Economics 249                                  Statistics

J.R. Carter

Spring 2008

 

Text:

 

Newbold, Paul, Carlson, William L., and Thorne, Betty.  Statistics for Business and Economics, 6th ed.  Upper Saddle River, NJ:  Pearson Prentice Hall, 2007.

 

Graded Assignments:

 

Problem Sets                                                              10%

First Exam                  February 14                             30%

Second Exam             April 1                                      30%

Final Exam                  May 10 (03), 9 (04)                  30%

 

Problem sets often use Microsoft Excel, available on campus PCs.  Exemptions from problem sets and midterms require a note from the class dean.  Late problem sets are accepted with penalty until answer sheets are distributed.  Makeup exams are not given; assignment weights are redistributed.  Exams, including the final, must be taken at their appointed time with the section in which the student is registered.  As described by the College’s academic honesty policy, cheating and collusion on exams are prohibited.

 

Provisional Course Outline and Readings:

 

I.          Introduction

 

A.         Probability and Statistics

Chap. 1.

 

B.         Review:  Summation Notation

 

C.        Measures of Central Location and Dispersion

Chap. 2, pp.10-12, 20-29.

Chap. 3, pp. 46-49, 51-58.

 

II.          Probability

 

A.         Preliminaries

Set Theory Concepts and Operations

Experiments, Sample Spaces, and Events

Concepts of Probability

Chap. 4, pp. 78-92.

 

B.         Elementary Probability

Probability Axioms and Implications

Counting Rules

Probability Rules

Bivariate Probabilities and Bayes' Theorem

Chap. 4, pp. 92-95, 131-133, 96-106, 109-114, 120-126.

 

C.        Random Variables and Probability Distributions

Discrete Random Variables and Probability Mass Functions

Chap. 5, pp. 134-140.

Review:  Differential and Integral Calculus

Continuous Random Variables and Probability Density Functions

Chap. 6, pp. 187-193.

Expected Value Operator, Mean, and Variance

Linear Transformations and Standardized Random Variables

Chap. 5, pp. 140-147.

Chap. 6, pp. 194-196.

 

D.        Bernoulli Trials and Binomial Distribution

Chap. 5, pp. 150-156.

 

E.         Normal Distribution and Central Limit Theorem

Chap. 6, pp. 197-205.

Chap. 7, pp. 243-248.

Chap. 6, pp. 210-213.

 

III.         Basic Statistics

 

A.         Sampling and Sampling Distributions

Sampling and Random Samples

Sampling Distribution of Sample Mean

Sampling Distribution of Sample Proportion

Chap. 7, pp. 232-237, 238-243, 254-258.

 

B.         Confidence Interval Estimation

Definition and Interpretation

Population Mean with Variance Known

Chap. 8, pp. 275-278, 282-288.

T Distribution and Population Mean with Variance Unknown

Population Proportion

Chap. 8, pp. 289-293, 295-297.

 

C.        Hypothesis Testing

Definitions and Rationale

Population Mean with Variance Known

Chap. 10, pp. 330-336, 337-347.

Population Mean with Variance Unknown

Population Proportion

Chap. 10, pp. 348-351, 352-354.

 

IV.        Regression and Correlation Analysis

 

A.         Regression Analysis

Introduction

Linear Regression Model

Ordinary Least Squares Estimation

Chap. 12, pp. 407-412, 413-417.

Chap. 13, pp. 454-462.

Coefficient of Determination R2

Chap. 12, pp. 418-425.

Sampling Distributions of Estimators

Confidence Intervals and Hypothesis Testing

Chap. 12, pp. 426-432.

Chap. 13, pp. 477-488.

Dummy Variables

Chap. 13, pp. 509-513.

 

B.         Correlation Analysis

Chap. 5, pp. 170-173.

Chap. 3, pp. 65-69.