Ch 14 - Introduction to Inference Flashcards
If you picked different samples from a population, you would probably get
different sample means ( x̅ ) and virtually none of them would actually equal the true population mean, m.
If the population is N(μ,σ), the sampling distribution is _____
If not, the sampling distribution is ____
N(μ,σ/√n).
~N(μ,σ/√n) if n is large enough.
We take one random sample of size n, and rely on the known properties of the sampling distribution.
When we take a random sample, we can compute the ____ and _____.
Based on the ~68-95-99.7% rule, we can expect that ____
sample mean and an interval of size plus-or-minus 2σ/√n about the mean.
~95% of all intervals computed with this method capture the parameter μ.
A confidence interval is a
range of values with an associated confidence level, C.
μ is expected to fall within C% of the confidence intervals constructed.
This confidence level gives the expected percentage of intervals which will likely contain the unknown population parameter.
A confidence interval (“CI”) can be expressed as
a center ± a margin of error m: μ within x̅ ± m
an interval: μ within (x̅ − m) to (x̅ + m)
The confidence level C (in %) represents an area of
corresponding size C under the sampling distribution.
When taking a random sample from a Normal population with known standard deviation σ, a level C confidence interval for µ is
How do we find z* values?
We can use a table of z and t values (Table C). For a given confidence level C, the appropriate z* value is listed in the same column.
____ depends on Z*
The confidence level C determines the value of z* (in Table C).
The margin of error also depends on z*.
precession and accuracy with C level
