Math 151 , Fall 2008 Friday Day 21, Oct. 17 Hit reload....after class.

HW:   (re)Read p. 186.  Now:  Chapter 8.  (Read p. 200 (Other designs) last (it's optional)).  Check p. 206, 8.17-22, 26 at first., then 8.23-25 with Table B.  Ahead, Chapter 9.

Hand in

p. 194, 8.4, 5, 6 population/sample
. . . . . .
p. 195, 8.7 Sampling badly on campus
- - - - - - -
p. 199 8.10 Minority Managers Use the Simple Random Sample Applet, and choose a sample of size 6. Give your answer by listing their names. (I believe that everyone will get different samples.) Five of the 28 managers have East Asian surnames:  Huang, Kim, Liao, Shen, Wang.  How many of these are in your sample? Be ready to pool your answers next time. 

p. 199 8.9 Apartment living, SRS. Use Table B.
p. 209, 8.36 Area code sample, SRS  Use Table B.
p. 211, 8.45 random digit dialing
p. 210, 8.41 random digit characteristics p.209-10, 8.38 b only Traffic lights
p. 208, 8.30 movie viewing
+ + postpone the rest+ + + + + +
p. 205, 8.16, Ask more people
p. 212, 8.50, Polling Hispanics

 Read, to discuss 


& &  . .p.195, 8.8 more Sampling badly on campus
- - - -
p. 211, 8.47 guns

p. 204, 8.14, 8.15 biases.
p. 208, 8.31 world affairs
p. 211, 8.46 wording survey questions

postpone p. 212, 8.49 Canada healthcare

Optional 

&.

p. 209, 8.35 Use table B (more practice)

p. 209, 8.34 seat belt use


Exam 2 Returned last class.  Get from me if you were absent:   Comments    Solutions
= = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = 

recall Ch. 8&9:  Producing Data:  Aim:  create data sets that will allow us to make inferences to a larger world than just the data we have.

  Observational Study:  Observes individuals, measures variables, does not influence the responses. (ch.8) 
                 Sometimes observe individuals who are (more or less) conveniently at hand, or, better,
                  Take Sample from a population, examine it.... (ch.8)
  Experiment: Imposes treatment  on individuals, to see how the treatment influences  the response. (ch.9)  

Confounding:  Two variables (explanatory or lurking) are confounded when you can't sort out their effects on a response variable. 

Start here Friday: Day 20 for details
Recap: Sampling  (see day 20)
>>Population: Entire group  that we want information about.
>>Sample: The part of the population we actually examine.
      Hope:  Sample will be representative of the population.
>> Sampling design:  Describes exactly how sample is to be chosen from population.

(SAMPLING) BIAS:  The design of a study is biased if it systematically favors certain outcomes.  
Non-probability samples (sampling badly): Voluntary response sample , Convenience sample

Our main sampling design:
Simple Random Sample (SRS) of size n:  n individuals chosen in such a way that every possible set of n individuals has an equal chance of being chosen.
 Using Random Number Table. See Day 20 for details. 
      (Simple Random Sample Applet, is easier.  Enter population size, sample size, hit Reset, then Sample.)
See Day 20 for rest of details on Ch. 8:
Some more sources of bias:  
**Undercoverage:     One possible source of undercoverage: Sampling frame excludes some.
** Nonresponse
**Response bias
**Wording of questions                         
 A probability sample (p.200) is from a design where impersonal chance is used to pick the individuals.  SRS is the most straightforward.  More sophisticated methods are often used, but they're optional this term. (More info)
+ + + + Got roughly to here Fri.+ + + +
Larger (RANDOM) samples give more accurate results than smaller random samples.
  (but Not because you have more of the population.)
 More discussion of terms used in sampling

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