Statistics I 

ECON-2140 Statistics 1, Spring 2022

This course aims at training students with skill sets in visual and statistical descriptions of data, data collection and sampling methods, probabilities, discrete and continuous distributions, sampling distributions, estimation from sample data and hypothesis testing using sample means and proportions. Students should be able to use statistical software selecting the appropriate techniques to make their own research, to interpret the output and draw conclusions based on their statistical results. (Syllabus)

Required Textbook

Ronald M. Weiers, Introduction to Business Statistics, 2008—7th edition. (PDF)

Optional Textbook

G. Jay Kerns, Introduction to Probability and Statistics Using R, 1st edition. (PDF)

Course Outlines

Here is a tentative schedule

◾ Section 1 - Data Sampling and Description

∘  Chapter 1: Introduction (Note)

∘  Introduction to R

Lab 0 RMD Lab 0 html Install Video

∘  Chapter 2: Visual Description of Data

‣ The Frequency Distribution (Lecture Note, Practice 1, Solution 1)

‣ Other Method Visual Representations of the Data (Lecture Note)

‣ The Scatter Diagram

Lab 1 RMD Lab 1 PDF Lab 1 Video (Deposit Data, Wage Data)

∘  Chapter 3: Statistical Description of Data

‣ Measures of Central Tendency

‣ Measures of Dispersion (Lecture Note, Practice 2, Solution 2)

‣ Additional dispersion topics

‣ Descriptive Statistics from grouped data (Lecture Note, Practice 3, Solution 3)

Statistical Methods of Association (Lecture Note)

Lab 2 RMD Lab 2 PDF Lab 2 Video

∘  Chapter 4: Data Collection and Sampling Methods

Homework 1 (pdf, doc) due Feb 21.

◾ Section 2 - Probability

∘  Chapter 5: Probability: Review of Basic Concepts

‣ Probability Space Operation (Lecture Note)

‣ Addition Rules for Probability

‣ Multiplication Rules for Probability (Lecture Note)

‣ Bayes’ Theorem and the revision of Probabilities (Lecture Note)

Counting Rules (Lecture Note)

∘  Review Session (Note)

∘  Chapter 6: Discrete Probability Distributions

‣ Discrete Random Variables and Distribution (Lecture Note)

‣ The Binomial Distribution (Lecture Note)

‣ The Hypergeometric Distribution (Lecture Note)

‣ The Poisson distribution

Homework 2 (pdf, doc) due April 10

Midterm Solution

Midterm Bonus

∘  Chapter 7: Continuous Probability Distributions

‣ The Normal Distribution

‣ The Standard Normal Distribution (Lecture Note)

‣ The Exponential Distribution (Lecture Note)

◾ Section 3 - Statistics

∘  Chapter 8: Sampling Distributions

‣ Sampling Distribution of the Mean (Lecture Note)

Lab3 RMD, Lab3 PDF

‣ The Sampling Distribution of the Proportion (Lecture Note)

‣ Sampling Distributions when the Population Is Finite

∘  Chapter 9: Estimation from Sample Data

‣ Point Estimator

Interval Estimates for the Mean

Final Review (Notes)

‣ Homework 3

Grading Policy

HW1: 70

HW2: 70

HW3: 60

Midterm: 150

Final: 150

Chunyu Qu