Joint Frequency Distribution of Images in MATLAB | Python | C++

Joint Relative Distribution Function: normalizes the frequencies by the number of pixels Joint Cumulative Frequency Distribution Function: indicates the frequency of pixels with gray levels less than or equal to gray level Ip in image p and gray level Iq in image q.
A joint frequency distribution is a table or matrix that shows the frequency of two or more variables occurring together in a dataset. It is often used in statistics and data analysis to analyze the relationship between two or more variables.

For example, consider a dataset of students and their exam scores in two subjects, math and science. A joint frequency distribution can be created by tabulating the number of students who scored a particular grade in both math and science. The resulting table would show the frequency of each possible combination of grades in the two subjects, such as the number of students who scored an A in math and a B in science, or the number of students who scored a C in both subjects.

Joint frequency distributions can be used to calculate various statistics, such as marginal frequencies (the frequencies of each variable separately), conditional frequencies (the frequency of one variable given a particular value of the other variable), and joint probabilities (the probability of two or more events occurring together). They are a useful tool for understanding the relationships between variables and for making predictions based on those relationships.
Statistics
Data Analysis
Probability
Correlation
Data Science
Descriptive Statistics
Normal Distribution
Bivariate Data
Scatter Plot
Two-way Table
Contingency Table
Marginal Distribution
Conditional Probability
Chi-Square Test
Frequency Table
Multivariate Data Analysis
Statistical Inference
Data Visualization
Quantitative Research
Statistical Methods