Exam (elaborations)
STA270 EXAM 3 QUESTIONS AND ANSWERS
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STA270 EXAM 3 QUESTIONS AND ANSWERS...
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hypothesis testsuse a known distribution to determine whether a null hypothesis can be rejected
extrasensory perception (ESP)
the controversial claim that perception can occur apart from sensory input;
includes telepathy, clairvoyance, and precognition
how to determine when sample proportion is far enough above 1/5 to provide
evidence of ESF?
with a statistical test
statistical tests
test used to determine whether results from a sample are convincing enough to
allow us to conclude something about the population
how are statistical test framed formally in terms of hypotheses
null and alternative hypothesis
null hypothesis
a statement or idea that can be falsified, or proved wrong; no effect or difference
alternative hypothesis
The hypothesis stating what the researcher is seeking evidence of. It can be
written looking for the difference or change in one direction from the null
hypothesis or both.
how is the alternative hypothesis established
by observing evidence (data) that contradicts the null hypothesis and supports
the alternative hypothesis
true or false: hypotheses are always about population parameters
, true
true or false: null hypothesis always contains an equality
true
true or false: alternative hypotheses always contains an inequality
true
true or false: the type of inequality in the alternative comes from the wording of
the question of interest
true
what is the goal of hypothesis tests
to determine whether the sample data provides enough evidence to refute the
null hypothesis in favor of the alternative
what hypothesis do we want to test
alternative hypothesis
randomization distribution
a collection of statistics from samples stimulated, assuming the null hypothesis
is true
what does a randomization distribution show
shows what statistics are common under random chance
where are randomization distribution centered at
centered at the value of the null hypothesis
true or false: closer to edges means more likely for true results
true
what do we do when the extremity of the observed statistic isn't obvious?
need a formal way of measuring how extreme a statistic would be, if null
hypothesis were true
right-tailed test (>)
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