Answer:
Each hiker receives 7 ounces of trail mix
Step-by-step explanation:
Trail mix=quantity of peanuts+quantity of raisins+quantity of walnuts+quantity of chocolate chips
where;
Quantity of peanuts=1.25 pounds
Quantity of raisins=14 oz, since 1 pound=16 oz.
Quantity of raisins=(14/16)=0.875 pounds
Quantity of walnuts=12 oz=(12/16)=0.75 pounds
Quantity of chocolate chips=10 oz=(10/16)=0.625 pounds
Replacing;
Trail mix=(1.25+0.875+0.75+0.625)=3.5 pounds
Trail mix=Quantity per hiker×Number of hikers
where;
Trail mix=3.5 pounds
Quantity per hiker=q
Number of hikers=8
Replacing;
3.5=q×8
q=3.5/8=0.4375 pounds
I pound=16 ounces
q=0.4375×16=7 ounces
Each hiker receives 7 ounces of trail mix
Answer:
Correct option: (a) 0.1452
Step-by-step explanation:
The new test designed for detecting TB is being analysed.
Denote the events as follows:
<em>D</em> = a person has the disease
<em>X</em> = the test is positive.
The information provided is:

Compute the probability that a person does not have the disease as follows:

The probability of a person not having the disease is 0.12.
Compute the probability that a randomly selected person is tested negative but does have the disease as follows:
![P(X^{c}\cap D)=P(X^{c}|D)P(D)\\=[1-P(X|D)]\times P(D)\\=[1-0.97]\times 0.88\\=0.03\times 0.88\\=0.0264](https://tex.z-dn.net/?f=P%28X%5E%7Bc%7D%5Ccap%20D%29%3DP%28X%5E%7Bc%7D%7CD%29P%28D%29%5C%5C%3D%5B1-P%28X%7CD%29%5D%5Ctimes%20P%28D%29%5C%5C%3D%5B1-0.97%5D%5Ctimes%200.88%5C%5C%3D0.03%5Ctimes%200.88%5C%5C%3D0.0264)
Compute the probability that a randomly selected person is tested negative but does not have the disease as follows:
![P(X^{c}\cap D^{c})=P(X^{c}|D^{c})P(D^{c})\\=[1-P(X|D)]\times{1- P(D)]\\=0.99\times 0.12\\=0.1188](https://tex.z-dn.net/?f=P%28X%5E%7Bc%7D%5Ccap%20D%5E%7Bc%7D%29%3DP%28X%5E%7Bc%7D%7CD%5E%7Bc%7D%29P%28D%5E%7Bc%7D%29%5C%5C%3D%5B1-P%28X%7CD%29%5D%5Ctimes%7B1-%20P%28D%29%5D%5C%5C%3D0.99%5Ctimes%200.12%5C%5C%3D0.1188)
Compute the probability that a randomly selected person is tested negative as follows:


Thus, the probability of the test indicating that the person does not have the disease is 0.1452.
Answer:
A. The larger the sample size the better.
Step-by-step explanation:
Central Limit Theorem
The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean
and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean
and standard deviation 
In this question:
We have to look at the standard error, which is:

This means that an increase in the sample size reduces the standard error, and thus, the larger the sample size the better, and the correct answer is given by option a.
Answer:
x < -10/7
Step-by-step explanation:
Divide both sides by -7. Because this divisor is negative, we must reverse the direction of the inequality sign, obtaining:
-7x < 10
----- < -----
-7 -7
Then x < -10/7