| Hand in
(All D&V) (Finally) Raw data problems. . "Backward" parts are marked with *. You have done these with a technology tool (see above). Now do them with table Z also. p.102, 25 Cholesterol a, b, c, d*, e* 26 Tires a, b, c, d*, e* 28 Body Temperatures: a, b, c* Also: I have a theory as to where the "wrong" number 98.6F came from. Early work on temperatures all took place in Europe. Convert 98.6F and 98.2F to Celsius (subtract 32, and divide by 1.8). What's my theory? = = = = = = = = = = = = = = = = = = Scatterplots (Ch. 7): p. 130, 5,6 describing simple plots 1,4 what relationship ALSO sketch an appropriate scatterplot for each. 8 Derby (This is actually a timeplot)ALSO, how does the variability change over the decades? 9 Pottery For a, dotplot is ok instead of histo. ALSO, is Batch # really Quantitative, or Ordinal? Postpone SPSS |
Read,
to discuss |
Optional
(more
practice) Normal Probability Practice handout. &&&&&&& with table Z: p.102, 27 Kindergarten a,b*,c* <>p.109, 25 BeQuick a,b,c,d,e*,f* = = = = = = = = = = = = = If you feel at all shaky about graphing or using straight lines (slopes, intercepts) be sure to do Linear Equations exercise and Line Equations, Activstats 8-1, activities 3&4 (in preparation for Ch.8) |
Relationships:(D&V
Ch 7 thru p.117,
AS7-1&2 )
Handout on SPSS Scatterplots etc.
(D&V Ch. 7-10, AS 7,8,9) pp.1-3,
p.4
govsal_vs_pay.sav is the file
used for most of the handout. (In SPSS for Class 05 folder)
Did 2 categorical variables (2-way tables),
quantitative
vs. categorical (side-by-side boxplots, stemplots, histo's)
Relating 2 quantitative variables: Scatterplots
explanatory = predictor =
independent
=
"x"
= horizontal axis ( = "cause", only
sometimes!)
response = dependent
= "y"
= vertical axis
= ("effect
")
(Living histograms: Height vs. weight, Height vs. gpa)
Timeplot (p.43-4) is special case, "time" on x axis.
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