MATH 251, Probability and Statistics I, Fall 2005, Day 1

Unless otherwise noted, all assignments are in Moore & McCabe, Intro to the Practice of Statistics, 5th ed. ("IPS")
Italics are notes to myself--which problem is it?
Day 1 (Fri. Aug. 26)  
 Read: To students xxxi ff.  Introduction p. 2ff. Section 1.1 (postpone timeplot).  Read ahead, 1.2 thru p. 49 

Do to hand in:  (Pie, bar, histogram.  Stem&leaf next time)
p.25, 1.9 
1.8 a,b,c by hand
1.21 (college costs)
1.32 (dates of coins-skewed left)
1.7 (Proportion)
1.30 a,b  (The data are in order so it's not too hard.)		 Read, be prepared to discuss
p. 25, 1.1, 1.3, 1.4(1st def's, choosing vbl)
1.14 (bar vs. pie)
1.19, 20, 31
p. 95, 1.135
 

 

 Optional

Take your pulse, write it down!
Prerequisite Calculus I.  See me if not.  Which course?
Handouts:
Syllabus   
Be sure to return the Info sheet to me, Mac 102.  Also tell me there if this is your first semester at Wells.
Pie, Bar template.
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Data:  Information (usually numbers)  in context: 
    Who (& how many), What (is measured. Units),  When and Where? Why? How?
Variable (possible values), individuals (cases)
    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.
       "Make Piles" -- Frequency table:  count,  percent="relative frequency"  (Hair color)
Graphical summaries of data:  Area represents proportion.
     Categorical: Bar or pie graph  (Bar chart ordered by size = "Pareto chart")
             Pie only ok if showing all categories (part of whole) & no overlap of categories.
                Pie by hand?  Template handout
    Quantitative: Histogram.  ( Stem-and-leaf (Stemplot), Dotplot next time.)
          Counts or proportions = heights; Equal width bars on continuous base ensures "Area represents proportion."
      ( Bar graph: space between bars (different categories).  Histogram: no space (continuous numbers))
     Describing:  Pattern-- and deviations from it
          Shape (symmetric, or skewed (think smeared, or sliding) right or left),
              (Humps:  uni- or bi- modal (multi-)   Two humps = two "causes"?)
               Some special shapes:  uniform (flat)   J-shaped (p. 36 top left)  bell-shaped (sec. 2.3)
          Center, Spread (roughly now)
          Outliers,  gaps ?  (different groups, sources?)

Add to text:  Pareto Chart (p.28): A bar graph of a categorical variable distribution, where the categories are arranged in order from the largest to the smallest frequencies.  (A simple idea, useful, e.g. to see which parts of an assembly line break most, should be fixed first.)  
Ordinal.  Know Skewed Left/Right
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