An error rate is simply the number of errors divided by the total number of attempts. In the context of system design, error rates are important because they help you understand the reliability of your system and the resources that are required to maintain it.
An error rate is the number of incorrect outputs divided by the total number of outputs. There are two types of outputs: correct outputs and incorrect outputs. All systems have some level of error rate, and no system is 100% accurate all the time. Depending on the application, acceptable error rates can range from 0.1% to 10%. For example, a spell checker might have an error rate of 0.1%, while a navigation system might have an error rate of 5%. if you have a highly trafficked website with a low error rate, that means your website is able to handle a lot of traffic without any issues. However, if you have a low trafficked website with a high error rate, that means your website is not able to handle much traffic and needs more work.
If your service is knowingly throwing an error due to an internal issue, 50X response codes should be used.
Error rates become especially important when you are designing a system that needs to be highly available (i.e. always up and running with minimal downtime). This is because a high availability system cannot tolerate any errors - even if those errors are rare. For example, if you are designing a system for an e-commerce website, the last thing you want is for the website to go down during a major sale or event. A single moment of downtime could cost the company millions of dollars in lost sales. As such, designers of high availability systems need to take into account not only the likelihood of errors occurring, but also the consequences of those errors occurring.
A false positive is when the system incorrectly classifies something as belonging to a certain category when it actually does not belong to that category. For example, if a spell checker marks the word "form" as being spelled incorrectly, that would be a false positive. A false negative is when the system incorrectly classifies something as not belonging to a certain category when it actually does belong to that category. For example, if a spell checker fails to mark the word "from" as being spelled incorrectly, that would be a false negative.
To calculate an error rate, you need two pieces of information: the number of correct outputs and the number of incorrect or incomplete outputs. You can then use this formula:
Error Rate = Number of Incorrect Outputs / Total Numberoftputs x 100
For example, let's say that out of 1,000 inputs, a spell checker produces 990 correct outputs and 10 incorrect outputs. The error rate would be calculated as follows: Error Rate = 10 / 1000 x 100 = 1%
As you can see, even though there are only 10 incorrect outputs out of 1,000 total inputs, that still equates to an error rate of 1%.