Meeting:
Tues Thurs 10.30  11.50 a.m. Wellman 2
Instructor Office Hours:
Tuesday afternoon 3.30  5.00 pm in
office SSH 1124 In person only
Wednesday afternoon 3.30  5.00 pm in office SSH
1124 In person only
Teaching Assistants:
Yuan Tao yuatao@ucdavis.edu
Office hours: Wednesday 10.00  11.00 am in SSH 0116
In person only
Wednesday 11.00 am  noon in SSH 0120 In person only
JouChun Lin joulin@ucdavis.edu
Office hours: Thursday 1.00  3.00 pm in SSH 0116 In person
only
Kyle Nabors kwnabors@ucdavis.edu
Office hours: Wednesday 4.00  6.00 pm in SSH 0116. In
person only
A01: Tuesday 1.10 
2.00 pm 93 Hutchison TA: Kyle Nabors
A02: Tuesday 2.10  3.00
pm 93 Hutchison TA: Kyle Nabors
A03: Tuesday 3.10  4.00
pm 93 Hutchison
TA: Jou
LIn
A04: Tuesday
4.10  5.00 pm 93 Hutchison
TA: Jou
LIn
A05: Thursday 12.10 
1.00 pm 93 Hutchison
TA: Yuan
Tao
A06: Thursday 1.10  2.00
pm 93 Hutchison TA: Yuan
Tao
Course Goals:
Prerequisites:
Economics 1AB, Statistics 13, 13Y or 32 and Math 16AB or 17AB
or 21AB or consent of instructor.
The essential prerequisites are exposure to introductory
lowerdivision courses in economics and statistics.
Relationship to Economics 140
Economics 140 (Econometrics) is a more advanced course that also
covers the methods of Economics 102.
Economics 140 has Economics 102 or Statistics 108 as a
prerequisite.
For more on possible data classes see http://cameron.econ.ucdavis.edu/e102/morestat.html
Topical Outline by Lecture Number:
The required text is A. Colin Cameron, Analysis of Economics
Data: An Introduction to Econometrics.
A. UNIVARIATE: Analysis of a single economics variable
Lecture 1: Introduction and getting going on Stata (chapter
1 + Stata http://cameron.econ.ucdavis.edu/stata/stata.html).
Lecture 2: Summarizing data using descriptive statistics and
visualizing data using charts (chapter 2.12.6)
Lecture 3: Probability theory for the sample mean (chapter
3.13.3, 3.8 and appendix B)
Assignment 1 due Friday Oct 6
Lecture 4: Probability theory for the sample mean (chapter
3.43.7)
Lecture 5: Statistical inference based on the sample mean:
confidence intervals and hypothesis tests (chapter 4.14.7)
Assignment 2 due Friday Oct 13
B. BIVARIATE REGRESSION: The relationship between two
economic variables
Lecture 6: Bivariate regression for data summary: scatter
plots, correlation and regression (chapter 5.15.6)
Lecture 7: ***** First midterm exam in class covers chapters 14
*****
Lecture 8: Bivariate regression for statistical inference: basics
(chapter 6.1, 7.17.5)
Lecture 9: Bivariate regression: further details (chapter
5.85.12, 6.26.4, 7.67.7)
Assignment 3 due Friday Oct 27
C. MULTIPLE REGRESSION: The relationship between more than
two economic variables
Lecture 10: Multiple regression for data summary (chapter
10.110.8)
Lecture 11: Inference for multiple regression (chapter 11.111.5)
Assignment 4 due Friday November 3
Lecture 12: Regression case study: Academic performance and
parents' education (chapter 13.1)
Lecture 13: ***** Second midterm exam in class *****
A. Colin Cameron, Analysis of Economics Data: An Introduction
to Econometrics.
The text is available from Amazon
for $25 paperback or $6.99 for a Kindle replica book.
A Kindle replica book is just a pdf but requires downloading the Kindle
App to your PC, Mac, Android or iOS.
Copies of the text are also on Reserve at the Library.
Slides for the course text are available at http://cameron.econ.ucdavis.edu/aed/
The datasets and Stata programs used in the course text are at http://cameron.econ.ucdavis.edu/aed/
Additional Materials:
The course Canvas site has assignments under Files/ Homeworks.
Assignments should be uploaded to Canvas under Assignments.
The website http://cameron.econ.ucdavis.edu/e102/e102.html
has past exams and solutions and some links to Stata material.
There are usually free tutors for 102: see http://economics.ucdavis.edu/undergradprogram/tutoring
The Khan Academy has excellent video tutorials and exercises. See
https://www.khanacademy.org/math/apstatistics
Reading List:
Topic  Lecture Notes  
A. Univariate  Chapters 14, Appendix B 

B. Bivariate Regression 
Chapters 59  
C. Multiple Regression  Chapters 1011, 12.1, 12.2, 13.1, 1416 
Discussion Sections:
These are held in a university computer lab in Hutchison 93.
Computer Materials: Assignments use Stata.
We use the package Stata that is used primarily in economics, other social
sciences and biostatistics.
To get started in Stata see http://cameron.econ.ucdavis.edu/stata/stata.html
and especially
http://cameron.econ.ucdavis.edu/stata/stataintro.html
Stata is installed in computer labs 93 Hutchison, 2101
SCC. To see whether these
labs are available see https://computerrooms.ucdavis.edu/available/.
It is also available
after hours in the
Virtual Lab (evenings and weekends when labs are
closed  see https://virtuallab.ucdavis.edu)
This
video provides directions if you use the Virtual lab: Connect_virtual_lab_and_start_Stata.mp4
You
can also purchase your own copy of Stata (recommended)  go to
https://www.stata.com/order/new/edu/gradplans/studentpricing/
For this course and other economics classes the cheapest
version Stata/BE is more than adequate and costs $48 (6
months), $94 (1 year); $225 (permanent copy).
To install Stata after it is purchased:
(1) Choose the correct operating system (e.g. Windows or Mac);
(2) Choose the correct version of Stata  the student price
version is Stata/IC;
(3) When you first run Stata after installation it will ask
for an "authorization code". These codes are given in a pdf
attachment you will received in the email from Stata following
purchase (some codes are lengthy and it is easiest to cut and paste them in).
The Stata code used in my ECN 102 text is
at https://cameron.econ.ucdavis.edu/aed/aedSTATAprograms.html
And the datasets are at https://cameron.econ.ucdavis.edu/aed/aeddatasources.html
For more advanced Stata my book https://cameron.econ.ucdavis.edu/mus2/ can be accessed online through the UCD library. All the data and code for that book are available free at https://www.statapress.com/data/mus2.html
The best ways to succeed in this class areAssignments will generally be graded satisfactory (4 points) or unsatisfactory (0 points); very occasionally partial credit will be given.
Academic honesty is required  see below.
Exams are closed book with a mixture of short answer (about twothirds) and multiple choice (about onethird) questions.