STAT 2, SUMMER 2010
Shobhana Murali Stoyanov
MAIN POINTS COVERED IN THE LECTURES SO FAR:
WEEK 1
M 6/21 Introduction, course overview, brief discussion of
ideas from Chapters 1 & 2
T 6/22 Ch.3: Histograms, qualitative and quantitative variables
W 6/23 Histograms continued, smooth curves to represent
histograms, center and spread
Th 6/24 Ch.4: Average, median, SD (r.m.s. deviation from
average), introduced Ch.5
F 6/25 Ch.5: Histograms to normal curve, use of normal curve
to approximate areas, idea that areas = percentages, use of z-table,
68-95-99.7 rule
WEEK 2
M 6/28 Ch.5: More examples, change of scale, standard units,
percentiles
T 6/29 Ch.8: Looking at relationship between two variables:
scatterplots, correlation. 5 summary statistics. Do storks really
bring babies?
W 6/30 Ch.8, 9: SD line, computing r, properties of r. r has
no units To use r, scatter plot must have
football-shape!! Ecological correlations defined.
Th 7/1 Ecological correlations discussed, along with more
examples. Also more examples discussing possible problems while using r.
F 7/2 Ch.10; Regression line introduced. Gave handout with 4
little scatter plots, and asked class to draw line of "best fit". Then
computed average y-value for each x-value, and drew another
line. Looked at square errors. Used this to discuss example of
height-weight data (from chapter 10)
WEEK 3
M 7/5 Holiday!
T 7/6 Linear regression, regression method. How to estimate
average value of y for a given x by using regression
method. (Regression estimate) Warning example of very small
person. Using regression method to predict percentile ranks.
Discussed regression effect and regression fallacy. Two regression lines.
W 7/7 Ch. 11: Definition of error, r.m.s. error. Relationship
to SD(y). Using SD versus regression to predict y. Residual
plots. Residuals must be scattered without a pattern, and have a flat regression line.
Th 7/8 Definition of homoscedastic
(football-shaped). Computing average and SD within a vertical
strip. Using normal approximations for data inside the strip. Examples.
F 7/9 Ch.12: The regression line. How to find slope and intercept
AND THE PLAN FOR THE WEEKS AHEAD:
WEEK 4
7/12 -7/16
Wrap up regression (Ch. 12), Probability (Ch. 13, 14, 15)
WEEK 5
7/19 -7/23
7/19 MIDTERM!!, Chance variability
(Chs. 17, 18, 19)
WEEK 6
7/26 -7/30
Sampling (Chs. 19, 20, 21, 23)
WEEK 7
8/2 -8/6
Tests of significance (Chs. 26, 27, 28)
WEEK 8
8/9 -8/13
Ch. 29, Review, 8/12 FINAL EXAM
Last modified: Sun Jul 11 07:21:03 PDT 2010