Stephen has developed a diagnostic tool that predict the probability of having the eye disease. He tested the device in 60 patients and got the following results: Diagnosed with eye disease Diagnosed without eye disease With eye disease 13 16 Without eye disease 17 14 What is the sensitivity of Stefáns tool? 1. 0.43 2. 0.47 3. 0.45 4. 0.41
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!
![Stephen has developed a diagnostic tool that predict the probability of having the eye disease.
He tested the device in 60 patients and got the following results:
Diagnosed with eye disease Diagnosed without eye disease
With eye disease
13
16
Without eye disease
17
14
What is the sensitivity of Stefáns tool?
1. 0.43
2. 0.47
3. 0.45
4. 0.41](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F479d2b79-8bd0-4544-821a-3e17d351982d%2Fbbb471bd-5bff-4a55-a6e1-bd0b1dc68d0f%2Fme1csqi_processed.png&w=3840&q=75)
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