Math 151 , Spring 2004, Wednesday Day 35, April 28 Hit reload...After class

HW assignment Day 35
(re)Read rest of 6.3.  Next 7.1
For Monday:(* do not require table C, can use for review)
Table C:  
p.341, 6.48 CEO pay again (what you would do if you didn't have Table A)
p. 341, *6.46, 6.49 general z statistic, significance,Turn the page--6.49 continues. 
p. 342 *6.50 patent protection; another z.
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Fixed significance levels: if you only have table C, what can you say? 
p. 337, 6.37 testing number generator
6.38 nicotine content

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Postpone: Sec. 6.3, (pp. 346-48 is new), and  notes below 
A. You have a theory that walls painted pale pink will have a mellowing effect on elementary school students and produce better grades.  So you receive permission to repaint one classroom  from each grade at the local school over Christmas vacation (the others stay as they were).  Indeed, the students in the pink classrooms do better on end-of-year tests.  What criticism can be made of your experiment, and how could it have been designed to avoid this? 

p. 347 6.58 500 tests for psychic powers
p. 348 6.62, 77 potential schizophrenia markers

Optional 
Review (for exam): p. 360, 6.75

Optional material
Sec. 6.2  Two-sided test is doable using confidence interval (pp. 337-9)
6.39 IQ tests Use your calculator to get the sample mean
 

 

>EXAM 3  this Friday, Day 36, April 25, closed book.   I will give you Normal table and Table C (t-table).
Ch. 4 +Ch. 6
(Through 6.3, p. 346 (not multiple analyses, etc.)Not specifically Table C, pp. 334-7  Not "tests from CI's", pp. 337-8.  )
All Sig. test problems can be done without table C, tho problem 2 on sample exam  suggests it.
To do sample exam #2 without table C: z = 1.831, p =1-.9664 = .0336.   .0336 is less than .10 and .05, but not less than .025 or .01
Sample exam outside my door, solutions-- on reserve, outside my door.
LaReina will have extra clinic hours Thurs. eve. 7-9.

 pp. 345-346
>>Data must be from SRS or reasonable facsimile
      All the other warnings p. 312:  normality, watch out for outliers, skewness.  Sigma known or n large.
All the warnings about designing experiments and surveys still apply.
Test ends here.
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No new material today.  Start here Monday.
"Significance testing" vs. "Hypothesis testing"--gathering evidence vs. making decisions.

Questions on HW:
Review "Significance ", using table C, see Day 34
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 More cautions and limitations--Sec 6.3, cont'd (pp. 346-8)
>>(not in text)You cannot legitimately test a hypothesis on the same data that first suggested that hypothesis. Every data set will turn up with some unusual pattern if you examine it hard enough.  (If you must explore and confirm with the same data set, one way is to (randomly) take half the data set, explore and generate hypotheses; then use the other half for confirmatory tests.  You can use P-value to describe unusualness, but be wary of making decisions with it if you didn't expect that particular unusualness.)
All the warnings about designing experiments and surveys still apply.
>> (not in text) Another common lurking variable is the Hawthorne effect:  People tend to respond positively when their environment is changed in a way they know is supposed to be "better," especially if they know they're being studied.  (Get half-page handout.)  (Prospective teachers, keep this in mind as the fads blow in and out.)

>>Multiple Tests: beware! pp. 346-7
    If you do 100 tests and use the alpha = .05 significance level for each, then the structure of testing requires this:
    When all 100 null hypotheses H0 are true, out of your 100, about 5 of the 100 (.05) will give "significant" results by chance alone (falsely indicating the alternative hypothesis is to be preferred.)
    Moral: if you use the testing mechanism as a screening instrument for many questions, a proportion will give falsely significant results.  You can't accept the results from such multiple tests as good evidence, only as indicating questions requiring further, more specific study. The game gives you one shot, not a hundred.


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