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
Yuan Tao email@example.com
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
Jou-Chun Lin firstname.lastname@example.org
Office hours: Thursday 1.00 - 3.00 pm in SSH 0116 In person only
Kyle Nabors email@example.com
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
Economics 1A-B, Statistics 13, 13Y or 32 and Math 16A-B or 17A-B or 21A-B or consent of instructor.
The essential pre-requisites are exposure to introductory lower-division 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 2.1-2.6)
Lecture 3: Probability theory for the sample mean (chapter 3.1-3.3, 3.8 and appendix B)
Assignment 1 due Friday Oct 6
Lecture 4: Probability theory for the sample mean (chapter 3.4-3.7)
Lecture 5: Statistical inference based on the sample mean: confidence intervals and hypothesis tests (chapter 4.1-4.7)
Assignment 2 due Friday Oct 13
B. BIVARIATE REGRESSION: The relationship between two
Lecture 6: Bivariate regression for data summary: scatter plots, correlation and regression (chapter 5.1-5.6)
Lecture 7: ***** First midterm exam in class covers chapters 1-4 *****
Lecture 8: Bivariate regression for statistical inference: basics (chapter 6.1, 7.1-7.5)
Lecture 9: Bivariate regression: further details (chapter 5.8-5.12, 6.2-6.4, 7.6-7.7)
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 10.1-10.8)
Lecture 11: Inference for multiple regression (chapter 11.1-11.5)
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
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/
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/undergrad-program/tutoring
The Khan Academy has excellent video tutorials and exercises. See https://www.khanacademy.org/math/ap-statistics
|A. Univariate||Chapters 1-4, Appendix B
|B. Bivariate Regression
|C. Multiple Regression||Chapters 10-11, 12.1, 12.2, 13.1, 14-16
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
can also purchase your own copy of Stata (recommended) - go to
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
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.stata-press.com/data/mus2.htmlThe best ways to succeed in this class are
Assignments 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 two-thirds) and multiple choice (about one-third) questions.