My goal: I'm trying to find out about the use of statistical packages in teaching statistical techniques and content in graduate education. Responses will be tabulated but not the individual identity of respondents.
1. If there is a specific stat package that is formally or informally the 'standard' for graduate education in your department, what would it be? Delete incorrect responses leaving the best answer(s). Multiple answers are possible.
a) No specific standard; faculty in my department typically use a wide variety of statistical programs in graduate education and research training
b) SAS
c) Minitab
d) SigmaStat
e) BMDP
f) SPSS
e) other (please name it)
2. Assuming that you and your department use some statistical package(s), how does your department teach students the use of statistical concepts and techniques with a Stat package as part of their graduate education? Delete responses thereby leaving the correct answer.
a) yes we require mastery of a Stat package as part of a formal course in statistics or methods. The specific course is the main vehicle for teaching the stat package.
b) yes we require mastery of a stat package but the Stat package is integrated into laboratory courses and not the focus of its own course
c) both a and b; we have a special course and the same stat package is intentionally integrated into lab courses across the department.
3. Certainly the availability of a computerized statistical package allows faculty to expect graduate students to acquire techniques that would be unwieldy if the calculations were done by hand. Please indicate those techniques that are customarily taught in your department that would not be taught if a Stat package was unavailable. Delete responses, leaving those topics that you would not teach without a stat package. When you are done, the list will contain only topics you would not cover in detail without the availability of a computerized stat package. Feel free to add any I have missed.
Simple one way anova
Factorial Anova
Ancova
Post-hoc comparisons such as Scheffe, HSD, Bonferroni, etc.
Orthogonal contrasts and trend analysis of main effects in Anova
Factor analysis
Multiple Regression
Residual Analysis in Multiple Regression
Discriminant Analysis.
Cluster Analysis
Eta-squared
Power analysis.
Chronbach's alpha
Cramers V
Levene's test for equality of variance
Log-Linear modeling
Multivariate Anova or Ancova
Finally, here is a free form question you can chose to answer or skip. Looking ahead into the future, do you see any changes in the quality of graduate education that are directly attributable to the availability of computerized statistical packages? Any real advantages to their availability? Any real downside? Anything you just want to say about the current or future state of graduate training in statistics? Here is your chance to make any comment re stat packages and/or the future of grad stat education.
Thank you. George Spilich Washington College [EMAIL PROTECTED]
. . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
