T/F: Confidence intervals for means are highly susceptible to the effects
of outliers. - ANSWERS-True. This is why it's a good idea to visualize
the data using boxplots or dotplots if we are dealing with a small sample
size. We have to ensure that there are no outliers or any other reason to
think that the original population was not normally distributed.
T/F: Probability applies to statistics. - ANSWERS-True.
T/F: Probability applies to parameters. - ANSWERS-False. Probability
applies to statistics, not parameters.
T/F: A 95% confidence interval suggests that, if we use it over and over
again for various samples, we will make correct inferences 95% of the
time in the long-run. - ANSWERS-True.
T/F: Confidence intervals can be used to assess the probability of
individual outcomes. - ANSWERS-False. Confidence intervals are
constructed to describe *POPULATION* means, not sample means or
individual observations.
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, STA 2023 EXAM 2 LATEST
T/F: Confidence intervals can be used to assess the likelihood of getting
a certain sample mean. - ANSWERS-False. Confidence intervals are
constructed to describe *POPULATION* means, not sample means or
individual observations.
Minimum Sample Size to Achieve a Particular Confidence Level When
Estimating a Population Proportion - ANSWERS-n= z^2 • p̂(1-p̂)/m^2
Minimum Sample Size to Achieve a Particular Confidence Level When
Estimating a Population Mean - ANSWERS-n= (zs/m)^2
Suppose you are calculating the min. sample size for a study intended to
estimate the pop. prop. and you have no idea what value you should use
for the sample proportion. What value should you use? - ANSWERS-
p̂=0.5
When calculating the min. sample size needed for estimating a
proportion or mean, you always round (down/up). - ANSWERS-up
Significance Tests - ANSWERS-With significance tests, we begin with
a preconceived notion or a claim about the value of a parameter. We
take a sample and use the results to determine whether the results
support or do not support the claim.
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