This article reviews the applications and best practices of statistical techniques in precision metrology, emphasizing their role in enhancing measurement accuracy, reducing uncertainties, and optimizing manufacturing processes. Statistical methods are crucial for analyzing measurement data, assessing measurement uncertainty, and making informed decisions in process control and quality assurance. Key applications include experimental design, statistical process control (SPC), uncertainty evaluation, and regression analysis. Best practices in statistical techniques involve proper data collection, adherence to statistical assumptions, selection of appropriate models, and cautious interpretation of results. The article also highlights real-world case studies from industries such as automotive, semiconductor, aerospace, and pharmaceuticals, demonstrating how statistical techniques are used to improve quality, efficiency, and reliability. Future directions include the integration of AI and ML, enhanced metrology in additive manufacturing, and advanced uncertainty quantification methods. Overall, the article underscores the importance of statistical techniques in precision metrology and their potential to drive innovation and improve performance in various industries.This article reviews the applications and best practices of statistical techniques in precision metrology, emphasizing their role in enhancing measurement accuracy, reducing uncertainties, and optimizing manufacturing processes. Statistical methods are crucial for analyzing measurement data, assessing measurement uncertainty, and making informed decisions in process control and quality assurance. Key applications include experimental design, statistical process control (SPC), uncertainty evaluation, and regression analysis. Best practices in statistical techniques involve proper data collection, adherence to statistical assumptions, selection of appropriate models, and cautious interpretation of results. The article also highlights real-world case studies from industries such as automotive, semiconductor, aerospace, and pharmaceuticals, demonstrating how statistical techniques are used to improve quality, efficiency, and reliability. Future directions include the integration of AI and ML, enhanced metrology in additive manufacturing, and advanced uncertainty quantification methods. Overall, the article underscores the importance of statistical techniques in precision metrology and their potential to drive innovation and improve performance in various industries.