Math 151, Fall 2004, Monday Aug. 30, Day 2 

Introduce yourself to your neighbors--sides, front & backCheck for Homework questions?
Hand in Info sheets, Math pretests if you didn't.   Sign in.
  Helpers   Faherty and LaReina's hours are now posted. Hours till 4 today.  Go in & meet them.  Link from class main page.

Honor code:  This community of learners is a rare and fragile thing.  Trust is the foundation of its structure.  Betraying the trust damages the whole community.  Please do not betray my or your fellows' trust, and I will do my best to reciprocate.  The flip side of this is that if you do betray our trust, I will definitely pursue it in Community Court.


Day 2(Wed. Feb.4): Reading:  Section 1.1, + stemplot  handout, Ahead in 1.2 thru p. 37.
Missed class? handout is outside my door, 151 box, white folder
Italicized notes give me a hint which problem it is. [my comments]
    Problems on the same line usually cover similar issues.
Needed for HW: Stemplot, rounding when there are more than 2 decimal places?  Handout says truncate (round down), Moore text says round to nearest.  Tukey, the inventor, said truncate; throw away the trailing digits; I agree.  This is supposed to be fast--rounding to nearest slows it down.  I encourage truncating but you can do it either way and be right.  If you truncate, your stemplot may look a little different from the text answers. (A stemplot is hard for a computer to do, but some packages do. For them, rounding to nearest is easiest.  SPSS truncates, which is hard for a computer.)
Hand in (all from Moore text unless otherwise noted). 
p. 20, 1.14 (hurricane hist)
    1.17 (cf. age dist.)
p. 17 1.9 (stem: SSHA)
p. 22ff, 1.18 &19 (back to back HR)
         1.24 (pop of states)
Read, to discuss 
1.15 batting, 1.16 coins
Optional 
 

1.26 teachers' salaries

Pretests:  order of operations, 3.5-6.2, 2(0) = 0 not 2,  #5
Data:
  Numbers (usually) in context: 
What, Who (how many), Why?  When and Where? How?
    Context for height, hair color, shoe size, pulse rate:  Any problems with the way I did it?
Variable (possible values), individuals (cases)
         Categorical (ordinal--has natural order or nominal--just names) Ordinal/nominal not in text!
    or Quantitative (can add, average--measured on a ruler-type scale) Units?! ("calories"?)

Distribution of one variable:  what values, how many (or what proportion) of each.
       (Frequency table)
Graphical summaries of data: Area represents proportion.
     Categorical: Bar or pie graph  (Bar chart ordered by size = "Pareto chart"--not in text)
             Pie only ok if showing all categories.
    Quantitative: Histogram, Stemplot (Stem-and-leaf), Dotplot
      (I will only require you to read, not make histograms by hand. You'll Make stemplots and dotplots by hand)
       Pretest:  Restate #5 as histogram of 100 "5-volt" batteries tested for actual voltage.
              The proportion with voltage < 1 is 20.  The proportion with voltage < 3 is 60.
               a) What proportion have voltage beween 1 and 3?  b) What proportion have voltage > 3?

    Stemplots (Stem-and-Leaf) are a powerful hand tool.  Handout
            Unordered first, then ordered if necessary.  By tens, then split?
        Back to back, comparing two groups.

Choosing a display (by hand):  Note bottom of p. 38, fig. 1.12, use of a dot plot to display a data set of size n = 7.
    A dot plot is most useful for n = 3 to about 15-20, or when the data only fall on a few values (just stack the dots up).
    A stemplot is good for continuous data, smeared around; you can do 100 values in 3-5 minutes.

Describing:  Pattern-- and deviations from it
              Shape (symmetric, skewed (think smeared, or sliding) right or left),
             (Humps:  uni- or bi- modal (multi-)   Two humps = two "causes"?)
             center, spread--outliers?

What do we see?  What can we infer? (Introduction)
    Data source? Lurking variables?
    Variability happens.  Things settle down on average, BUT conclusions are never certain.
    Statistics gives us a language for talking about uncertainty.


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