- #1
The normal distribution is a statistical concept that describes the spread of data around a central average value. It is also known as the Gaussian distribution or bell curve due to its characteristic shape.
The normal distribution is significant because many real-world phenomena can be modeled using this distribution. It allows for easy interpretation and analysis of data, making it a fundamental tool in statistical analysis.
The normal distribution is used in hypothesis testing to determine the probability of obtaining a specific sample mean or proportion. It is also used to calculate critical values and confidence intervals for hypothesis tests.
The Central Limit Theorem states that as sample size increases, the sampling distribution of the sample mean becomes approximately normal. This means that regardless of the underlying distribution of the population, the distribution of sample means will approach a normal distribution. This is why the normal distribution is often used in statistical inference.
The normal distribution has many real-life applications, such as in quality control, risk management, and finance. It is also used in psychology and social sciences to model human behavior and in natural sciences to describe physical phenomena. It is also commonly used in medical research and drug development.