ECON 83A
Statistics for Economic Analysis
Spring 2016
Brandeis University
Instructor
Krastina Dzhambova
Lecture Time
Office Hours
M W 5:00 – 6:20 PM
M 6:30 – 8:30 PM
Recitation
Recitation Time
Ziyu’s Office Hours
Ziyu Qiu
W 6:30-8:20 PM
M and W 4-5 PM
PhD Candidate (Economics, Boston College)
email:
dzhambov@brandeis.edu
phone: 857-234-4179
office: IBS 1D
LOC: IBS L54
or by arrangement (please shoot me an email)
LOC: Lown Cntr 002
LOC: IBS Academic Court
Course Overview
This is the first course in statistical inference. The objective of the course is to help you
understand fundamental statistical concepts and prepare you for future classes in
econometric analysis. The course will introduce mathematical concepts and notation as
well as statistical formulas. Another important objective for the course is to help you
develop statistical intuition.
Topics to be covered are:
 Descriptive statistics
 Laws of Probability
 Random Variables and Distributions
 Sampling and Sampling Distributions
 Point and Interval Estimation
 Properties of Estimators
 Hypothesis Testing
 Analysis of Variance and Regression
Prerequisites
Econ 2a or 10a. Students must earn C- or higher in Math 10a, or otherwise satisfy the
calculus requirement to enroll in this course.
Course Textbook
th
Introductory Statistics (5 Edition), Author: Wonnacott & Wonnacott
Assigned readings come form this textbook (abbreviated WW) as per the detailed course
outline below.
The textbook is available from the university bookstore.
Learning Catalytics Access (6 months): https://learningcatalytics.com/users/sign_up
1
Homework Assignments
I will assign (almost) weekly homework assignments. They are part of your grade. The
assignments are due by 5pm on Wednesdays.
You are allowed to work on the assignments together, but everyone should submit an
individual problem set in order to receive points. There will be a total of 8 assignments for
the whole semester.
We will use Learning Catalytics for the homework assignment.
Please register as a student on the website and purchase a 6-month access at your earliest
convenience. If you already have a valid Learning Catalytics account, you can continue
using it for this class too.
You can find detailed registration instructions here:
http://help.pearsoncmg.com/learning_catalytics/student/en/Topics/lc_create_student_acc
t.htm
Each homework assignment has a unique “session access code”, which I will give to
you.
You will use Learning Catalytics at home: bringing a laptop or a smart phone to class is
not required.
Exams
There will be 2 in class midterm exams and a final exam.
Calculators
Absence from an
exam
Special
Accommodations
Exam Policy
The use of a simple non-programmable calculator is allowed during
exams.
Absence from an exam is admissible only for a serious illness or a
personal / family emergency (please be prepared to show
documentation / evidence). A student who is unable to take the final
exam for a legitimate reason must obtain advance authorization from
the Office of Undergraduate Academic Affairs.
There will be no make up exams during the semester. If the first
(second) midterm exam is missed for a legitimate reason, I will
transfer the missed exam weight towards the second midterm (final)
exam.
If you are a student with a documented disability on record at
Brandeis University and wish to have a reasonable accommodation
made for you in this class, please contact me immediately.
2
Academic
Honesty
Homework
2 Midterms
Final Exam
You are expected to be familiar with and to follow the University’s
policies on academic integrity. For details please refer to the Rights
and Responsibilities webpage.
(http://www.brandeis.edu/studentlife/srcs/rr/)
How will your grade be formed?
15 % of your grade
Each 25 % of your grade
35 % of your grade
Important Dates
January 18
January, 27
February 15, 17
February 22
March 28
March 30
May 2
May 5 at 6pm
No Class
Add/Drop ends
No Class
1st Midterm (in class)
No Class
2nd Midterm (in class)
Last Lecture
Final Exam
Some Suggestions
 Attend the lectures and recitation sessions
 I strongly encourage you to come to class: this will allow you to keep up with the
material and help you prepare for the tests
 Ask questions: there is no such thing as a silly question
 Participate in class and do not worry about saying something wrong: this is what
classroom discussions are for!
 If you can, quickly read through the upcoming chapter of the book (WW).
3
Week
Week 1
Week 2
Lecture Date Special Dates
13-Jan
18-Jan No Class
(Monday
20-Jan Schedule)
Weekly Topic(s)
Introduction: The Notion
of Statistics; Descriptive
Statistics and Probability
Probability, Discrete
Random Variables &
Distributions, The
Binomial Distribution
Week 3
25-Jan
27-Jan
Readings
WW Chapters 1,2 (Skim
chapter 1)
Detailed Description
Descriptive Statistics
Assignment
WW Chapters 3.1, 3.2,
3.3
Inroducing Probability
Models
More on Probability Models:
Independence and
Conditional Probability;
Bayes Law; How to defne
"probability"?
Probability distributions:
discrete random variables
and the binomial distribution
Assignment
1 available
WW Chapter 3.4, 3.5,
3.6, 3.7
WW Chapter 4.1, 4.2, 4.3
Probability distributions
continued
Week 4
1-Feb
WW Chapter 4.4, 4.5
3-Feb
WW Chapter 4.6
Two Random Variables &
Review for Exam
Week 5
Week 6
Week 7
8-Feb
WW Chapter 5.1, 5.2
10-Feb
15-Feb No Class
17-Feb No Class
22-Feb
WW Chapter 5.3, 5.4
Assignment
1 DUE;
Assignment
2 available
Continuous random
variables; Introduce the
Normal Distribution
Functions of a single random Assignment
variables: mean and variance 2 DUE;
Assignment
3 available
Joint probability
distributions and functions
of 2 random variables
More on two random
variables; introduce
Assignment
covariance and correlation
3 DUE
Winter Break
1st Midterm Exam (in
class)
4
Sampling
24-Feb
Week 8
Feb-29
Random sampling; Sampling
WW Chapter 6.1, 6.2 6.3, distribution; Moments of the
sample mean
6.4
Return 1st Midterms and
go over the exam
Point Estimators
WW Chapter 7.1, 7.2,
7.3, 7.4
2-Mar
Confidence Intervals
Week 9
7-Mar
WW Chapter 8.1, 8.2
9-Mar
WW Chapter 8.3, 8.4, 8.5
Hypothesis Testing
Week 10
Week 11
14-Mar
16-Mar
21-Mar
Week 13
23-Mar
28-Mar No Class
30-Mar
4-Apr
Week 14
6-Apr
11-Apr
Week 12
Introduce Estimators:
Properties of an Estimator:
Bias and Efficiency
Introduce Confidence
Intervals; CI for a single
mean; z versus t statistic
CI-s for two means
WW Chapter 9.1, 9.2
Hypothesis Testing
continued and Review
for 2nd Exam
WW Chapter 9.3
WW Chapter 9.6
Relationship between CI-s
and hypothesis testing; p
values
Classical hypothesis testing;
type I and II error
Assignment
4 available
Assignment
4 DUE;
Assignment5
available
Assignment
5 DUE;
Assignment
6 available
Two sided tests
Assignment
6 DUE
2nd Midterm
ANOVA & Fitting a Line
WW Chapter 10
One and Two way Anova
Regression Analysis
WW Chapter 11
WW Chapter 12
Fitting a Line: Introduce OLS
Simple Regression
Assignment
7 available
5
Multiple Regression
13-Apr
Week 15
18-Apr
Week 16
20-Apr
25-Apr No Class
27-Apr No Class
Week 17
2-May
May 3- May
4
Study Days
May 5 -May
12
Final Exams
WW Chapter 13.1, 13.2
Topics in Regression
Analysis
WW Chapter 13.3, 13.4
WW Chapter 14.1, 14.2,
15.1, 15.2, 15.4
Review
Multiple Regression
continued
Dummies Variables;
Relationship between
ANOVA and Regression;
Correlation and Regression
Assignment
7 due;
Assignment
8 available
Assignment
8 due
6