Stephanie has a homeowners insurance policy for her $355,000 home with an annual premium of $0.42 per $100 of value and a deduct
2 answers:
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Answer:
The correct answer is
(0.0128, 0.0532)
Step-by-step explanation:
In a sample with a number n of people surveyed with a probability of a success of , and a confidence interval
, we have the following confidence interval of proportions.
In which
Z is the zscore that has a pvalue of
For this problem, we have that:
In a random sample of 300 circuits, 10 are defective. This means that and
Calculate a 95% two-sided confidence interval on the fraction of defective circuits produced by this particular tool.
So = 0.05, z is the value of Z that has a pvalue of
, so
.
The lower limit of this interval is:
The upper limit of this interval is:
The correct answer is
(0.0128, 0.0532)
A conservative vector field 
has curl 
. In this case,
so the vector field is not conservative.
so the vector field is not conservative.
Answer:
a) For this case we can find the cumulative distribution function first:
So then by the complement rule we have this:
b)
So then we have this using independence:
We want to find the following probability:
Using the definition of conditional probability we got:
And we see that if a = 2 and b=5 we have:
c) For this case we use independent identical and with the same distribution experiments.
And the result for part b makes sense since we are interest in find the probability that the random variable of interest would be higher than an specified value given another condition with a value lower or equal.
Step-by-step explanation:
Previous concepts
The geometric distribution represents "the number of failures before you get a success in a series of Bernoulli trials. This discrete probability distribution is represented by the probability density function:"
If we define the random of variable Y we know that:
Part a
For this case we can find the cumulative distribution function first:
So then by the complement rule we have this:
Part b
For this case we can use the result from part a to conclude that:
So then we have this assuming independence:
We want to find the following probability:
Using the definition of conditional probability we got:
And we see that if a = 2 and b=5 we have:
Part c
For this case we use independent identical and with the same distribution experiments.
And the result for part b makes sense since we are interest in find the probability that the random variable of interest would be higher than an specified value given another condition with a value lower or equal.