Economics 91

Spring 2021

This course provides an introduction to probability and statistics with emphasis on topics that are central to the study of econometrics. We will begin with descriptive statistics, probability distributions and expected values. We will learn how to make statistical inferences and tests of significance. At the end of the semester we will study classical models of bivariate and multivariate regressions. This will allow us to test various economic theories about how the world works. The aim is to provide you with sufficient knowledge of statistical and econometric theory to make you an effective consumer of empirical research in the social sciences.

Though this is not a math class, statistics can not be discussed in a meaningful way without the use of a lot of graphs and algebra. Thus Math 25 or equivalent is a prerequisite for this class. It may be good to review your knowledge in these areas. You must be able to add, subtract, multiply, and divide. But calculus will not be necessary for this class. The course is designed to prepare students for Economics 125, Econometrics. The statistical sofware we will use is Microsoft Excel.

Requirements for the course will include class attendance, six problem sets, two midterm exams, and a final exam. The problem sets will serve as excellent practice for the exams. They will be posted on this web page. Students are encouraged to do additional problems in the textbook. The midterm exams will be on Wednesday 24 February and Wednesday 7 April. The final exam will be given on Tuesday 11 May from 2-5pm PST. The problem sets will count for 30%, each midterm exam for 20% and the final exam for 30% of the final grade. All the problem sets will be posted on Sakai. You may choose to write an optional essay of 1000 words on how randomness rules your life after reading *The Drunkard's Walk: How Randomness Rules Our Lives* by Leonard Mlodinow. If you choose to write this essay, it will count as extra credit, and is due on Wednesday 5 May. This essay can only improve your grade.

A written version of the lectures is available on Sakai. Since all the material will be covered in lecture, the textbook is optional, but recommended as a reference. The optional textbook for the course is Gerald Keller, *Statistics for Management and Economics*, 11th edition, South-Western College Pub, 2018. This textbook is available at Huntley Bookstore. We will learn to use the statistics tables in the back of the book. Leondard Mlodinow, *The Drunkard's Walk: How Randomness Rules Our Lives*, is optional but recommended reading for the semester.

If any material is ever unclear, or even if everything is perfectly clear, please chat with me about statistics, economics or anything for that matter. If you have a short question, feel free to email me. For longer and better explanations, please make an appointment to see me on Zoom at your convenience. I can be reached at the following:

Office: Fletcher 216

Office Hours: Monday-Thursday 2:00-3:00pm, and by appointment

Phone: 607-3769

Email lyamane@pitzer.edu

After this pandemic, please join me for lunch every Friday from 12:00-1:00pm in the east wing of McConnell Dining Hall. Look for the table with the Economics Lunch sign. These are just office hours over lunch.

Introduction Ch 1

Descriptive Statistics Ch 2

Probability Ch 3

Probability Distributions Ch 4

Special Probability Distributions Ch 5

Statistical Inference Ch 6

Confidence Intervals Ch 7

Hypothesis Testing Ch 8

Hypothesis Testing with Two Samples Ch 9

Simple Linear Regression Ch 10

Multiple Regression Ch 11

Interpreting Regression Results Ch 12

Problem Set #1 Due Wednesday 3 February

Problem Set #2 Due Wednesday 17 February Keno

Midterm #1 Wednesday 24 February

Problem Set
#3 Due Wednesday 17 March

Problem
Set #4 Due Wednesday 31 March

Midterm #2 Wednesday 7 April

Problem Set #5 Due Wednesday 21 April

Problem Set #6 Due Wednesday 28 April

Final Exam Tuesday 11 May 2pm

Probability
Rules

Probability
Distributions

Confidence
Intervals and Hypothesis Testing

Regression

Week 6

Week 11

Week 15