What is a distribution?
Please help, thank you.
http://www.mathsisfun.com/data/frequency-distribution.html
or do you mean?
http://www.mathsisfun.com/associative-commutative-distributive.html
It was the first one, thank you very much. Now I can understand my homework. :)
You're welcome. :-)
Doez the communative propety apply to division. Give an exampls
A distribution refers to the way in which a set of data or values is spread out or organized. It provides information about how frequently different values occur within a dataset. To understand distributions, you'll need to take a few steps:
1. Start by collecting the data: Gather the dataset that you want to analyze. This could be a set of numerical values, such as exam scores, heights of individuals, or sales figures.
2. Organize the data: Sort the data in ascending or descending order, depending on your preference. This step is crucial for identifying patterns and visualizing the distribution effectively.
3. Determine the types of distributions: There are several types of distributions, including normal (bell-shaped), uniform (flat), skewed (asymmetric), and bimodal (two peaks), among others. The type of distribution you encounter will depend on the nature of your data.
4. Plot a histogram: One common way to visualize a distribution is by creating a histogram. A histogram is a bar graph that represents the frequency of values within different intervals or bins. To make a histogram, you need to determine the appropriate number of bins, which influences the level of detail in your visualization.
5. Analyze the shape: Examine the shape of the distribution by analyzing the histogram or other graphical representations. Look for patterns like symmetry or skewness, as these characteristics can provide insights into the data's properties.
6. Calculate measures of central tendency and variability: To further understand a distribution, you can calculate measures such as the mean (average), median (middle value), and mode (most frequently occurring value). Additionally, you can compute measures of spread, such as the range, variance, and standard deviation.
By following these steps, you can gain a deeper understanding of what a distribution represents and how it can provide insights into the data you are analyzing.