang, H., & Cao, X. (2020). The Properties and Application of Poisson Distribution [Paper Presentation]. Journal of Physics: Conference Series. https://www.researchgate.net/publication/342205996_The_Properties_and_Application_of_Poisson_Distribution

This material may be protected under Copyright Act which governs the making of photocopies or reproductions of copyrighted materials.
You may use the digitized material for private study, scholarship, or research.

Back to previous page