Explaining basic statistical techniques

Transcript

1. 11/11/2017 Introductory Statistics Aji John, PhD Student - Buckley Lab
2. Lab Scores Student# Lab 1 Lab 2 Lab 3 Lab 4 Lab 5 Lab 6 Total Afternoon 1 5.25 7 5.5 7 7 8 39.75 Afternoon 2 8 6 7.5 6 6 7 40.5 Afternoon 3 5.25 7 5.5 7 6 7 37.75 Afternoon 4 6 7 8 7 6 7 41 Afternoon 2 5.25 8 7 7 4 7 38.25 Afternoon 5 6.75 8 8 7 7 8 44.75 Afternoon 6 6 7 8 8 7 8 44 Evening 7 6.75 8 8 7 7 8 44.75 Evening 8 7.25 5 8 7 7 8 42.25 Evening 9 6.75 8 8 7 7 8 44.75 Evening 10 6 4 8 5 6 8 37 Evening 11 7.25 8 7.5 6 6 7 41.75 Evening 12 6.75 7 7 7 7 8 42.75 Analyze this
3. Ideas?
4. Is evening class performing better than afternoon class ?
5. Is evening class performing better than afternoon class ? Mean scores for afternoon/evening batch 0 250 500 750 1,000 949 942
6. Are the scores improving by lab ?
7. Are the scores improving by lab ? 0 15 30 45 60 Lab 1 Lab 2 Lab 3 Lab 4 Lab 5 Lab 6 Afternoon Evening
8. Are students scoring 100% in either of the groups ?
9. Are students scoring 100% in either of the groups ? Lab Scores Afternoon Evening Scores 100% 6 6 12 Doesn’t score 100% 1 0 1 7 6
10. P-value Credit - Statistics for Managers - Prentice Hall 2004
11. Critical value Credit - Statistics for Managers - Prentice Hall 2004
12. Regression R Handbook: Advanced Parametric Methods
13. Questions ? Thanks