We are given a uniform random variable U∼U(10,19) U \sim U(10, 19) U∼U(10,19). The parameters of this distribution are:
The quantile function for a uniform distribution is defined as:
Q(p)=a+p×(b−a) Q(p) = a + p \times (b - a) Q(p)=a+p×(b−a)
For our case, we want to find the 0.75 quantile, so we set p=0.75 p = 0.75 p=0.75:
Q(0.75)=10+0.75×(19−10) Q(0.75) = 10 + 0.75 \times (19 - 10) Q(0.75)=10+0.75×(19−10)
Calculating the difference:
19−10=9 19 - 10 = 9 19−10=9
Now substituting back into the equation:
Q(0.75)=10+0.75×9 Q(0.75) = 10 + 0.75 \times 9 Q(0.75)=10+0.75×9
Calculating 0.75×9 0.75 \times 9 0.75×9:
0.75×9=6.75 0.75 \times 9 = 6.75 0.75×9=6.75
Thus, we have:
Q(0.75)=10+6.75=16.75 Q(0.75) = 10 + 6.75 = 16.75 Q(0.75)=10+6.75=16.75
The calculated quantile Q(0.75)=16.75 Q(0.75) = 16.75 Q(0.75)=16.75 is already rounded to two decimal places.
The 0.75 quantile of the uniform distribution U(10,19) U(10, 19) U(10,19) is:
16.75 \boxed{16.75} 16.75
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