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ALC Exam STA4211 Terms in this set (24) Parameter vs statistic A parameter is a measure that describes the entire population, whereas a statistic describes a sample of the population. Testing for sample means vs proportions sampling distribution probab$7.99
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ALC Exam STA4211 Terms in this set (24) Parameter vs statistic A parameter is a measure that describes the entire population, whereas a statistic describes a sample of the population. Testing for sample means vs proportions sampling distribution probab
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Course
GED - General Educational Development
Institution
GED - General Educational Development
ALC Exam STA4211
Terms in this set (24)
Parameter vs statistic A parameter is a measure that describes the entire population, whereas a statistic describes a sample of the population.
Testing for sample means vs proportions
sampling distribution probability distribution of a given statistic b...
A parameter is a measure that describes the entire population, whereas a statistic
Parameter vs statistic
describes a sample of the population.
Testing for sample means vs proportions
sampling distribution probability distribution of a given statistic based on a random sample
An unbiased estimator is an accurate statistic that's used to approximate a population
parameter. "Accurate" in this sense means that it's neither an overestimate nor an
unbiased estimator underestimate. If an overestimate or underestimate does happen, the mean of the
difference is called a "bias."
bias( thetahat) = E(thetahat) - (thetahat)
In a confidence interval, the range of values above and below the sample statistic is
margin of error
called the margin of error.
The standard error is an estimate of the standard deviation of a statistic. The standard
standard error
error is computed from known sample statistics.
"We are 95% confident that the mean time it takes all workers in this city to get to work
interpreting a confidence interval
is between 18.3 and 23.7 minutes."
increase in sample size or decrease in more precise or narrow confidence interval
confidence level
Type 1- rejecting the null when it is actually true
type 1 and type 2 error
Type 2- fail to reject null when it is actually false (dangerous)
All hypothesis tests ultimately use a p-value to weigh the strength of the evidence. The
p-value is a number between 0 and 1 and interpreted in the following way:
p-value
A small p-value (typically ≤ 0.05) indicates strong evidence against the null hypothesis,
so you reject the null hypothesis.
How do we graphically check whether a data • bell shape
set is a drawn from a normal distribution? • it is symmetric around the point x=u (mu)
ALC Exam STA4211
Blocking factors and nuisance factors provide the mechanism for explaining and
what is the purpose of blocking in an
controlling variation among the experimental units from sources that are not of interest
experimental design
to you and therefore are part of the error or noise aspect of the analysis.
Replication reduces variability in experimental results, increasing their significance and
what are the advantages of replication in an
the confidence level with which a researcher can draw conclusions about an
experiment?
experimental factor.
what are the advantages of randomization of Using randomization is the most reliable method of creating homogeneous treatment
treatments to experimental units? groups, without involving any potential biases or judgments.
Another type of bias that is most apparent in medical experiments is the placebo effect.
Since many patients are confident that a treatment will positively affect them, they react
why are placebo used in medical to a control treatment which actually has no physical affect at all, such as a sugar pill.
experiments? For this reason, it is important to include control, or placebo, groups in medical
experiments to evaluate the difference between the placebo effect and the actual
effect of the treatment.
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