Previous: 2.3 – The Probability Density Function
Next: 2.5 – Some Common Continuous Distributions
Previous: 2.3 – The Probability Density Function
Next: 2.5 – Some Common Continuous Distributions
Previous: 2.3 – The Probability Density Function
Next: 2.5 – Some Common Continuous Distributions
Let f(x) = k(3x2 + 1).
Therefore, k = 1/10.
Notice that f(x) ≥ 0 for all x. Also notice that we can rewrite this PDF in the obvious way so that it is defined for all real numbers:
Using our value for k from Part 1:
Therefore, Pr(1 ≤ X ≤ 2) is 4/5.
Using the Fundamental Theorem of Calculus, the CDF of X at x in [0,2] is
We can also easily verify that F(x) = 0 for all x < 0 and that F(x) = 1 for all x > 2.
Since X is a continuous random variable, we immediately know that the probability that it equals any one particular value must be zero. More directly, we compute
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Throughout this website, the following acronyms are used.
PDF = probability distribution function
CDF = cumulative distribution function
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