Answer:
<u>Type I error: </u>D. Reject the null hypothesis that the percentage of adults who retire at age 65 is less than or equal to 62 % when it is actually true.
<u>Type II error: </u>A. Fail to reject the null hypothesis that the percentage of adults who retire at age 65 is less than or equal to 62 % when it is actually false.
Step-by-step explanation:
A type I error happens when a true null hypothesis is rejected.
A type II error happens when a false null hypothesis is failed to be rejected.
In this case, where the alternative hypothesis is that "the percentage of adults who retire at age 65 is greater than 62%", the null hypothesis will state that this percentage is not significantly greater than 62%.
A type I error would happen when the conclusion is that the percentage is greater than 62%, when in fact it is not.
A type II error would happen when there is no enough evidence to claim that the percentage is greater than 62%, even when the percentage is in fact greater than 62% (but we still don't have evidence to prove it).
Answer:
sampling error is not known
Step-by-step explanation:
Probability sampling may be defined as the sampling technique where the researcher or the experimenter chooses the samples from the larger population group using such method that is based on probability theory.
While non probability sampling is the kind of sampling method which is not feasible or possible for random sampling. It is the opposite of the probability sampling method. Here, the odds of any individual to be selected for any sample cannot be calculated.
The difference between the two is that the sampling error is not known.
The answer would be 458, 752
B because of the y to the zero? Anyone wanna back me up?
Answer:
Scalene and obtuse
Step-by-step explanation:
The triangle is scalene because all the sides are not equal, and it is obtuse because the central angle is greater than 90 degrees.