Math 151 , Fall 2006 Wednesday Day 23, Oct. 18 Hit reload...After class

HW:  Start Chapter 9, first to p. 224.  Check p. 228: For last HW: 9.16, 17, 18, 20 (obs/expt, factors)  Then 21 (choosing groups), then read p. 224 on, then Check 9.19, 22, 23, 25.   Read Data Ethics, pp. 235-242. Next, Ch. 10, Ch 11 to p. 285, (Skip Ch. 12, 13) Ch. 14, 15, unstarred parts of 16,17, 18, 19...
Hand in  Friday
p. 229 9.27 wine, beer, spirits , diagram design.
p. 230 9.32 a only headache prevention design
p. 231 9.33 fabric finishing, design

p. 230, 9.28 marijuana Use the Simple Random Sample Applet, see Day 22 for details, to find who to put in the two groups.  (Also: pick just the first 3 people for the "weak" group using Table B at line 131.Postpone this if you don't know how.)
p230, 9.30 TV ads  Use the Simple Random Sample Applet, see Day 22 for details.

p. 234, 9.48 Randomization avoids bias
p. 222, 9.8 conserving energy
p. 223, 9.9 exercise/heart
p. 233, 9.45 a,b,c,e antioxidants (review) 

DO p. 243 #7 anonymity or confidentiality? (read pp. 237-8)
- - - - - - - - - -  -Postpone Ch. 9 problems below- -
p. 233, 9.45 d antioxidants (review) 
 
p. 223 9.10 significance on Monday

p. 226, 9.13 hand strength, MP
p. 231, 9.35 forest CO2

p. 226, 9.15 teaching techn.  Why might I call this a  matched pairs rather than a general block design?   Don't actually do the randomization, but think about what ought to be done; we'll talk about it.
p. 232, 9.40 TV ads, block design.  Use the  Applet, to assign your subjects.  Number your Women and your Men, and show their numbers as well as the group they're in. 
p. 229, 232, 9.27 and 9.39 wine, beer, spirits two ways

- - - - - - - - - -
Hand in Friday Yes
Hand in answers to these questions on the "Placebo Effect" articles (outside my door/on reserve): 
a) Give two examples of the placebo effect (from the article!)
b) What do researchers believe causes the placebo effect? 
c)  In the separate article: "Pill will make you feel better...," what country was surveyed?
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Hand in Monday
Yes:  "Ethics": Read Data Ethics, pp 235-242.  Find at least one other person in the class, and together discuss  one of these questions.  Write up your answers (If you have consensus, fine! If you disagree, say who thinks what).  pp. 242-245, # 4 or 5 or 9 or 11 or 13 or 14 or 17
Read, to discuss
p. 234, 9.47 explaining medical research

p.233 9.41 prayer & meditation (clarification: they help the person praying; careful experiments to see if they help a person prayed for have not shown positive results.)

Postpone:
p. 232, 9.38  spine fractures You lack the information to make a complete design (i.e. how many women at each hospital.)  Sketch in what you can.

Optional 

p. 230, 9.29 red wine. 
This is a complex experiment with different amounts of polyphenols in different kinds of liquids.
 Doesn't fall neatly into our Factors-value structures?  Think about it a bit...

p. 226, 9.14 matched and not, more practice


Homework questions:  Day 22


Ch. 9 Designing Experiments  See Day 22 for details
recap:    
Treatment
:  Specific experimental condition we impose on one or more subjects.
Factor:
Explanatory Variable we manipulate. Specific values of a factor that we set.
Response variable(s) 
Results that we measure.

Lurking/confounding variables:  Control--how?  Nothing except experimental treatment should differentially affect response. Placebo effect?! use placebo as control group...
    Compare responses under several treatments, look at differences. 

How to get groups "just like" one another?  Randomize who goes into which group. 
  (Batch of experimetees is usually  not a random sample from the population of all individuals)

Randomized comparative experiment : Diagrams of design, Moore pp. 218-19: shows where randomizing happens, how many to each treatment, what the treatments are.
Completely randomized: all exp. units allocated at random among the treatments.

 Use enough subjects for each treatment so that you can  "average out" chance variation in the subjects. 

Principles of designing an experiment:  Control as much as you can, to make all the same except for treatments, Randomize the rest; Use enough subjects  to average out bad "chance"

More issues:
Placebo
and biasing effects--avoiding:   "Blind",  "Double blind."
Start here Friday:  Will also revisit using Table B, random number table.
+ + + + + + + + + + + + + + + + +
Lack of realism:  
Do sociology, psychology experiments generalize to "real life?"
--Subjects are not a random sample from the population. (Most psychology "facts" were based on studies of Ivy League males, before 1970's.)
--Ethical questions...Milgram.  Whole section BPS4e, pp. 235-242
 
Statistical Significance p.221: An observed effect so large that it would rarely occur by chance (assuming no real difference in treatments) is called "statistically significant".   "So large", "rarely", "by chance" will be defined and quantified in Ch. 6.
Example:  Suppose 95% of the subjects  had their headaches cured by treatment 9 and only 25%  by treatment 1 (placebo).  IF the medicine in fact did "no good" that would be a very unlikely outcome (at least if we have "enough" people in each treatment).  So we will say the difference in headache cures between treatment 1 and treatment 9 is "statistically significant" and be inclined to believe the medicine "works".

= = = = = = = = = = = = = = = = = = =
Fancier Experimental designs (not "completely randomized") Control extraneous variability by pre-sorting individuals into  homogeneous groups.  (BPS4e pp. 224-226)
Matched pairs: To compare Control and experimental treatments (i.e. 2 levels)
   Sort experimental units into "matching" pairs.   One member of pair gets control, other gets experimental.
                Randomize which.
        Compare within pair, then summarize all comparisons.
  Common: Do the control and experiment to same individual (matched with self). (Randomize order)
        Are right feet bigger than left feet? (not an experiment)      Sunburn salve experiment?
    Aside:  Sampling data, "longitudinal study" following same people through time.
            Works like matched pair to control variability.
Block design:  Sort experimental units into "Blocks" = groups homogeneous on potentially confounding variables
     e.g. M/F, age, income, weight, fruitflies wild or curly-winged.  (No randomization here.)
    Within each block, randomize the treatments. Compare results  within each block, then summarize all results.
    (Matched pairs is a special case of block design--each pair is a "block".)


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