figures for chapter 2

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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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STATISTICAL INFERENCE. FIGURES FOR CHAPTER 2. Click the mouse or use the arrow keys to move to the next page. Use the ESC key to exit this chapter. Section 2.1 Example 1. Section 2.1 Example 2. Figure 2.1 The normal distribution: Y ~ N ( m , s 2 ). Section 2.2 Example 6. - PowerPoint PPT Presentation

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Page 1: FIGURES FOR CHAPTER 2

©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.

Page 2: FIGURES FOR CHAPTER 2

©2005 Brooks/Cole - Thomson Learning

Section 2.1 Example 1

Page 3: FIGURES FOR CHAPTER 2

©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 2.2An unbiased estimator has a sampling distribution that is centered over the population parameter. Y is unbiased because its sampling distribution is centered over .

Page 7: FIGURES FOR CHAPTER 2

©2005 Brooks/Cole - Thomson Learning

Figure 2.3The 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 samplingdistributions (uniformpopulation).

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©2005 Brooks/Cole - Thomson Learning

Figure 2.7

Yi i.i.d.(,2).

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©2005 Brooks/Cole - Thomson Learning

Figure 2.8The 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 samplingdistributions for the statistic t = √n(Y − )/sunder nonnormality.

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©2005 Brooks/Cole - Thomson Learning

Figure 2.14A histogram of the monthly return on IBM stock, July 1963–June 1968.

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©2005 Brooks/Cole - Thomson Learning

Figure 2.15Deterministic and stochastic trends.

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©2005 Brooks/Cole - Thomson Learning

Figure 2.16The rate of return on IBM stock, July 1963–June 1968.