1. Slide Slide 1 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Lecture Slides Elementary Statistics Tenth Edition and the Triola Statistics Series by Mario F. Triola

2. Slide Slide 2 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Chapter 15 Projects, Procedures, Perspectives 15-1 Projects 15-2 Procedures 15-3 Perspectives

3. Slide Slide 3 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Section 15-1 Projects Created by Erin Hodgess, Houston, Texas Revised to accompany 10th Edition, Jim Zimmer, Chattanooga State, Chattanooga, TN

4. Slide Slide 4 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Key Concept This section includes suggestions for a final project in the introductory statistics course. One fantastic advantage of this course is that it deals with skills and concepts that can be applied immediately to the real world. After only one semester, students are able to conduct their own studies.

5. Slide Slide 5 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Projects  Group/Individual Topics can be assigned to individuals, but group projects are particularly effective because they help develop the interpersonal skills that are so necessary in today’s working environment.  Oral Report A 10- to 15-minute-long class presentation should involve all group members in a coordinated effort to clearly describe the important components of the study.

6. Slide Slide 6 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Projects  Written Report A brief written report should include the following: 1. List of data collected along with description of how the data were obtained. 2. Description of the method of analysis. 3. Relevant graphs and/or statistics, including STATDISK, Minitab, Excel, or TI-83/84 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.

7. Slide Slide 7 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Projects  Large Classes or Online Classes: Posters or PowerPoint Some classes are too large for individual projects or group projects with three or four or five students per group. Some online classes are not able to meet as a group. For such cases, reports of individual or small group projects can be presented through posters or PowerPoint presentations.  Surveys can be an excellent source of data.  Project Topic suggestions are listed in the text.

8. Slide Slide 8 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Section 15-2 Procedures Created by Erin Hodgess, Houston, Texas Revised to accompany 10th Edition, Jim Zimmer, Chattanooga State, Chattanooga, TN

9. Slide Slide 9 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Key Concept This section describes a general procedure for conducting a statistical analysis of data.

10. Slide Slide 10 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Procedures  Exploring, Comparing, Describing After collecting data, address the following: 1. Center: Find the mean and median. 2. Variation: Find the range and standard deviation. 3. Distribution: Construct a histogram and a normal quantile plot. 4. Outliers: Identify any sample values that lie very far away from the vast majority of the others. 5. Time: Determine if the population is stable or if its characteristics are changing over time.

11. Slide Slide 11 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Procedures  Inferences: Estimating Parameters and Hypothesis Testing Here are some key questions that should be answered: What is the level of measurement (nominal, ordinal, interval, ratio) of the data? Does the study involve one, two, or more populations? What is the relevant parameter (mean, standard deviation, proportion)? Is the population standard deviation known? Is there reason to believe that the population is normally distributed? What is the basic question or issue to address?

12. Slide Slide 12 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. What is the level of measurement of the data? 1-2 Level of Measurement Nominal (data consisting of proportions or frequency counts for different categories) Ordinal (such as data consisting of ranks) Interval or Ratio (such as heights, weights) FIGURE 15-1 Selecting the Appropriate Procedure

13. Slide Slide 13 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. One Population More than Two Populations Chap. 12, 13-5 Two Populations What is the level of measurement of the data? 1-2 Level of Measurement Number of Populations Nominal (data consisting of proportions or frequency counts for different categories) Ordinal (such as data consisting of ranks) Interval or Ratio (such as heights, weights) FIGURE 15-1 Selecting the Appropriate Procedure

14. Slide Slide 14 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Variance One Population More than Two Populations Chap. 12, 13-5 Mean Two Populations What is the level of measurement of the data? 1-2 Level of Measurement Number of Populations Claim or Parameter Nominal (data consisting of proportions or frequency counts for different categories) Ordinal (such as data consisting of ranks) Interval or Ratio (such as heights, weights) FIGURE 15-1 Selecting the Appropriate Procedure

15. Slide Slide 15 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Variance Means: 9-3, 9-4 Correlation, Regression Chap. 10, 13-6 Variances: 9-5 One Population More than Two Populations Chap. 12, 13-5 Mean Two Populations What is the level of measurement of the data? 1-2 Level of Measurement Number of Populations Claim or Parameter Nominal (data consisting of proportions or frequency counts for different categories) Ordinal (such as data consisting of ranks) Interval or Ratio (such as heights, weights) FIGURE 15-1 Selecting the Appropriate Procedure

16. Slide Slide 16 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Estimating with Confidence Interval: 7-3, 7-4 Hypothesis Testing with Large Sample: 8-4, 8-5 Variance Means: 9-3, 9-4 Correlation, Regression Chap. 10, 13-6 Variances: 9-5 One Population More than Two Populations Chap. 12, 13-5 Mean Two Populations What is the level of measurement of the data? 1-2 Level of Measurement Number of Populations Claim or Parameter Inference Nominal (data consisting of proportions or frequency counts for different categories) Ordinal (such as data consisting of ranks) Interval or Ratio (such as heights, weights) FIGURE 15-1 Selecting the Appropriate Procedure

17. Slide Slide 17 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Estimating with Confidence Interval: 7-3, 7-4 Hypothesis Testing with Large Sample: 8-4, 8-5 Estimating with Confidence Interval: 7-5 Variance Means: 9-3, 9-4 Correlation, Regression Chap. 10, 13-6 Variances: 9-5 One Population More than Two Populations Chap. 12, 13-5 Mean Hypothesis Testing: 8-6 Two Populations What is the level of measurement of the data? 1-2 Level of Measurement Number of Populations Claim or Parameter Inference Nominal (data consisting of proportions or frequency counts for different categories) Ordinal (such as data consisting of ranks) Interval or Ratio (such as heights, weights) FIGURE 15-1 Selecting the Appropriate Procedure

18. Slide Slide 18 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Estimating with Confidence Interval: 7-3, 7-4 Hypothesis Testing with Large Sample: 8-4, 8-5 Estimating with Confidence Interval: 7-5 Variance Means: 9-3, 9-4 Correlation, Regression Chap. 10, 13-6 Variances: 9-5 One Population More than Two Populations Chap. 12, 13-5 One Population 13-2 Two Populations Mean Hypothesis Testing: 8-6 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 13-5 Nominal (data consisting of proportions or frequency counts for different categories) Ordinal (such as data consisting of ranks) Interval or Ratio (such as heights, weights) FIGURE 15-1 Selecting the Appropriate Procedure

19. Slide Slide 19 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Estimating with Confidence Interval: 7-3, 7-4 Hypothesis Testing with Large Sample: 8-4, 8-5 Estimating with Confidence Interval: 7-5 Variance Means: 9-3, 9-4 Correlation, Regression Chap. 10, 13-6 Variances: 9-5 One Population More than Two Populations Chap. 12, 13-5 One Population 13-2 Two Populations Mean Independent: 13-4 Matched Pairs: 13-3 Hypothesis Testing: 8-6 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 13-5 Nominal (data consisting of proportions or frequency counts for different categories) Ordinal (such as data consisting of ranks) Interval or Ratio (such as heights, weights) FIGURE 15-1 Selecting the Appropriate Procedure

20. Slide Slide 20 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Estimating with Confidence Interval: 7-3, 7-4 Hypothesis Testing with Large Sample: 8-4, 8-5 Estimating with Confidence Interval: 7-5 Variance Means: 9-3, 9-4 Correlation, Regression Chap. 10, 13-6 Variances: 9-5 One Population More than Two Populations Chap. 12, 13-5 One Population 13-2 Two Populations Mean Independent: 13-4 Matched Pairs: 13-3 Hypothesis Testing: 8-6 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 13-5 Nominal (data consisting of proportions or frequency counts for different categories) Ordinal (such as data consisting of ranks) Interval or Ratio (such as heights, weights) FIGURE 15-1 Selecting the Appropriate Procedure

21. Slide Slide 21 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Estimating with Confidence Interval: 7-3, 7-4 Hypothesis Testing with Large Sample: 8-4, 8-5 Estimating with Confidence Interval: 7-5 Variance Means: 9-3, 9-4 Correlation, Regression Chap. 10, 13-6 Variances: 9-5 One Population More than Two Populations Chap. 12, 13-5 One Population 13-2 Two Populations Mean Contingency Table (multiple rows, columns) 11-3 Independent: 13-4 Matched Pairs: 13-3 Multinomial (one row) 11-2 Hypothesis Testing: 8-6 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 13-5 Nominal (data consisting of proportions or frequency counts for different categories) Ordinal (such as data consisting of ranks) Interval or Ratio (such as heights, weights) FIGURE 15-1 Selecting the Appropriate Procedure

22. Slide Slide 22 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Estimating with Confidence Interval: 7-3, 7-4 Hypothesis Testing with Large Sample: 8-4, 8-5 Estimating with Confidence Interval: 7-5 Variance Means: 9-3, 9-4 Correlation, Regression Chap. 10, 13-6 Variances: 9-5 One Population More than Two Populations Chap. 12, 13-5 One Population 13-2 Two Populations Mean Contingency Table (multiple rows, columns) 11-3 Two Populations: 9-2 Independent: 13-4 Matched Pairs: 13-3 Multinomial (one row) 11-2 One Population Hypothesis Testing: 8-6 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 13-5 Nominal (data consisting of proportions or frequency counts for different categories) Ordinal (such as data consisting of ranks) Interval or Ratio (such as heights, weights) FIGURE 15-1 Selecting the Appropriate Procedure

23. Slide Slide 23 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Estimating with Confidence Interval: 7-3, 7-4 Hypothesis Testing with Large Sample: 8-4, 8-5 Estimating with Confidence Interval: 7-5 Estimating Proportion with Confidence Interval: 7-2 Variance Means: 9-3, 9-4 Correlation, Regression Chap. 10, 13-6 Variances: 9-5 One Population More than Two Populations Chap. 12, 13-5 One Population 13-2 Two Populations Mean Contingency Table (multiple rows, columns) 11-3 Two Populations: 9-2 Independent: 13-4 Matched Pairs: 13-3 Multinomial (one row) 11-2 One Population Hypothesis Testing: 8-6 Hypothesis Testing: 8-3, 13-2 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 13-5 Nominal (data consisting of proportions or frequency counts for different categories) Ordinal (such as data consisting of ranks) Interval or Ratio (such as heights, weights) FIGURE 15-1 Selecting the Appropriate Procedure

24. Slide Slide 24 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Section 15-3 Perspectives Created by Erin Hodgess, Houston, Texas Revised to accompany 10th Edition, Jim Zimmer, Chattanooga State, Chattanooga, TN

25. Slide Slide 25 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Key Concept No single introductory statistics course can transform anyone into an expert statistician. Know that professional help is available from expert statisticians, and this introductory statistics course will help you in discussions with one of these experts.

26. Slide Slide 26 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Perspective  Successful completion of an introductory statistics course results in benefits far beyond the attainment of credit toward a college degree. Improved job marketability Ability to critically analyze reports in media and journals Understanding of the basic concepts of probability and chance Knowledge of importance of statistical procedures

27. Slide Slide 27 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Perspective  Remember that expert ability in analyzing statistics is of little value if good sampling techniques are not employed to develop the sample.  Although computers and calculators are good at yielding results, careful interpretation of the results are required.  Successful Completion of an introductory statistics course can enable students to grow as individuals and professionals and become people who are truly educated.