125/12 would be your equivalent improper fraction
The pattern is n-3, so we will start from the beginning, from 1.
7, 4, 1, -2, -5, -8, -11, -14, -17, -20, -23, -26, -29, -32, -35, -38, -41, -44.
-44 is the 18th term in the sequence.
Answer:
Step-by-step explanation:
Answer:
10.5
Step-by-step explanation:
there are 2 middle values when you have an even number of data items so you must take their average
(10+11)/2 = 21/2 = 10.5
Answer:
There is approximately 17% chance of a person not having a disease if he or she has tested positive.
Step-by-step explanation:
Denote the events as follows:
<em>D</em> = a person has contracted the disease.
+ = a person tests positive
- = a person tests negative
The information provided is:

Compute the missing probabilities as follows:

The Bayes' theorem states that the conditional probability of an event, say <em>A</em> provided that another event <em>B</em> has already occurred is:

Compute the probability that a random selected person does not have the infection if he or she has tested positive as follows:


So, there is approximately 17% chance of a person not having a disease if he or she has tested positive.
As the false negative rate of the test is 1%, this probability is not unusual considering the huge number of test done.