As you know that sum of complementary angles equal 90°
so,
7x + 11x = 90
18x = 90
x = 90/18
x =5
so,
option A is the correct one.
Answer:
mean (μ) = 4.25
Step-by-step explanation:
Let p = probability of a defective computer components = 
let q = probability of a non-defective computer components = 
Given random sample n = 25
we will find mean value in binomial distribution
The mean of binomial distribution = np
here 'n' is sample size and 'p' is defective components
mean (μ) = 25 X 0.17 = 4.25
<u>Conclusion</u>:-
mean (μ) = 4.25
Answer:
New Digit = 315,864
Step-by-step explanation:
Given:
Digit - 135,864
Value of digit 3 = 30,000
Find:
New Digit, Value of 3 is 10 times greater
Computation:
Value of 3 is 10 times greater = (30,000) = 300,000
New Digit = 315,864
The domain would be x ≥ 0.
This is because the outlet cannot have profit before it was open. Therefore, the growth must be from year 0 to present. If they give a year as starting, you can have an upper limit too, but there is not enough information here to determine that information.
Answer:
23.1% probability of meeting at least one person with the flu
Step-by-step explanation:
For each encounter, there are only two possible outcomes. Either the person has the flu, or the person does not. The probability of a person having the flu is independent of any other person. So we use the binomial probability distribution to solve this question.
Binomial probability distribution
The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

In which
is the number of different combinations of x objects from a set of n elements, given by the following formula.

And p is the probability of X happening.
Infection rate of 2%
This means that 
Thirteen random encounters
This means that 
Probability of meeting at least one person with the flu
Either you meet none, or you meet at least one. The sum of the probabilities of these outcomes is 1. So

We want
. Then

In which



23.1% probability of meeting at least one person with the flu