Standard deviation (goes with mean)
Variance: (almost) average
of squared deviations from the mean.
(Divide by (n-1)
"degrees of freedom")
s : Standard deviation is the square
root of the variance.
Computation: I will require you to know how to do it by hand for
4 or 5 observations(see p. 39 for pattern).
Physics: angular momemtum (spinning ice skater)
Not so weird: High school geometry?
Remember Pythagorean theorem: c2 = a2
+ b2:
hypotenuse of right triangle is also square root of a sum of squares.
Very
sensitive to outliers (squared deviations do it)
Mean/standard deviation
pair useful for symmetric, unimodal (one-humped), no outliers. ("Normal"
dist.)
Will cover Friday or Monday:
Density curve (1.3) --a mathematical model
(abstraction) of a histogram. (For Quantitative, continuous data)
"x-axis" gives possible values of observations.
Proportion of Area above interval = proportion
of all observations we would find in that interval.
| Hand in (combined with the parts done last time.)
p. 40, 1.34 a, b. Graph the data with a dotplot. Use SPSS to do c. 1.35 (Maris HR-w/w.o.outliers) Use SPSS for calculations p. 44, 1.42 xbar=7.50, s = 2.03, the same for both dist's--compare their shapes! |
Read, to discuss
1.43 states' oldies: which?why? (don't calculate)
|
Optional |
| Hand in
p. 51, 1.50, 51, 52 general densities, mean &median |
PLEASE read ahead in 1.3, The Normal Distributions: There's a
lot there, and I will cover most of it Monday.
| Sievers home | Math151-Sp01/Day5.htm | 1:30 pm | 2/7/01 |