Hi You don't say what background students come into your course with. Is this their first exposure to statistics / methods? Or is it a second course after the basics? I have our honours students for a full year after an intro stats course (one term) followed by an intro methods course (one term). I do a review and multiple regression in the fall term and analysis of variance in the winter term, with relevant methods interspersed throughout (e.g., measurement in fall, randomization in winter). I focus on some basic concepts each term (e.g., unique contribution of predictors in fall and interaction in winter, interaction being fundamental to understanding within-s designs as well as of merit in its own right). I also emphasize the commonality of regression and anova approaches, which is why I teach regression first. Students tell me they are well prepared for graduate school, where I expect they are exposed to more sophisticated stats and some of the (arguable I think) criticisms of standard hypothesis testing. Again, depending on their background, I would wonder how much they would take away from a course where too much was jammed into a single year, with coverage of Bayesian (even basic) contributing to the jamming. Take care Jim James M. Clark Professor of Psychology 204-786-9757 204-774-4134 Fax [email protected]
>>> Marc Carter <[email protected]> 20-May-11 2:35 AM >>> Hi, all -- Next year I've planned on developing a stats/methods integrated text (I have some sabbatical time). More and more, though, lately I've been reading that "we're doing stats wrong" and need to start moving to Bayesian stats. I understand and appreciate the arguments. I think they're right. The recent Psych Science has a bevy of articles about it, exacerbated, I'm sure, by Bem's JPSP article. Our program is essentially a grad-school-prep program, and the text will be for these students: all grad-school-bound, and smart. But most are going into the helping, rather than research-side of psych. But they'll get PhDs. Can I get a show of hands to help me decide whether or not I should a) include only Bayesian hypothesis testing, 2) both trad and Bayesian hypoth tests, or iii) just the trad stuff. It's a year-long course with a lab (I get them 6 hours a week for a year), and right now they come out knowing things all the way through mixed-model factorial ANOVA. Should I back off the hard-core experimental design (ANOVA) and move toward this recent (sorta) issue about how we have been doing hypothesis tests? What thinkest thous? m ------ Do not judge me before going to www.damnyouautocorrect.com. > The information contained in this e-mail and any attachments thereto ("e-mail") is sent by Baker University ("BU") and is intended to be confidential and for the use of only the individual or entity named above. The information may be protected by federal and state privacy and disclosures acts or other legal rules. If the reader of this message is not the intended recipient, you are notified that retention, dissemination, distribution or copying of this e-mail is strictly prohibited. If you have received this e-mail in error please immediately notify Baker University by email reply and immediately and permanently delete this e-mail message and any attachments thereto. Thank you. --- You are currently subscribed to tips as: [email protected]. To unsubscribe click here: http://fsulist.frostburg.edu/u?id=13251.645f86b5cec4da0a56ffea7a891720c9&n=T&l=tips&o=10648 or send a blank email to leave-10648-13251.645f86b5cec4da0a56ffea7a89172...@fsulist.frostburg.edu --- You are currently subscribed to tips as: [email protected]. To unsubscribe click here: http://fsulist.frostburg.edu/u?id=13090.68da6e6e5325aa33287ff385b70df5d5&n=T&l=tips&o=10677 or send a blank email to leave-10677-13090.68da6e6e5325aa33287ff385b70df...@fsulist.frostburg.edu
