340.8 cm^2.
72+72+72+62.4+62.4=340.8cm^2.
Answer:
P (X ≤ 4)
Step-by-step explanation:
The binomial probability formula can be used to find the probability of a binomial experiment for a specific number of successes. It <em>does not</em> find the probability for a <em>range</em> of successes, as in this case.
The <em>range</em> "x≤4" means x = 0 <em>or</em> x = 1 <em>or </em>x = 2 <em>or</em> x = 3 <em>or</em> x = 4, so there are five different probability calculations to do.
To to find the total probability, we use the addition rule that states that the probabilities of different events can be added to find the probability for the entire set of events only if the events are <em>Mutually Exclusive</em>. The outcomes of a binomial experiment are mutually exclusive for any value of x between zero and n, as long as n and p don't change, so we're allowed to add the five calculated probabilities together to find the total probability.
The probability that x ≤ 4 can be written as P (X ≤ 4) or as P (X = 0 or X = 1 or X = 2 or X = 3 or X = 4) which means (because of the addition rule) that P(x ≤ 4) = P(x = 0) + P(x = 1) + P (x = 2) + P (x = 3) + P (x = 4)
Therefore, the probability of x<4 successes is P (X ≤ 4)
Answer:
C or B if not then its B
Step-by-step explanation:
Answer:
82%
Step-by-step explanation:
We let the random variable X denote the number of defective units in the production run. Therefore, X is normally distributed with a mean of 21 defective units and a standard deviation of 3 defective units.
We are required to find the probability, P(17 < X < 25), that the number of defective units in the production run is between 17 and 25.
This can be carried out easily in stat-crunch;
In stat crunch, click Stat then Calculators and select Normal
In the pop-up window that appears click Between
Input the value of the mean as 21 and that of the standard deviation as 3
Then input the values 17 and 25
click compute
Stat-Crunch returns a probability of approximately 82%
Find the attachment below.
. So:
