1. Slide 1 Copyright © 2004 Pearson Education, Inc.

2. Slide 2 Copyright © 2004 Pearson Education, Inc. Created by Erin Hodgess, Houston, Texas Section 14-1 through 14-3 Projects, Procedure and Perspective

3. Slide 3 Copyright © 2004 Pearson Education, Inc. A Statistics Group Project  Group/Individual  Oral Report  Written Report 1. List of data collected 2. Description of the method of analysis 3. Relevant graphs and/or statistics, including STATDISK,Minitab, Excel, or TI-83 displays 4. Statement of conclusion 5. Reasons why the results might not be correct, along with a description of ways in which the study could be improved, given sufficient time and money.

4. Slide 4 Copyright © 2004 Pearson Education, Inc. Which Procedure Applies ?  Data Collection  Exploring, Comparing, Describing  Inferences: Estimating Parameters and Hypothesis Testing

5. Slide 5 Copyright © 2004 Pearson Education, Inc. Interval or Ratio (such as heights, weights) Nominal (data consisting of proportions or frequency counts for different categories Ordinal (such as data consisting of ranks) What is the level of measurement of the data? 1-2 Level of Measurement FIGURE 14-1 Inferential Statistics: Applicable Text Sections

6. Slide 6 Copyright © 2004 Pearson Education, Inc. Interval or Ratio (such as heights, weights) One Population Nominal (data consisting of proportions or frequency counts for different categories More than Two Populations Chap. 11, 12-5 Ordinal (such as data consisting of ranks) Two Populations What is the level of measurement of the data? 1-2 Level of Measurement Number of Populations FIGURE 14-1 Inferential Statistics: Applicable Text Sections

7. Slide 7 Copyright © 2004 Pearson Education, Inc. Variance Means: 8-3, 8-4 Correlation, Regression Chap. 9, 12-6 Variances: 8-5 Interval or Ratio (such as heights, weights) One Population Nominal (data consisting of proportions or frequency counts for different categories More than Two Populations Chap. 11, 12-5 Mean Ordinal (such as data consisting of ranks) Two Populations What is the level of measurement of the data? 1-2 Level of Measurement Number of Populations Claim or Parameter FIGURE 14-1 Inferential Statistics: Applicable Text Sections

8. Slide 8 Copyright © 2004 Pearson Education, Inc. Variance Means: 8-3, 8-4 Correlation, Regression Chap. 9, 12-6 Variances: 8-5 Interval or Ratio (such as heights, weights) One Population Nominal (data consisting of proportions or frequency counts for different categories More than Two Populations Chap. 11, 12-5 Mean Estimating with Confidence Interval: 6-3, 6-4 Hypothesis Testing with 7-4, 7-5 Ordinal (such as data consisting of ranks) Two Populations What is the level of measurement of the data? 1-2 Level of Measurement Number of Populations Claim or Parameter Inference FIGURE 14-1 Inferential Statistics: Applicable Text Sections

9. Slide 9 Copyright © 2004 Pearson Education, Inc. Variance Means: 8-3, 8-4 Correlation, Regression Chap. 9, 12-6 Variances: 8-5 Interval or Ratio (such as heights, weights) One Population Nominal (data consisting of proportions or frequency counts for different categories More than Two Populations Chap. 11, 12-5 Mean Estimating with Confidence Interval: 6-3, 6-4 Hypothesis Testing with Large Sample: 7-2, 7-3 Estimating with Confidence Interval: 6-5 Hypothesis Testing: 7-6 Ordinal (such as data consisting of ranks) Two Populations What is the level of measurement of the data? 1-2 Level of Measurement Number of Populations Claim or Parameter Inference FIGURE 14-1 Inferential Statistics: Applicable Text Sections

10. Slide 10 Copyright © 2004 Pearson Education, Inc. Variance Means: 8-3, 8-4 Correlation, Regression Chap. 9, 12-6 Variances: 8-5 Interval or Ratio (such as heights, weights) One Population Nominal (data consisting of proportions or frequency counts for different categories More than Two Populations Chap. 11, 12-5 One Population 12-2 Two Populations Mean Estimating with Confidence Interval: 6-3, 6-4 Hypothesis Testing with Large Sample: 7-4, 7-5 Estimating with Confidence Interval: 6-5 Hypothesis Testing: 7-6 More than Two Populations 12-5 Ordinal (such as data consisting of ranks) Two Populations What is the level of measurement of the data? 1-2 Level of Measurement Number of Populations Claim or Parameter Inference FIGURE 14-1 Inferential Statistics: Applicable Text Sections

11. Slide 11 Copyright © 2004 Pearson Education, Inc. Variance Means: 8-3, 8-4 Correlation, Regression Chap. 9, 12-6 Variances: 8-5 Interval or Ratio (such as heights, weights) One Population Nominal (data consisting of proportions or frequency counts for different categories More than Two Populations Chap. 11, 12-5 One Population 12-2 Two Populations Mean Independent: 12-4 Matched Pairs: 12-3 Estimating with Confidence Interval: 6-3, 6-4 Hypothesis Testing with Large Sample: 7-4, 7-5 Estimating with Confidence Interval: 6-5 Hypothesis Testing: 7-6 Ordinal (such as data consisting of ranks) Two Populations What is the level of measurement of the data? 1-2 Level of Measurement Number of Populations Claim or Parameter Inference More than Two Populations 12-5 FIGURE 14-1 Inferential Statistics: Applicable Text Sections

12. Slide 12 Copyright © 2004 Pearson Education, Inc. Variance Means: 8-3, 8-4 Correlation, Regression Chap. 9, 12-6 Variances: 8-5 Interval or Ratio (such as heights, weights) One Population Nominal (data consisting of proportions or frequency counts for different categories More than Two Populations Chap. 11, 12-5 One Population 12-2 Two Populations Mean Independent: 12-4 Matched Pairs: 12-3 Estimating with Confidence Interval: 6-3, 6-4 Hypothesis Testing with Large Sample: 7-4, 7-35 Estimating with Confidence Interval: 6-5 Hypothesis Testing: 7-6 Ordinal (such as data consisting of ranks) Two Populations Frequency Counts for Categories Proportions What is the level of measurement of the data? 1-2 Level of Measurement Number of Populations Claim or Parameter Inference More than Two Populations 12-5 FIGURE 14-1 Inferential Statistics: Applicable Text Sections

13. Slide 13 Copyright © 2004 Pearson Education, Inc. Variance Means: 8-3, 8-4 Correlation, Regression Chap. 9, 12-6 Variances: 8-5 Interval or Ratio (such as heights, weights) One Population Nominal (data consisting of proportions or frequency counts for different categories More than Two Populations Chap. 11, 12-5 One Population 12-2 Two Populations Mean Contingency Table (multiple rows, columns) 10-3 Independent: 12-4 Matched Pairs: 12-3 Multinomial (one row) 10-2 Estimating with Confidence Interval: 6-3, 6-4 Hypothesis Testing with Large Sample: 7-4, 7-5 Estimating with Confidence Interval: 6-5 Hypothesis Testing: 7-6 Ordinal (such as data consisting of ranks) Two Populations Frequency Counts for Categories Proportions What is the level of measurement of the data? 1-2 Level of Measurement Number of Populations Claim or Parameter Inference More than Two Populations 12-5 FIGURE 14-1 Inferential Statistics: Applicable Text Sections

14. Slide 14 Copyright © 2004 Pearson Education, Inc. Variance Means: 8-3, 8-4 Correlation, Regression Chap. 9, 12-6 Variances: 8-5 Interval or Ratio (such as heights, weights) One Population Nominal (data consisting of proportions or frequency counts for different categories More than Two Populations Chap. 11, 12-5 One Population 12-2 Two Populations Mean Contingency Table (multiple rows, columns) 10-3 Two Populations: 8-2 Independent: 12-4 Matched Pairs: 12-3 Multinomial (one row) 10-2 One Population Estimating with Confidence Interval: 6-3, 6-4 Hypothesis Testing with Large Sample: 7-4, 7-5 Estimating with Confidence Interval: 6-6 Hypothesis Testing: 7-6 Ordinal (such as data consisting of ranks) Two Populations Frequency Counts for Categories Proportions What is the level of measurement of the data? 1-2 Level of Measurement Number of Populations Claim or Parameter Inference More than Two Populations 12-5 FIGURE 14-1 Inferential Statistics: Applicable Text Sections

15. Slide 15 Copyright © 2004 Pearson Education, Inc. FIGURE 14-1 Inferential Statistics: Applicable Text Sections

16. Slide 16 Copyright © 2004 Pearson Education, Inc. Perspective 1. Be able to interpret results. Saying “we reject the null hypothesis is meaningless without a clear understanding of the hypothesis testing procedure. 2. Use common sense. Computers don’t think. We do. 3. Look for the truth. H.G. Wells once said that “statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write.” That day is now.