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Parametric Analysis is statistical analysis done on known distributions, where we can make inference on population parameters like mean and standard deviation based on sample statistic. Exp. Normal Distribution. There are some key features of Parametric Analysis: 1. Assumption: It follows specific know distribution. 2. Efficiency: If efficiency holds true, it provides precise results. 3. Rely on Statistical theories and formulas. Usage Across Industries: 1. Pharmaceuticals & Healthcare Industries: In pharma & healthcare for new drug development we need clinical trial and bio equivalence study which heavily relies on parametric analysis as it requires inference based on sample data provided that the data follows known data distribution. 2. Manufacturing & Quality Control: For developing robust product we need to ensure that process parameters have high sigma level. Generally, we try to increase sigma level of Critical Quality Attributes (CQAs) through optimising Critical Process Parameters (CPPs). 3. Aerospace & Automotive: High reliability is a must requirement for aerospace & automative industries which requires high precision and accuracy which means it has high application of parametric analysis. 4. Service Industries: In service industry, the arrival rate, service rate and queuing follows specific statistical distributions that also requires parametric analysis. Advantages of Parametric Analysis: 1. High Precision: In manufacturing, if we want to compare machine’s output to specific standard the parametric t-test is the best option. 2. Power of Test: In pharma, while conducting clinical trials the parametric tests like ANOVA can help with checking efficiency of new drug. 3. Wide Applications: Most real life applications follow normal distribution which is helpful for regression modelling (Exp- Energy Prediction Modeling) 4. Simple Interpretation: Process capability analysis through Cp & Cpk helps with summarising how the process is performing against customer defined specification limits. Exp- Moisture content in drug can be measured in Cp & Cpk and can be interpreted on how it performs against specification limits.