Numerical distribution
Numerical distribution is a term used in statistics to describe the way data is spread out or distributed across different values. Understanding numerical distribution is essential for analyzing and interpreting data effectively.
There are several types of numerical distributions, including:
- Uniform distribution: where all values have an equal probability of occurring, such as rolling a fair six-sided die.
- Normal distribution: a bell-shaped curve where most values cluster around the mean, such as heights or weights of a population.
- Skewed distribution: where the data is not evenly distributed and may have a longer tail on one side, such as income distribution.
By examining the numerical distribution of data, statisticians can identify patterns, trends, and outliers that may be present in the data set. This information can then be used to make informed decisions and predictions based on the data.
For more information on numerical distribution, you can visit the Wikipedia page on frequency distribution.