5. Mean projections and mean student scores are calculated. Student Projection1 Student Score 1 Student Projection 2 Student Score 2 Student Projection 3 Student Score 3 Student Projection 4 Student Score 4 Student Projection 5 Your School Student Score 5 Student Projection 6 Student Score 6 Student Projection 7 Student Score 7 Student Projection 8 Student Score 8 Student Projection 9 Student Score 9 Student Projection 10 Student Score 10 Student Projection 11 Student Score 11 Student Projection 12 Student Score 12 Student Projection 13 Student Score 13 Student Projection 14 Student Score 14 Student Projection 15 Student Score 15 Student Projection 16 Student Score 16 Student Projection 17 Student Score 17 Student Projection 18 Student Score 18 Student Projection 19 Student Score 19 Student Projection 20 Student Score 20 Mean Projected Score Mean Student Score Copyright © 2003. Battelle for Kids
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The Contestants… Team 1: Team 2: Team 3: Team 4: Team 5: Team 6: Team 7: Team 8: Team 9: Team 10: Team 11: Team 12: Team 13: Team 14: Team 15: Team 16: Team 17: Team 18: Team 19: Team 20: Team 21: Team 22: Team 23: Team 24: Team 25: Team 26: Team 27: Team 28: Back to the Contest…
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Expected Counts in Two-Way Tables Finding the expected counts is not that difficult, as the following example illustrates. The overall proportion of French wine bought during the study was 99/243 = 0.407. So the expected counts of French wine bought under each treatment are: 99 99 experiment is that there’s no 99 The null: hypothesis in theFrench wine and music No music ×84 =34.22 music : ×75 =30.56 Italian music : ×84 =34.22 243 243 243 difference in the distribution of wine purchases in the store when no music, French accordion music, or Italian string music is played. To find the proportion expected counts, wewine startbought by assuming thatstudy H0 is was true.31/243 We can=see The overall of Italian during the 0.128. So two-way the expected wine bought under each treatment from the table counts that 99ofofItalian the 243 bottles of wine bought during theare: study were 31 French wines. French music : 31 ×75 =9.57 Italian music : 31 ×84 =10.72 No music : ×84 =10.72 243 243 243 If the specific type of music that’s playing has no effect on wine purchases, the proportion of French The overall proportion of Other wine bought during the study was 113/243 = wine sold under each music 0.465. So the expected countscondition of Other wine bought under each treatment are: should be113 99/243 = 0.407. 113 113 No music : 243 ×84 =39.06 French music : 243 ×75 =34.88 Italian music : 243 ×84 =39.06 12
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Expected Counts in Two-Way Tables 9 Finding the expected counts is not that difficult, as the following example illustrates. The overall proportion of French wine bought during the study was 99/243 = 0.407. So the expected counts of French wine bought under each treatment are: 99 99 experiment is that there’s no 99 The null: hypothesis in theFrench wine and music No music ×84 =34.22 music : ×75 =30.56 Italian music : ×84 =34.22 243 243 243 difference in the distribution of wine purchases in the store when no music, French accordion music, or Italian string music is played. To find the proportion expected counts, wewine startbought by assuming thatstudy H0 is was true.31/243 We can=see The overall of Italian during the 0.128. So two-way the expected wine bought under each treatment from the table counts that 99ofofItalian the 243 bottles of wine bought during theare: study were 31 French wines. 31 31 No music : 243 ×84 =10.72 French music : ×75 =9.57 Italian music : ×75 =34.88 Italian music : 243 243 ×84 =10.72 If the specific type of music that’s playing has no effect on wine purchases, the proportion of French The overall proportion of Other wine bought during the study was 113/243 = wine sold under each music 0.465. So the expected countscondition of Other wine bought under each treatment are: should be113 99/243 = 0.407. 113 113 No music : 243 ×84 =39.06 French music : 243 243 ×84 =39.06
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Expected Counts in Two-Way Tables 12 Finding the expected counts is not that difficult, as the following example illustrates. The overall proportion of French wine bought during the study was 99/243 = 0.407. So the expected counts of French wine bought under each treatment are: 99 99 experiment is that there’s no 99 The null: hypothesis in theFrench wine and music No music ×84 =34.22 music : ×75 =30.56 Italian music : ×84 =34.22 243 243 243 difference in the distribution of wine purchases in the store when no music, French accordion music, or Italian string music is played. To find the proportion expected counts, wewine startbought by assuming thatstudy H0 is was true.31/243 We can=see The overall of Italian during the 0.128. So two-way the expected wine bought under each treatment from the table counts that 99ofofItalian the 243 bottles of wine bought during theare: study were 31 French wines. 31 31 No music : 243 ×84 =10.72 French music : ×75 =9.57 Italian music : ×75 =34.88 Italian music : 243 243 ×84 =10.72 If the specific type of music that’s playing has no effect on wine purchases, the proportion of French The overall proportion of Other wine bought during the study was 113/243 = wine sold under each music 0.465. So the expected countscondition of Other wine bought under each treatment are: should be113 99/243 = 0.407. 113 113 No music : 243 ×84 =39.06 French music : 243 243 ×84 =39.06
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Formative measurement example • Construct – • Team electronic communication use Indicators (question-statements answered on a Likert-type scale) 1. 2. 3. 4. 5. 6. 7. The team used e-mail to fellow team members (1 to 1). The team used e-mail to team distribution lists (1 to many). The team used team messaging boards or team discussion forums. The team used shared electronic files. The team used Lotus notes to facilitate sharing information among team members. The team used electronic newsletters that covered project information. The team used auto routing of documents for team member and management approval. 8. The team used file transfer protocols (FTP) to attach documents to e-mails and Web pages. 9. The team used a Web page dedicated to this project. 10. The team used a Web page for this project that contained project specs, market research information, and test results. 11. The team used voice messaging. 12. The team used teleconferencing. 13. The team used video conferencing 14. The team used desktop video conferencing 15. The team used attached audio files to electronic documents. 16. The team used attached video files to electronic documents.
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Data Management Fire Site         Team #1 Team #2 Team #3 Team #4 Team #5 ONCE YOU HAVE YOUR CONC./GRAM DATA Conc. Cu ((µg/mL)/g) 1.179 0.643 0.712 0.689 0.972 COME UP TO THIS COMPUTER AND ENTER IT IN Conc. Fe ((µg/mL)/g) 2.032 1.298 1.052 1.708 1.135 SO EVERYONE CAN SEE IT!!!!! Conc. Zn ((µg/mL)/g) 0.774 0.772 0.791 0.787 0.805 Suspect #1 Suspect #2   Suspect #3 Suspect #4 Suspect #5 Team #1 Team #2 Team #3 Team #2 Team #6 Team #3 Team #4 Team #4 Team #5 Team #1 Team #5 Conc. Cu ((µg/mL)/g) 0.120 -0.059 0.168 0.176 xxxxxxxx 0.701 0.632 -0.042 0.276 0.120 0.649 Conc. Fe ((µg/mL)/g) 0.012 0.757 0.907 0.820 xxxxxxxx 1.048 1.399 1.661 0.703 1.812 0.868 0.000 -0.053 0.250 xxxxxxxx 0.774 0.678 0.253 0.247 0.405 0.624 G E S Conc. Zn ((µg/mL)/g) Blank #1   0.210   Blank #2   Team #1 Team #2 Team #3 Team #4 Team #5 Conc. Cu ((µg/mL)/g) 0.120 Conc. Fe ((µg/mL)/g) 0.005 0.638 0.497 0.657 0.354 Conc. Zn ((µg/mL)/g) 0.000 -0.024 -0.108 -0.078 -0.014 A -0.054 -0.047 E -0.084 R 0.008 Fire Site V Susp. #1 A Conc. Cu ((µg/mL)/g) 0.839 0.031 0.428 0.666 0.117 0.384 Conc. Fe ((µg/mL)/g) 1.445 0.385 0.559 1.223 1.182 1.340 0.380 0.505 Conc. Zn ((µg/mL)/g) 0.786 -0.027 0.210 0.726 0.250 0.514 -0.044 -0.046 Susp. #2 Susp. #3 Susp. #4 Susp. #5 Blank #1 Blank #2 0.006 -0.038
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Level II Placements 1st Rotation 2nd Rotation FW Site 1 1 Student 1- 1st Choice 1 Student 2- 1st Choice FW Site 1 1 Student 1- 1st 0 Student 2- 1st FW Site 2 1 Student 2- 1st Choice Student 3- 2nd Choice Student 4- 3rd Choice 1 Student A- 1st Student B- 2nd choice Student C- 3rd Choice FW Site 3 1 Student 4- 1st Choice Student 5- 1st Choice Student 6- 1st Choice Student 7-2nd Choice Student 8- 2nd Choice Student 9- 3rd Choice 1 Student 2- 1st Student 3- 1st Student 4- 1st Student 5- 1st Student 6- 1st Student 7- 1st FW Site 4 0 Student 10- 1st 0 Student 11- 1st Choice FW Site 5 1 No Student 1 No Student FW Site 6 1 No Student 1 Student 11- 1st Student 12- 1st Lake Charles MC with free housing
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