Answers to Tutorial 8 Questions
1.
Which hypothesis, the null or the alternative, is the status quo hypothesis? Which is the
research hypothesis? What hypothesis is held true during testing till rejected by strong
evidence? Why do we keep
α
, the level of significance, low usually?
Answer:
During testing, the null hypothesis is held true until there is sufficient statistical evidence to
prove otherwise.
As the null hypothesis represents the status quo or existing belief, incorrectly reject the null
hypothesis when actually it is true, namely making a Type I error, will usually lead to
serious consequences, thus we usually control the chance of making such an error to be low.
2.
What is the difference between Type I and Type II errors in hypothesis testing? Are
α
and
β
conditional probabilities and if so, what are their conditions?
Answer:
A Type I error is rejecting the null hypothesis (Ho) when it is true.
A Type II error is failing to reject the null hypothesis when it is false
α
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 Spring '10
 woo
 Statistics, Null hypothesis, Hypothesis testing, Statistical hypothesis testing, Type I and type II errors

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