Evaluation/Questionaire

I'd like some feedback from you to help me design and advertise this course for the future.  
These questions are more of an essay than short-answer or multiple choice.  Please be 
effusive.  Feel free to offer any other comments you have, particularly if they are not 
addressed by these questions.  If you'd like to download this form off the web to type on 
your own computer, it is available at 
http://www.stat.ucla.edu/~rgould/x401w00/eval.txt

Please return next week.   Consider this part of your final exam.

An outline of topics covered and data sets used is included.

Time

1. Was the time of day good (5-8pm)?  If you could choose any three hour time period 
during the week, which would it be?

2. Was the day of the week okay?


3.  Would you have taken this class if it were offered in the summer?  Which of the 
following periods do you think most highschool teachers will find most appealing: Fall, 
Winter, Spring, Summer?


Technical Content

1. Were you satisfied with the amount of technical content?  Would you  have liked more 
discussion of technical matters?  Less discussion?


2. If you answered "more", are there any topics in particular?  If you answered "less", was 
there a specific topic you had in mind?

3. Did you feel you were adequately prepared for the class discussions?  Would you have 
liked weekly lectures to fill in background?  


4. Any comments on the data sets we used?  Were they interesting?  Would high school 
kids find them interesting?

Structure

1. I'm interested in your comments on the structure of the course.  Would you have 
preferred more structure (maybe worksheets to be filled out, time limits, concrete weekly 
goals) or less structure (more time to "play" with data)?  



Usefulness

1. Do you feel this course was useful for helping you teach high school students?  Can you 
please explain?  For example, if you said useful, describe in which ways it was useful.  If 
you didn't feel it was useful, please give suggestions as to what you would have liked to see.


2. Would you have liked to spend more time addressing topics immediately applicable to 
your own students?  Or less?

3. Please look over the list of topics and comment on any that you found particularly useful 
or particularly useless.


Books
1. Was there a sufficient amount of reading, or would you have liked more?


2. Do you have a textbook you would recommend for this course?



Final Question
Is this a class you would benefit from taking again?  Would you?

General Comments:
Please add any comments, thoughts, or suggestions.



Topics

Week1:
	I. Getting to Know You, or How I Became a Statistician
II. Lecture:  What do Statisticians Really Do?   
III. Practice: Describing Data

Week 2:
	I. Discussion
	What do you look for when doing an exploratory analysis?
II. Exercises: Describing/summarizing some small data sets
III. Discussion
	Questions about Chatfield's paper?
IV. Activity
	Analyze blood pressure data
V. Discussion
		Questions
		Finite Population variance
		Formula for degrees of freedom for two sample: 
useful in itself?  Is it okay to use the smaller, more conservative 
degrees of freedom.
		Pooling: do not pool for two sample t?
		Others?

Week 3:
I. Discussion: Comparing Two Samples
		1. t-test follow up
		2. Non-parametric Test
		3. Bootstrap?
	
II. Activity:  Does captopril improve blood pressure?
		(Technical Detail: How to download data from the internet.)
	III. Questions from the battle fields.

Week 4

	I. Technical Stuff:  what's come up in your classroom?
	1. Power, significance levels
	2.??
II.  Mathematical Models -- a philosophical discussion
III. Activity:  Brain size data
	A warm-up to regression

Week 5
	I. Questions, discussion
II. Reading: Chatfield: Chapter 5.
III. Activity: "twins" data. (Regression.)

Week 6
	I. Questions, follow up from last time?
II. Ozone Presentation
	Yi Huang, graduate student, Department of Atmospheric Sciences, UCLA
III.Multiple Regression: analyze ozone data

Week 7
I. Classroom stuff:  Discussion of assumptions behind testing.
II. Ozone continuedÉ	
III. Life in a parallel universe:  How would you have done this using ARC?

Week 8
	1. Ozone Analysis Paper
2. Chi-squared assumptions
3. Experimental Design:  lead case study 

Week 9
	1. Anova


Data Sets

Blood pressure (effectiveness of captopril)
Ozone in Upland
Brain size of mammals
Twins Economic data (education and income relation)
Lead levels in blood of children of lead-workers
NHANES alcohol (are drinking and age/education related?)