Answer:
-35
Step-by-step explanation:
PEMDAS
1/6 = 0.16 with a line over the 6 because it is repeating
Answer:
4
+ 8 x - 435=0
Step-by-step explanation:
Let x be any natural number
Let the age of Bill= 2 x+ 1 years (Since age is odd integer)
Than, age of a Susan= 2 x + 3 years
Since ages are consecutive odd integers
According to question
(2 x+1)(2 x+ 3)= 438
4
+ 8 x + 3 = 438
4
+ 8 x + 3 - 438 =0
4
+ 8 x - 435=0
This equation can be used to find the ages of both
Hence, the correct answer is 4
+ 8 x - 435=0
Answer:
The circumference would be 12*3.14/2=18.84
Answer:
The probability that a woman in her 60s has breast cancer given that she gets a positive mammogram is 0.0276.
Step-by-step explanation:
Let a set be events that have occurred be denoted as:
S = {A₁, A₂, A₃,..., Aₙ}
The Bayes' theorem states that the conditional probability of an event, say <em>A</em>ₙ given that another event, say <em>X</em> has already occurred is given by:
![P(A_{n}|X)=\frac{P(X|A_{n})P(A_{n})}{\sum\limits^{n}_{i=1}{P(X|A_{i})P(A_{i})}}](https://tex.z-dn.net/?f=P%28A_%7Bn%7D%7CX%29%3D%5Cfrac%7BP%28X%7CA_%7Bn%7D%29P%28A_%7Bn%7D%29%7D%7B%5Csum%5Climits%5E%7Bn%7D_%7Bi%3D1%7D%7BP%28X%7CA_%7Bi%7D%29P%28A_%7Bi%7D%29%7D%7D)
The disease Breast cancer is being studied among women of age 60s.
Denote the events as follows:
<em>B</em> = a women in their 60s has breast cancer
+ = the mammograms detects the breast cancer
The information provided is:
![P(B) = 0.0312\\P(+|B)=0.81\\P(+|B^{c})=0.92](https://tex.z-dn.net/?f=P%28B%29%20%3D%200.0312%5C%5CP%28%2B%7CB%29%3D0.81%5C%5CP%28%2B%7CB%5E%7Bc%7D%29%3D0.92)
Compute the value of P (B|+) using the Bayes' theorem as follows:
![P(B|+)=\frac{P(+|B)P(B)}{P(+|B)P(B)+P(+|B^{c})P(B^{c})}](https://tex.z-dn.net/?f=P%28B%7C%2B%29%3D%5Cfrac%7BP%28%2B%7CB%29P%28B%29%7D%7BP%28%2B%7CB%29P%28B%29%2BP%28%2B%7CB%5E%7Bc%7D%29P%28B%5E%7Bc%7D%29%7D)
![=\frac{(0.81\times 0.0312)}{(0.81\times 0.0312)+(0.92\times (1-0.0312)}\\](https://tex.z-dn.net/?f=%3D%5Cfrac%7B%280.81%5Ctimes%200.0312%29%7D%7B%280.81%5Ctimes%200.0312%29%2B%280.92%5Ctimes%20%281-0.0312%29%7D%5C%5C)
![=\frac{0.025272}{0.025272+0.891296}](https://tex.z-dn.net/?f=%3D%5Cfrac%7B0.025272%7D%7B0.025272%2B0.891296%7D)
![=0.02757\\\approx0.0276](https://tex.z-dn.net/?f=%3D0.02757%5C%5C%5Capprox0.0276)
Thus, the probability that a woman in her 60s has breast cancer given that she gets a positive mammogram is 0.0276.