Answer:
<h2>
B. ST = 2</h2><h2 />
Step-by-step explanation:
|<-------------- 10 --------------------->|
S-------------------T--------------------U
X-6 2X - 8
FIND: ST
SOLUTION:
ST + TU = SU
x - 6 + 2x - 8 = 10
combine like terms:
3x - x = 10 + 8 + 6
x = 24/3
x = 8
plugin the value of x= 8 into the ST = x - 6
ST = x - 6
ST = 8 - 6
ST = 2
proof:
x - 6 + 2x - 8 = 10
8 - 6 + 2(8) - 8 = 10
10 = 10 ---OK
Answer:
3
Step-by-step explanation:
Answer:i dont know
ok
i just need points
Step-by-step explanation:
done ??
The linear equation is y=mx+b
Using the Poisson distribution, it is found that:
a) The mean is of 15.63.
b) The probability is of 0.0911 = 9.11%.
c) The probability is
, which is less than 0.05, hence 0 births in a single day would be a significantly low number of births.
<h3>What is the Poisson distribution?</h3>
In a Poisson distribution, the probability that X represents the number of successes of a random variable is given by:

The parameters are:
- x is the number of successes.
- e = 2.71828 is the Euler number.
is the mean in the given interval.
Item a:
The mean is given by:

Item b:
The probability is P(X = 17), hence:


The probability is of 0.0911 = 9.11%.
Item c:
The probability is P(X = 0), hence:


The probability is
, which is less than 0.05, hence 0 births in a single day would be a significantly low number of births.
More can be learned about the Poisson distribution at brainly.com/question/13971530
#SPJ1