A standard normal distribution is a bell-shaped curve that represents the distribution of a continuous random variable. It is also known as a Gaussian distribution or a normal distribution. It is characterized by a mean of 0 and a standard deviation of 1.
The properties of a standard normal distribution include:
A standard normal distribution is a specific type of normal distribution with a mean of 0 and a standard deviation of 1. A normal distribution can have any mean and standard deviation, and is often used to describe real-world data that may not follow a perfect bell-shaped curve.
The standard normal distribution is useful because it allows us to standardize data and make comparisons between different distributions. By converting data to z-scores (the number of standard deviations away from the mean), we can compare data from different distributions and make predictions about the likelihood of certain values occurring.
The standard normal distribution is used in many statistical analyses, such as hypothesis testing and confidence intervals. It is also used to calculate probabilities and make predictions about future data. In data analysis, it can help us identify outliers and determine the significance of relationships between variables.