Normal distribution and its role in the formulation of distributions and other statistical relationships
Abstract
This research explains the effect of the normal distribution on the formulation and formation of various statistical distributions and relationships, as well as how the characteristics of the normal distribution can change the parameters, features, and forms of distributions and other relationships.It reveals important correlations between the normal distribution and these distributions, formulas, and relationships, and that the distributions and statistical relationships affected by the normal distribution exhibit comparable characteristics such as mean, variance, and overall shape, highlighting that the normal distribution plays an important role in the statistical behavior of these distributions and relationships.
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References
1. Agbonaye, A. I., Izinyon, O. C. (2023) Evaluation of best-fit probability distribution models for prediction of rainfall in Southern Nigeria. doi: https://core.ac.uk/download/552648093.pdf
2. Arendarczyk, Marek, Skowronek, Katarzyna, Wyłomańska, Agnieszka, Zimroz, et al. (2024) Modified Greenwood statistic and
its application for statistical testing. doi: http://arxiv.org/abs/2405.11834
3. Bentler, Peter M., Zheng, Bang Quan (2024) Enhancing Model Fit Evaluation in SEM: Practical Tips for Optimizing Chi-Square Tests. doi: http://arxiv.org/abs/2308.13939.
4. Boyer, C , Corrigan, N (2022) Living in the Moment: A Mathematically Verified Approach for Molecular Weight Distribution Analysis and Application to Data Storage. doi: https://unsworks.unsw.edu.au/bitstreams/6dca2d85-d026-48c7- bcf1-6f4387a8633c/download
5. Cairoli, Andrea, Giona, Massimiliano, Klages, Rainer (2022) In the folds of the Central Limit Theorem: L'evy walks, large deviations and higher-order anomalous diffusion. doi: https://core.ac.uk/download/552662461.pdf
6. Chen, Yu-Tong, Dong, Liang, Huang, Wei-Tian, Lu, et al. (2023) Comprehensive study of the blazars from Fermi-LAT LCR: The log-normal flux distribution and linear RMS-Flux relation. doi: http://arxiv.org/abs/2307.10547
7. Haubold, Hans J., Mathai, Arak M., Provost, Serge B. (2022) Multivariate Statistical Analysis in the Real and Complex Domains. doi: https://core.ac.uk/download/548537345.pdf
8. Hirsch, Christian, Juhasz, Peter (2023) On the topology of higher-order age-dependent random connection models. doi: http://arxiv.org/abs/2309.11407
9. Li, Xinran, Shi, Lei (2024) Some theoretical foundations for the design and analysis of randomized experiments. doi: https://core.ac.uk/download/628472161.pdf
10. Maulina, Riska, Nisa, Eva Khoirun (2024) The Comparison of Inverse Gaussian and Gamma Regression: Application on Stunting Data in Jepara. doi: https://core.ac.uk/download/620269799.pdf
11. Qureshi Yaser , Dharmender Singh (2023) Non parametric statistical tools in biological research : A review. Doi: https://core.ac.uk/download/588567433.pdf
12. Winters, Kenneth (2022) A NEW APPLICATION OF THE CENTRAL LIMIT THEOREM. doi:


