You may use other software, but I won't be able to help you with it
Follow links from my web page: http://diskworld.wharton.upenn.edu
(Hint: --> teaching --> stat 541)
Course goals
Real data: Learn statistics useful for analysing real data. This means
that you have to identify the real problem and not the part of the
problem most easilly modelled. This requires knowledge of the
underlieing science.
Graphics: The primary tool is to use graphical methods. Linked plots.
Dynamic graphics. The RIGHT simple plot goes a long ways.
Standard errors: In reporting information the
thing that seperates statistics
from the animals, is the concept of error of an estimator.
Before an estimator is useful, a standard error for it must be
computed.
Today's material: EDA (Exploratory Data Analysis) and box plots
What is EDA?
(For further readings see Mosteller and Tukey chapter 3)
population/sample: --> probability <-- statistics
Models in theoretical stat can be very complex
Models used in the real world are often
DATA = SIGNAL + NOISE
Statistics can be ANY function of the data
Real world statistics again are very simple
Goals:
resistence: (small changes in data don't
change statistic very much)
Robustness: (small changes in the model don't change the
properties of statistics very much)