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  • Confidence Intervals and Sampling Distributions
    • Overview
    • Tools and Technologies Used
    • Results and Key Findings
    • Reflection

Project 3

Confidence Intervals and Sampling Distributions

Overview

This analysis was divided into two parts. Part A focused on confidence interval construction using the House Price dataset. Part B examined sampling distributions using an external dataset on accident costs.

In Part A, three confidence intervals (90%, 95%, 99%) were calculated for average house price. A 95% confidence interval was calculated for average house size in Cork, and another for the proportion of detached houses sold in Ireland. The required sample size to reduce sampling error to 0.02 was also calculated.

In Part B, an Excel dataset on accident costs was analysed to compare individual accident cost distributions across 1,000 companies with average costs from 200 samples of 100 companies, with reference to the Central Limit Theorem.

Tools and Technologies Used

  • Jamovi
  • Microsoft Excel
  • Microsoft Word

Results and Key Findings

The analysis demonstrated how confidence level affects interval width, and how averaging across samples reduces variability in line with the Central Limit Theorem.

Reflection

This project deepened my understanding of inferential statistics, confidence intervals, and sampling theory.

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