We'll start using SPSS Wednesday (next
time)--have
class in the
computer lab that day. Everything by "hand" till then!
| Hand in Friday (we'll discuss then) (all from D&V text) Ch3p. 31, 2 cat.
variables |
Read, be able to discuss in class
Ch3 25
Family planning |
Optional Ch.3 |
Distribution of one variable: Area represents proportion.
Homework?
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 (p. 40) && J-shaped (#6 p.50)
bell-shaped
(Ch 6)
Center, Spread
(roughly now, Ch.5 numerically)
Outliers, gaps ? (different
groups, sources?) Looked at
pulse
data. &&"Lurking variable"
Look at heights.
"Two way table"
"Contingency
table" "Crosstab(ulation)s" (color vs. hand)
A thousand people are interviewed by the census bureau, and the results
tabulated in this two way table.
Working Status vs. Sex.
| Women | Men | Total | |
| In Labor Force | 350 | 450 | 800 |
| Not in Labor Force | 150 | 50 | 200 |
| Total | 500 | 500 | 1000 |
What is the "Percent of women in the labor force" ?
Write your
answer down on a scrap of paper.
When you write or see percents, be clear what
is on the bottom of the fraction (even if it takes longer to
say)!!.
Marginal distribution: Distribution of one variable, ignoring/summingover the other.
|
|
Conditional distribution: Distribution of one variable,
with the individuals being only those which satisfy a condition in the
other variable.
For women, their conditional distribution
as to working status; For
men, their distribution as to working status.
"Column %s"--columns add to 100%: "conditional
distributions
of working status by sex".
| Women | Men | Total | |
| In Labor Force | 350/500 = 70% | 450/500 = 90% | 80% |
| Not in Labor Force | 150/500 = 30% | 50/500 = 10% | 20% |
| Total | 500/500=100% | 500/500=100% | 100% |
For those in the labor force,
conditional
distribution as to sex.
For those not in the labor
force, conditional distribution as to sex.
"Row
%s"--rows add to 100%: "conditional distributions of sex by
working
status."
| Women | Men | Total | |
| In Labor Force | 350/800 = 43.8% | 450/800 = 56.2% | 800/800=100% |
| Not in Labor Force | 150/200 = 75% | 50/200 = 25% | 200/200=100% |
| Total | 50% | 50% | 100% |
Graphs to compare proportions: parallel pies,
see
text.
Segmented (stacked) bar charts, of % (so
total length the same)
% Women
O
% Men X
OOOOOOOOOOOOOOXXXXXXXXXXXXXXXXXX In Labor Force
OOOOOOOOOOOOOOOOOOOOOOOOXXXXXXXX Not in Labor Force
&&Can do segmented bars of raw numbers, conveys different
info:
25 Women
O
25 Men X
OOOOOOOOOOOOOOXXXXXXXXXXXXXXXXXX In Labor Force
OOOOOOOOXX
Not in Labor Force
Independence: two variables are
independent when the
(conditional)
distribution of one is the same for all categories of the
other.
Working status is clearly not independent of sex.
Circle experiment: Is color independent of hand? (Usually--Do
we have enough data to tell whether it's true in general?)
Misuse: From the New
Yorker magazine,
traditionally the most literary and error-free of all, Feb.14/21, '05:
CORRECTION: The Mail of January 3rd contained the incorrect statistic that four-fifths of Bush voters identified moral values as the most important factor in their decision. In fact, four-fifths of those identifying moral values as the most important factor of their decision were Bush voters.Next: Measures of middle: Mode/ modal class, Midrange, Mean, Median, ....
| Sievers home | Math151-Sp06/Daysp4.htm | 11am | 2/6/06 |
| Women | Men | Total | |
| In Labor Force | 350 | 450 | 800 |
| Not in Labor Force | 150 | 50 | 200 |
| Total | 500 | 500 | 1000 |