Imagine that a study of prostate cancer was initiated in Des Moines, Iowa. A total of 1,000 men, 55-64 years of age, with no prior evidence of prostate cancer were enrolled in the study. Each year during the study, the men being observed were examined and tested for presence of prostate cancer. The results of annual examinations revealed: 10 cases confirmed at 1st exam 15 additional cases at 2nd exam 20 additional cases at 3rd exam 25 additional cases at 4th (final) exam What is incidence density of prostate cancer in this group?
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!
- Imagine that a study of prostate cancer was initiated in Des Moines, Iowa. A total of 1,000 men, 55-64 years of age, with no prior evidence of prostate cancer were enrolled in the study. Each year during the study, the men being observed were examined and tested for presence of prostate cancer. The results of annual examinations revealed:
10 cases confirmed at 1st exam
15 additional cases at 2nd exam
20 additional cases at 3rd exam
25 additional cases at 4th (final) exam
What is incidence density of prostate cancer in this group?
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