Answer:
The answer would be 6/18 or 3/9
Step-by-step explanation:
Answer:
The sampling of this study is bias
Step-by-step explanation:
Sampling bias is a bias that is gotten during sampling where some members of the population have a lower representation or probability than others in the sample pool. In this case, only the residents living near a river was sampled, and because they are subjected to relatively the same conditions (living near a river), the result of the study will not be a true representation of every member of the town because the people living far away from the river will most likely have different opinions due to their different environmental exposure than the people living close to the river. The correct thing to have been done for the result to be reliable and accurate will be to sample at random, people in the two both close to and far away from the river, or to sample equal number of people each living close to and far away from the river.
Another example of sampling bias is a study to determine the effect of alcohol on pregnancy in women in America, and only pregnant white women who drink are sampled, leaving out Black or Hispanic women, what ever result gotten in the study may hold true for white women in America, but it may not hold true for every woman in America
Answer:
22.
Step 1: Find area of inner square = 4 ft × 12 ft = 48ft2
Step 2: Find area of outer shape =
25 ft +11 ft = 36 cm2
Step 3: Area of shaded region = area of outer shape – area of inner square
= 36 ft2 – 48 ft2
= 12 ft2
Answer:
98.1% chance of being accepted
Step-by-step explanation:
Given:
sample size,n=56
acceptance condition= at most 2 batteries do not meet specifications
shipment size=7000
battery percentage in shipment that do not meet specification= 1%
Applying binomial distribution
<h3>P(x)=∑ᵇₐ=₀ (n!/a!(n-a)!)p^a (1-p)^(n-a)</h3>
In this formula, a is the acceptable number of defectives;
n is the sample size;
p is the fraction of defectives in the population.
Now putting the value
a= 2
n=56
p=0.01
=0.56960+0.32219+0.08949
After summation, we get 0.981 i.e. a 98.1% chance of being accepted. As this is such a high chance, we can expect many of the shipments like this to be accepted!
Answer:
(3,1)
Step-by-step explanation:
