gaussian distribution Synonyms
No Synonyms and anytonyms found
gaussian distribution Meaning
Wordnet
gaussian distribution (n)
a theoretical distribution with finite mean and variance
gaussian distribution Sentence Examples
- In statistics, the Gaussian distribution, also known as the normal distribution, is a bell-shaped curve that represents the distribution of data.
- Many natural phenomena, such as human height and IQ scores, follow a Gaussian distribution.
- The central limit theorem states that the sum or average of a large number of independent random variables tends to follow a Gaussian distribution.
- Gaussian distribution is characterized by its mean and standard deviation, which determine its shape and spread.
- The probability density function of the Gaussian distribution is given by the famous bell-shaped curve formula.
- Gaussian distribution is widely used in various fields such as finance, engineering, and physics due to its mathematical properties and real-world applicability.
- When plotting data on a histogram, if it forms a symmetrical bell curve, it indicates that the data follows a Gaussian distribution.
- Gaussian distribution is essential in hypothesis testing and inferential statistics to make predictions and draw conclusions about populations.
- One of the assumptions in linear regression analysis is that the error terms follow a Gaussian distribution.
- Gaussian distribution plays a crucial role in machine learning algorithms like Gaussian Naive Bayes and Gaussian process regression for classification and regression tasks.
FAQs About the word gaussian distribution
a theoretical distribution with finite mean and variance
No synonyms found.
No antonyms found.
In statistics, the Gaussian distribution, also known as the normal distribution, is a bell-shaped curve that represents the distribution of data.
Many natural phenomena, such as human height and IQ scores, follow a Gaussian distribution.
The central limit theorem states that the sum or average of a large number of independent random variables tends to follow a Gaussian distribution.
Gaussian distribution is characterized by its mean and standard deviation, which determine its shape and spread.