The below PDF describes a triangular distribution of a length (L) that is falling between 20.1 em and 20.2 cm. Prove mathematically that the probability density of the best measurand in the below triangular PDF is 2/ar. p(L) dl - 2/ar Best approximation: Avg value - 20.15 cm 20.1 20.2 L (cm)
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!
![The below PDF describes a triangular distribution of a length (L) that is falling
between 20.1 cm and 20.2 cm. Prove mathematically that the probability density of the
best measurand in the below triangular PDF is 2/ar.
p(L)
dL
2/ar
Best approximation:
Avg value = 20.15 cm
20.1
20.2
L (cm)
Fig. 1: Schematic diagram of a triangular PDF. The
vertical axis denotes the probability density function or
probability per range (p/dL). The horizontal axis describes
the length of the object.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F5171acf4-3bf2-45f1-b7fb-6dcff96f34d8%2F1a292999-f671-47e3-863a-4da417101f16%2Fg9dyvc_processed.jpeg&w=3840&q=75)
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