Quantitative Research Methods I Dr.
Sanda Kaufman, Instructor
UST803 Department
of Urban Studies
Spring 2006 M 6:00-9:30 CSU,
MGL College of Urban Affairs
·
Make it
useful to you: although answers are available, try to solve the problems
on your own; the correct answer is useless if you do not know how to obtain
it.
·
Make it easy
to find:
label your products with your name, the homework number and date, and page
numbers.
·
Make it easy
to read:
type all text other than formulae and computations.
·
Make it easy
to understand: explain the logic.
Include computations, in preparation for tests. Have printouts at the end; briefly state
and interpret results referring to them.
State conclusions where
appropriate--don’t leave the reader guessing, especially when using SPSS
(restate in words what you believe your results mean in terms of the question.)
·
Make it
complete:
the (max) 2 points per homework are given for effort & for tackling all
questions, rather than for correct answers.
(tentative -- changes are expected and will be
announced in class; if not taught in class, not required; due on Mondays unless
noted)
Week
|
Due from Gujarati
|
(numbers represent
chapter.problem number):
|
|
2. 1-30 |
Chapters
1, 2 |
1.6, 1.7, 2.4, 2.8.2.9, 2.12, 2.14, 2.16 |
|
3. 2-06 |
Chapters
3, 4 |
3.8, 3.12, 3.13, 3.15, 4.10, 4.11, 4.13,
4.16, 4.20 |
|
4. 2-13 |
Chapters
5, 6 |
5.6, 5.8, 5.9-11, 5.13-14, 5.16, 5.18,
5.20, 5.21 |
|
6. 2-27 |
Chapters
6, 7 |
6.4, 6.8, 6.11, 6.167.7, 7.9, 7.12, 7.15 |
|
9. 3-20 |
Chapter
8 |
7.18, 7.21, 8.5, 8.7, 8.8, 8.9, 8.11,
8.13, 8.15, 8.18 |
|
10. 3-27 |
Chapters
9, 10 |
9.9, 9.10, 9.13, 9.14, 9.18,10.9, 10.10 |
|
11. 4-03 |
Chapters
11 |
10.14, 10.17, 10.20, 10.21, 10.24, 11.13,
11.17, 11.19 |
|
12. 4-10 |
Chapters
12 |
12.13, 12.20, 12.22, 12.23, 12.25 |
|
13. 4-17 |
Chapter
13 |
13.6, 13.7, 13.9, 13.10, 13.13, 13.14,
13.19 |
|
14. 4-24 |
Chapter
14 |
¨14.10,
14.11,14.13, 14.19, ¨7.3 (p. 194), 9.9 (p.
273), 15.1 (p. 466): ü obtain
descriptive statistics for the variables and graph ü formulate
hypotheses, select sig levels ü run
the model, obtain diagnostics ü interpret
F, R2,
standard error of prediction, coefficients, standardized values, etc. ü graph
residuals ü run
and interpret tests for multicollinearity, heteroscedasticity,
autocorrelation |