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:D, “the number of calories...”
Step-by-step explanation:
Answer:
m<N, m<L, m<M
Step-by-step explanation:
The angle that sees the longest side length has the bigger angle measurement
so the angles would be listed as following :
from smallest to largest :
m<N, m<L, m<M
Answer:
Step-by-step explanation:
Thank you
Answer:
a) p=0.39, where p the parameter of interest represent the true proportion of adults that would erase all their personal information online if they could
b) Null hypothesis:
Alternative hypothesis:
Step-by-step explanation:
A hypothesis is defined as "a speculation or theory based on insufficient evidence that lends itself to further testing and experimentation. With further testing, a hypothesis can usually be proven true or false".
The null hypothesis is defined as "a hypothesis that says there is no statistical significance between the two variables in the hypothesis. It is the hypothesis that the researcher is trying to disprove".
The alternative hypothesis is "just the inverse, or opposite, of the null hypothesis. It is the hypothesis that researcher is trying to prove".
On this case the claim that they want to test is: "The true proportion of adults that would erase all their personal information online if they could is 0.39 or 39%". So we want to check if the population proportion is different from 0.39 or 0.39%, so this needs to be on the alternative hypothesis and on the null hypothesis we need to have the complement of the alternative hypothesis.
Part a. Express the original claim in symbolic form. Let the parameter represent the adults that would erase their personal information.
p=0.39, where p the parameter of interest represent the true proportion of adults that would erase all their personal information online if they could
Part b. Identify the null and alternative hypotheses.
Null hypothesis:
And for the alternative hypothesis we have
Alternative hypothesis: