Uncategorized pages

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Showing below up to 50 results in range #51 to #100.

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  1. Course videos from 2014
  2. Course wrap-up
  3. Course wrap-up (2011)
  4. Course wrap-up - 2012
  5. Course wrap-up - 2013
  6. Course wrap-up - 2014
  7. DOE trade-off table
  8. Design and analysis of experiments
  9. Design and analysis of experiments (2013)
  10. Design and analysis of experiments (2014)
  11. Design of Experiments project - 2011
  12. Design of Experiments project - 2012
  13. Designed experiments project - 2013
  14. Designed experiments project - 2014
  15. Designed experiments projects from prior years
  16. Electronic submissions - 2013
  17. Electronic submissions - 2014
  18. Final exam - 2012
  19. Final exam - 2013
  20. Final exam - 2014
  21. Final exams from prior years
  22. Latent variable methods and applications (2011)
  23. Latent variable methods and applications (2012)
  24. Latent variable methods and applications (2013)
  25. Least squares modelling
  26. Least squares modelling (2013)
  27. Main Page
  28. Materials for the 2013 class
  29. Materials for the 2014 class
  30. Midterms from prior years
  31. Module:Hatnote
  32. Practice questions
  33. Process monitoring
  34. Process monitoring (2013)
  35. Process monitoring (2014)
  36. Response surface bonus project - 2013
  37. Response surface project - 2014
  38. Response surface project from prior years
  39. Software-tutorial/About the course software
  40. Software tutorial
  41. Software tutorial/About the course software
  42. Software tutorial/Annotating plots: grid lines, arrows, lines, and identifying interesting points
  43. Software tutorial/Basic data manipulation in R
  44. Software tutorial/Basic plots in R
  45. Software tutorial/Building a least squares model in R
  46. Software tutorial/Calculating statistics from a data sample
  47. Software tutorial/Dealing with distributions
  48. Software tutorial/Dealing with factors (categorical variables)
  49. Software tutorial/Extending R with packages
  50. Software tutorial/Extracting information from a linear model in R

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