True/False Censoring occurs when the event of interest (e.g., disease status) is observed on every individual, usually due to time constraints. The incidence rate (IR), is computed by taking the ratio of the number of new cases of disease to the total number of person-time units available. The prevalence of a disease depends on the incidence of the disease as well as the duration of the disease.
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
True/False
Censoring occurs when the event of interest (e.g., disease status) is observed on every individual, usually due to time constraints.
The incidence rate (IR), is computed by taking the ratio of the number of new cases of disease to the total number of person-time units available.
The prevalence of a disease depends on the incidence of the disease as well as the duration of the disease.
Trending now
This is a popular solution!
Step by step
Solved in 4 steps with 3 images
