# Discussion Post Wk3 Secondary Questions

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Data Analytics
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1.
What are some of the errors that can occur while testing the hypothesis?
Two main errors can occur during the testing of a hypothesis. One of the two errors is type
I error, it is as a result of a researcher rejecting a null hypothesis that should not be rejected, while
a type II error is not rejecting false null hypothesis.
How would you go about mitigating these errors?
To mitigate a type I error, we set smaller levels of significance, this lowers the probability
of type I error. On the other hand, mitigation of a type II error is by choosing a large but reasonable
sample size that is representative of the population for the hypothesis test.
2.
What are some of the errors that can occur while testing the hypothesis?
A type I and type II error are the ones associated with testing hypothesis. A type I error
results from rejecting a true null hypothesis. A type II error is as a result of not rejecting a null
hypothesis that is false and should be rejected.
The most serious error in hypothesis testing.
The most serious of the two errors is a type I error because of the impact of its conclusion
that there is a treatment effect when there is none. The outcome of this conclusion is that no further
test is to be performed on the data, and theories can be formulated using the false conclusion. A
type II error is not as serious because in a conclusion of no treatment effect is found, there is room
for further analysis.

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1. What are some of the errors that can occur while testing the hypothesis? Two main errors can occur during the testing of a hypothesis. One of the two errors is type I error, it is as a result of a researcher rejecting a null hypothesis that should not be rejected, while a type II error is not rej ...
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