Math 151 , Spring 2001, Day 1 Hit reload to get most current version

final version
Syllabus, class mechanics
Honor code
Data collection:  Class, heart rate (pulse), height, hair color
Variable (possible values), individuals (cases) What, who (how many), why?  How?
    Categorical (can be ordinal--has natural order) or Quantitative (can add, average)
Distribution of one variable:  what values, how many (or what proportion) of each.
    Bar or pie graph: (categorical)| | Histogram or Stemplot (Stem-and-leaf):(quantitative)
        (I will only require you to read, not make histograms. Make stemplot (more next time))
    Describing:  Pattern-- and deviations from it
        Shape (symmetric, skewed (think smeared) right or left), 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.


HW assignment  Day1, Monday Feb. 8
From David S. Moore, The Basic Practice of Statistics, unless otherwise noted.
Reading:  Intro, xxv-xxxi [very good], Chapter 1, section 1.1(Distributions with graphs).  Ahead in 1.2 thru p. 37.
Italicized notes give me a hint which problem it is. [my comments]
    Problems on the same line usually cover similar issues.
Hand in 
p.5, 1.2 cat/quant
p.8,  1.4 bar/pie
p. 14, 1.8 read histo(stocks)
    [for d) add amts of  bars]		 Read, be able to discuss     1.1 indiv/vble
1.3 bar (pie OK?)
1.7 		 Optional 
p. 20, 1.11 
 

 

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