| Hand in
Mon. Scatterplots: 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? (Keep a copy of the graph, to use in later work.) p. 107 4.23 reading ability - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Scatterplots using SPSS. Get Scatterplot handout, outside my door, or. pp.1-3, p.4 ---From now on, make all scatterplots on SPSS! Don't forget to check Measure, and to add Labels. (Trouble printing? Try copy/paste into Word, printing in Word. If you print from Word, on a computer without SPSS, symbols may look funny. 'S OK.) 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). Do Handout questions on a separate page, and Keep till we have finished all 12 questions! p. 96, 4.4 and 4.5 (SPSS) bird colonies (Save your file; you'll use it again for 4.10) 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. (Keep a copy of the graph, to use in the next section.) - -.Postpone all Correlation.
- - - - - - - - - - - - - - - 4.26 date heights again You graphed this by
hand. r = .5653. Now answer the questions in the text. A. If women always married men who were exactly two years older than themselves, what would be the correlation between the ages of husband and wife? (Hint: make a data table and the corresponding scatterplot for 4 or 5 couples with different x's, and look at it.) Correlation (computing & thinking) p. 104, 4.11 (SPSS) gas, speed: association but 0 correlation. Find the means and draw the mean lines on your graph (by hand) to help explain the 0 correlation. p. 104, 4.10 (SPSS) bird colonies again. To add
a data pair in SPSS just type them in a new row at the bottom. To
delete, click on the case number, which highlights the whole row, hit
delete. |
Read to discuss |
Optional
Do now (for ch. 5!) 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. - - - - .Postpone Correlation. 4.28, I said to
draw the line by hand.
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Exam1 returned: 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 and mark, or copy, only 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
in the Measure column? Solutions,
p. 2 The numbers become just labels; the ruler line becomes a list of
labels. Check every data set for this!
What happens further out in normal tails? Almost (but not quite) 0.
Homework questions? Day 11 Day 12
Relationships: (BPS4e, Ch. 4) Day 12
Timeplots: are scatterplots, where the x axis shows time.
(often
a lurking variable: plot data against order of taking
observations)
Handout on SPSS Scatterplots etc. p.1-3,
p.4
, showing subgroups, labeling individual points.
govsal_vs_pay.sav
is the file used for most of the handout. (In SPSS for Class BPS
folder)
Start
here Monday:
Correlation: The (Pearson)
correlation coefficient r is a numerical measure for how strongly linear
(and in what direction) the relationship is. Doesn't
substitute for a scatterplot.
Use if data is: 2 quantitative variables,
& "nice":
One cluster/cloud/band.
Pretty straight.
Outlier(s)? Do with/without & be cautious.
Correlation experiments:
Website, http://www.whfreeman.com/bps4e,"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.
Using SPSS (p.4, Scatterplot handout) Analyze>Correlate>Bivariate
Properties (p. 101) and cautions (p. 103):

--You won't have to calculate a correlation coefficient by hand. This
formula is a bad one for hand computation (roundoff error); if you must
do one by hand, find the computational formula in an old textbook.
--Eyeballing: sketch xbar and ybar lines, see how much
data is
in + quadrants, how much in - quadrants.
Strength of correlation says NOTHING about causality!
Strong
correlation could be:
A causes B/ B causes A/ C
causes both A and B (lurking C)/ just Chance that they go
together in this data set.
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