Math 151 , Day 12, Friday, Feb.23, 2007 Hit Reload...After class

HW Day 12 Please read ahead! Read Ch. 4 (Scatterplotts and correlation) to p. 99 Check p.105 4.12, 13, 14,   and  ahead pp. 99-105 (correlation) Check 4.14 thru 4.20.  You do not have to be able to calculate r by hand.  You should be able to guess roughly at an r for a swarm of data; as p.102, eg. 4.6, and know and  be able to use facts 1-4, p. 101, and cautions 1-4 p. 103.

Hand In Monday: NOTHING new!  work on repairing Day 11 to hand in Monday. . Monday I'll quickly go over    p. 87, 3.46 surprising difference in tails
   
p. 80-81 3.11 and 3.12 (locomotive adhesion, 2 dist's) 
   and discuss the implications of the pregnancy question.  Then I'll start chapter 4.
Postpone all below here:
p. 92, 4.1 explanatory/response or just association
   
4.2 expl/ resp in an experiment (coral)
   
4.3 beer and blood alcohol, other variables
p. 108, 4.24 date heights Make the scatterplot by hand.  Answer these questions instead of the ones given:  Describe the relationship--form, direction, strength,  (with only 6 points there's not enough data  to talk about outliers).  Is there any female dating a male shorter than she is?
p. 107 4.23 reading ability
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  Scatterplots using SPSS.  Scatterplot handout p.1-3, p.4
---From now on, make all scatterplots on SPSS!  Don't forget to check Measure, and to add Labels.
SPSS Scatterplot Handout:  Use the handout and govsal_vs_pay.sav  data file to use SPSS and answer questions 1-5 (page 3 of handout).
p. 96, 4.4 and 4.5 (SPSS) bird colonies
p.96, 4.6 (SPSS) gas mileage
p. 98 4.7 (SPSS) icicle growth. Data is in table 4.2. Be sure to write on your graph which group is slow water and fast.
p. 109 4.25 a, c (not b) (SPSS) running records, M/F These are record breaking times, so a year without a number is one in which the best time was slower than the last record.
Read, to discuss 
 

 

Optional 
Do now if you need the practice:
Straight line graphing practice:
A.  y = -10 + 3x, graph for 2<x<10.
B.  y = 500 - 20x, graph for 0<x<10.











Exams returned today:   Comments and solutions     Solutions
SPSS comments.
1) More is not better.  Snowstorms of graphs and tables are not the point.  Make the one graph (or 2) that address the issue.  Find the summary values you need.  Discuss.  Don't throw in un-discussed or irrelevant stuff.
2) What goes wrong with scale (quantitative) data labeled categorical?  Solutions, p. 2  The numbers become just labels; the ruler line becomes a list of labels.
  Handout from last time: Normal probability practice  here
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HW Questions?  <>Using z tables to go between raw values and proportions (percentiles)  See Day 10
  Optional Handout:  Using SPSS to compute new variables, find Normal table values
Activism symposium/ (Friday March 2) No formal class.  Alternative assignment, or meet with me to work Normal dist. problems.

Start here Monday!
"San Diego Reader"  --What proportion of pregnancies last 310 days or more?  z = (310-266)/16 = 44/16= 2.75.  Area above 2.75 = .0030.
        3 in a thousand pregnancies last that long.  Pretty rare.  Is "San Diego Reader" one of the 3-in-a-thousand, or is she lying?  (this is the kind of question we deal with in Significance Testing, part 3 of the course).Discussion
= = = = = = = = = = = = = = = = = = = =
Relationships: (BPS4e Ch.4, at first to p. 98)  
Two Related quantitative variables  (We used side by side stemplots, boxplots, histograms to relate a quantitative variable to a categorical variable)
    "Just Related" or "explanatory & response?"
(Scatterplots)
explanatory = independent = "x" = horizontal axis ( = "cause", sometimes but not always)
  response =    dependent= "y" = vertical axis      = ("effect ")

(Living histograms:  Height vs. weight, Height vs. gpa)

Discussing Scatterplot
General Pattern                                      Deviations
Clusters?                                                      Outliers? (label if possible)
Form (linear, curved, ...?)
    Strength of relationship (how unfuzzy)  "Weak, moderate, strong"
Direction
    Positively associated:  y increases as x increases (generally).
    Negatively associated:  y decreases as x increases.

Mark subgroups differently to do comparisons. (Subgroups defined by categorical variable, like Sex, Region of country)
  Some scatterplot data:  educ-v-mortality.sav  ,   studatsp03.sav
Handout on SPSS Scatterplots etc. (BPS Ch. 4&5)  pages.1-3  ,  page.4 
govsal_vs_pay.sav  is the file used for most of the handout.



Correlation (pp. 98-105)
Website,  http://www.whfreeman.com/bps4e,
  Choose "Statistical Applets",  Correlation/Regression.  Play with data points, observing the Correlation Coefficient.
    Check in the "Show Mean X &Mean Y lines" box.  See how much is in each quadrant, compare with Correlation Coefficient..
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*Bear in mind that there were around 400,000 births in California in 1970. (I'm guesstimating.  There were 605,694 births in 1990, and the population of California in 1970 was 2/3 of that in 1990).  So a 3-in-a-thousand event would occur in 3x400 = 1200 births--there would be 1200 women in San Diego Reader's position (many of whom wouldn't know it.)  Rare events DO happen--it's not really fair to only notice and question them AFTER the fact.
Note--pregnancy in 1970 usually didn't involve the level of medical intervention (ultrasound, inducement of labor, Caesarian, etc.) it often gets now.