# Lecture 1 - Course Introduction

```Logistics
Statistics
Econ 249
 No cell phones or laptops.
 Moodle web page (Won’t print out future notes)
 Prerequisites (one of)
 Econ 110 (Principles of Microeconomics)
 Econ 111 (Principles of Macroeconomics)
 Econ 199 (Principles of Economics)
Introduction
 Questionnaire and Data Sheet
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What texting in class looks like
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People and Places
Professor:
 Essential of Statistics for Business and
Economics, 9th Edition by Anderson, Sweeney,
Williams, Camm, Cochrane ISBN 978-0357045435
 Wall Street Journal, Financial Times, Economist
Dan Tortorice
Stein 505
dtortori@holycross.edu
OH: Tuesdays 11am-12pm and 1-3pm
Fridays 10am-11pm and 3-5pm
Class:
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 Blogs: Greg Mankiw, Paul Krugman, Marginal
Lecture 1: M/W/F 11am –11:50am
Location: Stein 302
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Course Objectives
 Learn how to represent data.
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 Working knowledge of the basic ideas of probability
 Learn how to make inference from data.
 Knowledge of linear regression.
 Problem sets
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 Obtain a working knowledge of Excel.
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Problem sets (15%)
Two in-class exams (20% each) [Make up policy]
Short in class quizzes (10%)
Final Exam (25%)
Class Participation (10%)
Check syllabus for due dates.
Will be posted on the website.
Turn in during lecture.
Expected to work together. But do not copy!
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Course Outline
Course Outline
 What is statistics and why do we care?
 Confidence intervals and hypothesis testing.
 Graphical methods.
 Linear Regression
 Numerical methods and Excel.
 Interpreting regression results
 Probability Theory
 Inference in regression
 Random Variables and Distributions
 Multiple variable regression
 Sampling
 Point Estimation
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