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QSCI 381B: Introduction to probability and statistics
Instructor: Krishna P. Rustagi (685-0877)
5 Anderson
email krishna@u.washington.edu
Office Hours: 10:30 - 11:20 (Mon, Thu), or by appointment
T.A.; Shizhen Wang
(swang@biostat.washington.edu)
Text: Freund & Simon: Modern Elementary Statistics
(tenth edition) (optional but strongly recommended)
Lecture notes (Ave Copy Center 4141 University
Way)
Course Outline:
Topic
|
chapter
|
day(s)
|
Introduction
|
1
|
2
|
Data summary, display and descriptive statistics
|
2-4
|
5
|
Possibilities & probabilities
|
5,6
|
4
|
Mathematical expectation
|
7
|
2
|
Probability distributions: binomial, poisson & normal
|
8,9
|
3
|
Sampling & sampling distributions
|
10
|
3
|
Inferences: means
|
11,13
|
6
|
variance & standard deviation
|
12
|
3
|
categorical data
|
15,16
|
6
|
regression & correlation
|
15,16
|
4
|
One day each week (Wednesday) will be used as a problem solving
session and for resolving problems encountered with Minitab computer
software.
Homework problems will be assigned periodically and will be due
in a week. These will be graded.
The course grade will be based on homework (20%), two midterm tests
(40%) and a final (40%). The final numeric grade will be computed
out of the maximum possible weighted score of 100 as follows:
Grade = [{weighted score - 50}/15] +1
Thus a total weighted score of 80 will yield a numeric grade of
3.0. A score ³ 95 will earn 4.0.
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