| Hand in
Wed. Scatterplots: p. 92, 4.1 explanatory/response or just association 4.2 expl/ resp in an experiment (coral) 4.3 beer and blood alcohol, other variables 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 the next hw.) 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 the 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 hw.) - -Postpone all the Correlation
work!!. - - - - - - - - - - - - - - - 4.26 date heights again You
graphed this by
hand. r = .5653. Now answer the questions. 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 Postpone!! p. 112, 4.33 Do a rough sketch for yourself. Look at all the graphs you make, and guesstimate the correlation coefficient (before you read or calculate it.) |
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 !! 4.28, I said to
draw the line by hand.
|
Get your Exam1 from me if you didn't. Comments and
solutions Solutions
Activism symposium/
(Friday March 2, Day 15) No formal class. Alternative assignment,
OR meet with me to work on Normal dist. problems or
others:
SIGN UP
Wed for an hour: 9:30, 10:30, NOT 11:30!. 1:00, 2:00, 3:00.
More Normal
distribution problems, from Day 11 assignment: Handout, Link
p. 80-81 3.11 and 3.12 (locomotive
adhesion, 2 dist's)
What happens further out
in normal tails? Almost (but not quite) 0.
p.
87, 3.46 surprising difference in tails
The pregnancy question (Dear
Abby): 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)
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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