FIGURES FOR CHAPTER 2

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FIGURES FORCHAPTER 2
STATISTICAL INFERENCE
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Section 2.1 Example 1
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Section 2.1 Example 2
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Figure 2.1The normal distribution Y N(m ,s2).
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Section 2.2 Example 6
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Figure 2.2An unbiased estimator has a sampling
distribution that is centered over the population
parameter. Y is unbiased because its sampling
distribution is centered over m.
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Figure 2.3The estimator is asymptotically
unbiased its sampling distribution becomes
centered over s2 as n?8.
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Figure 2.4The variance of Y decreases as the
sample size increases.
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Figure 2.5The comparative efficiency of three
estimators.
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Figure 2.6Simulated samplingdistributions
(uniformpopulation).
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Figure 2.7Yi i.i.d.(m,s2).
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Figure 2.8The least squares estimator is the
value of m that minimizes the sum of squares
function S.
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Figure 2.9p-value for Example 10.
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Figure 2.10Rejection regions.
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Figure 2.12Y is lognormally distributed ln Y
N(m , s2).
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Figure 2.13Simulated samplingdistributions for
the statistic t vn(Y - m)/sunder
nonnormality.
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Figure 2.14A histogram of the monthly return on
IBM stock, July 1963June 1968.
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Figure 2.15Deterministic and stochastic trends.
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Figure 2.16The rate of return on IBM stock, July
1963June 1968.