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Chapter 7
Inferences Based on a Single Sample:
Estimation with ConFdence Intervals
7.1
Identifying and Estimating the Target Parameter
DeFnition 7.1 Target Parameter:
The unknown population parameter (mean or pro
portion) that we are interested in estimating is called the target parameter.
Parameter
Phrases
Data Type
μ
Mean (average)
quantitative
p
Proportion (fraction, percentage)
qualitative
DeFnition 7.2 Point Estimator:
A point estimator of a population parameter is a rule
that tells you how to use the sample data to calculate a single number that can be used as an
estimate of the population parameter. For example, the sample mean ¯
x
is a point estimator
for the population mean
μ
.
DeFnition 7.3 Interval Estimator:
An interval estimator of a population parameter is a
rule that tells you how to calculate two numbers; an upper and a lower limit, based on the
sample data, forming an interval within which the parameter is expected to lie. This pair
of numbers is called an interval estimate or con±dence interval. The large number which
located at the upper end of the interval, is called the
upper conFdence limit (UCL)
and
the number that located at the lower extreme of the interval, is called the
lower conFdence
limit (LCL)
.
ConFdence width:
The di²erence between UCL and LCL is called con±dence width. That
is
Con±dence width =
UCL
−
LCL
35
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View Full Document7.2
Confdence Interval For a Population Mean: Nor
mal (z) Statistic
Defnition 7.4 Confdence Coeﬃcient:
Confdence coeﬃcient is the probability that a
randomly selected confdence interval will enclose the parameter. The confdence coeﬃcient
measures the proportion oF samples that produce a confdence interval containing the pop
ulation parameter. A good confdence interval is as narrow as possible and has a confdence
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 Fall '08
 McGuckian
 Statistics

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