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©2005 Brooks/Cole - Thomson Learning FIGURES FOR CHAPTER 2 STATISTICAL INFERENCE Click the mouse or use the arrow keys to move to the next page. Use the ESC key to exit this chapter.

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©2005 Brooks/Cole - Thomson Learning Section 2.1 Example 1

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©2005 Brooks/Cole - Thomson Learning Section 2.1 Example 2

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©2005 Brooks/Cole - Thomson Learning Figure 2.1 The normal distribution: Y N(, 2 ).

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©2005 Brooks/Cole - Thomson Learning Section 2.2 Example 6

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©2005 Brooks/Cole - Thomson Learning Figure 2.2 An unbiased estimator has a sampling distribution that is centered over the population parameter. Y is unbiased because its sampling distribution is centered over .

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©2005 Brooks/Cole - Thomson Learning Figure 2.3 The estimator is asymptotically unbiased; its sampling distribution becomes centered over 2 as n → ∞.

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©2005 Brooks/Cole - Thomson Learning Figure 2.4 The variance of Y decreases as the sample size increases.

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©2005 Brooks/Cole - Thomson Learning Figure 2.5 The comparative efficiency of three estimators.

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©2005 Brooks/Cole - Thomson Learning Figure 2.6 Simulated sampling distributions (uniform population).

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©2005 Brooks/Cole - Thomson Learning Figure 2.7 Y i i.i.d.(, 2 ).

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©2005 Brooks/Cole - Thomson Learning Figure 2.8 The least squares estimator is the value of that minimizes the sum of squares function S.

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©2005 Brooks/Cole - Thomson Learning Figure 2.9 p-value for Example 10.

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©2005 Brooks/Cole - Thomson Learning Figure 2.10 Rejection regions.

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©2005 Brooks/Cole - Thomson Learning Figure 2.12 Y is lognormally distributed: ln Y N(, 2 ).

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©2005 Brooks/Cole - Thomson Learning Figure 2.13 Simulated sampling distributions for the statistic t = √n(Y − )/s under nonnormality.

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©2005 Brooks/Cole - Thomson Learning Figure 2.14 A histogram of the monthly return on IBM stock, July 1963–June 1968.

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©2005 Brooks/Cole - Thomson Learning Figure 2.15 Deterministic and stochastic trends.

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©2005 Brooks/Cole - Thomson Learning Figure 2.16 The rate of return on IBM stock, July 1963–June 1968.

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