Galton Board Experiment: Proof of Central Limit Theorem

This paper investigates the application of the Central Limit Theorem (CLT) using a Galton board experiment. The Galton board, which produces a binomial distribution of ball positions, serves as a practical model to test the CLT’s assertion that the distribution of sample means approaches a normal distribution as the sample size increases. In this experiment, 30 independent trials were conducted, with 100 balls passing through 10 rows of pegs in each trial. The sample means for each trial were computed, and the resulting sampling distribution was analyzed. A normal distribution curve was fitted to the data, visually demonstrating alignment with CLT predictions. Additionally, statistical tests, including the Shapiro-Wilk test, were applied to rigorously evaluate the normality of the sample means, providing empirical validation for the theoretical model. The findings confirm the applicability of the CLT to the Galton board, as the sampling distribution closely follows a normal pattern, highlighting the theorem’s generalizability even when the original data follows a binomial distribution.

Authors

Publication Details

Journal
Science and Technology of Engineering Chemistry and Environmental Protection
Published
2024-12-31
DOI
https://doi.org/10.61173/z5yb2616
Citations
1
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
Field-Weighted Citation Impact
0.71
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Galton Board Experiment: Proof of Central Limit Theorem

Jen J. Gong
1 citations
Science and Technology of Engineering Chemistry and Environmental Protection
Statistical Distribution Estimation and Applications
0.71
article

Galton Board Experiment: Proof of Central Limit Theorem

Jen J. Gong
article en
1 citations

Abstract

This paper investigates the application of the Central Limit Theorem (CLT) using a Galton board experiment. The Galton board, which produces a binomial distribution of ball positions, serves as a practical model to test the CLT’s assertion that the distribution of sample means approaches a normal distribution as the sample size increases. In this experiment, 30 independent trials were conducted, with 100 balls passing through 10 rows of pegs in each trial. The sample means for each trial were computed, and the resulting sampling distribution was analyzed. A normal distribution curve was fitted to the data, visually demonstrating alignment with CLT predictions. Additionally, statistical tests, including the Shapiro-Wilk test, were applied to rigorously evaluate the normality of the sample means, providing empirical validation for the theoretical model. The findings confirm the applicability of the CLT to the Galton board, as the sampling distribution closely follows a normal pattern, highlighting the theorem’s generalizability even when the original data follows a binomial distribution.

Science and Technology of Engineering Chemistry and Environmental ProtectionVol. 1(10)
Openalex Percentile: Top 23%
Statistical Distribution Estimation and Applications
0.71
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.