Diseases over time change: Example: TB was very common here in the US in 1800. It was found more commonly in cities like NY. But now in 2000 it very uncommon but still more likely found in cities. If you would make dots for every 100 cases and put them on a map, in 1800 the distribution for TB would be much different than in 2000. There would be many more dots for 1800 than 2000. Also there may be more dots in other cities than NY. TB is much more common in other parts of the world and "dots" for 1800 compared to 2000 would show that.
The components of epidemiology includes: Disease frequency, Distribution of disease, Out comes of disease
The frequency and distribution of disease.
Biological
biological
Biological
Influenza
It is a theoretical probability distribution. I have included two links from the internet which describe the distribution and some of its applications. Sometimes in statistics, we are more interested in the more extreme statistics rather than the average. For example, if we are studying the spread of a disease, perhaps the long distance that the disease can travel one time in 100 is more important than the average distance. Both the exponential and the Pareto distribution are used when the tail end probabilities (cumulative probability close to 1) are of interest. See related links.
The distribution of resources among the population was not equitable, leading to disparities in access to education and healthcare.
Everything that is normal and can can be distributed easily is known as normal distribution time.
gender.
The Poisson distribution. The Poisson distribution. The Poisson distribution. The Poisson distribution.
stable distribution