70208 Homework 2
Due February 4, 2015
Homeworks must be turned in during lecture. No late assignments will be
accepted. You may work in groups, but you must write up the answers on your
own and write down who you worked with. Write your recitation section

Lecture 1: Introduction
Professor Rebecca Lessem
70208 Regression Analysis
January 12, 2015
Outline
1. Introduction to topics in course
2. Overview of syllabus
Course overview
Continuation of statistics sequence for undergraduate
business majors
Study the

Lecture 2: Inference about the population mean
70-208 Regression Analysis
January 14, 2015
Outline
1. Sampling distribution of the sample mean
2. Law of Large Numbers
3. Central Limit Theorem
4. Review of the normal distribution
5. Condence intervals
6. S

Lecture 12: Multiple Regression
70208 Regression Analysis
March 4, 2015
Outline
1. Understand omitted variable bias
2. Fit of the regression
3. Classical regression model
4. Sections 4.1, 4.2, and 4.3
Omitted variables bias
In example from last class, loo

Lecture 6: Univariate Regression
70208 Regression Analysis
February 2, 2015
Outline
1. Algebraic properties of least squares line
2. Goodness of t of a regression
3. Read and use an ANOVA decomposition
4. Relate the mean squared residual to the standard e

Lecture 11: Multiple Regression
70208 Regression Analysis
March 2, 2015
Outline
1. Understand why the coefcient on one regressor may change
as you add more variables
2. Distinguish total effect from partial effect
3. Understand omitted variable bias
4. As

Regression Analysis Recitation 6
February 27, 2015
Today we will work with the Excel le gpa.xls, which is the same dataset that
we have been using in lecture. We are interested in the relationship between
high school and college GPA. The data gives the hi

70208 Spring 2015
70208-Regression Analysis
Spring 2015
Instructor
Professor Rebecca Lessem
Oce: 323 GSIA
E-mail: [email protected]
Oce hours: Tuesdays 9:30-11 or by appointment
Course website
Located on Blackboard
Teaching Assistants
1. Erica VanSan

Lecture 9: Classical regression model
70208 Regression Analysis
February 11, 2015
Outline
1. View least squares as a mechanism to understand the
parameters of the Classical Regression Model
2. Section 3.3.2
Inferences about parameters
b 0 and b 1 are esti

Lecture 7: Univariate Regression and Classical
Regression Model
70208 Regression Analysis
February 4, 2015
Outline
1. Read and use an ANOVA decomposition
2. Interpretation of results
3. Classical Regression Model
4. Sections 3.4.2, 3.7, 3.3.1, and 3.3.2
E

Lecture 3: Inference about the population mean
70208 Regression Analysis
January 21, 2015
Outline
1. Hypothesis testing
2. Section 2.7
Example
Remember example from last lecture
Sampling the weight of boxes constructed condence
intervals for the mean
Now

Lecture 5: Univariate regression
70208 Regression Analysis
January 28, 2015
Outline
1. Univariate regression
2. Sections 3.1 and 3.2
Regression
Last slides looked at the relationship between two variables
(education and income)
We saw a positive relations

70208 HOMEWORK 3
SOLUTIONS
1. (a) Using Excel to obtain the line for the least squares regression where college GPA is the Y
variable and high school GPA is the X variable, we get the following output and equation:
y = 1.435 + 0.476x
(b) The coecient of t

Lecture 14: Multiple Regression
70208 Regression Analysis
March 18, 2015
Outline
1. Multicollinearity
2. F-tests
3. Sections 4.3.2, 4.4, and 4.6
Multicollinearity
Adding extra independent variables improves the t of a
regression
What happens if independen

Lecture 13: Multiple Regression
70208 Regression Analysis
March 16, 2015
Outline
1. Classical regression model
2. Standard errors of parameters
3. Multicollinearity
4. Section 4.2
Effect of education on wages
Education increases wages
Call this the short

70208 HOMEWORK 5
SOLUTIONS
1. Using Excel to obtain the line for the least squares regression where wage is the Y variable and
years of education is the X variable, we get the following output and equation:
wage = 2.866 + 1.614 education
2. The results in

Practice problems on hypothesis tests for least squares parameters
You are interested in how participation in free school lunch programs aects
average test scores in schools. In this analysis, we do not have information on the
parental income for students

70208 HOMEWORK 2
SOLUTIONS
1. Note: The data in this problem are meant to be treated as a sample, not a population (which
aects your degrees of freedom). However, we have not deducted points for treating it as a
population in this problem.
(a) The conditi

70208 Homework 1
Due January 28, 2015
Homeworks must be turned in during lecture. No late assignments will be
accepted. You may work in groups, but you must write up the answers on your
own and write down who you worked with. Write your recitation section

Lecture 8: Classical regression model
70-208 Regression Analysis
February 9, 2015
Outline
1. Understand the usefulness of a statistical model to provide
measures of reliability
2. Identify and understand the assumptions of the Classical
Regression Model
3

70-208: Regression and Forecasting
Spring 2014
Updated February 2, 2014
Instructor : John Gasper
Oce: CMUQ 2160
Email : [email protected]
Course Time / Location:
Monday and Wednesday: room 1185 CMUQ
Section W 09:00AM 10:20AM;
Section X 10:30AM 11:50A

70208 HOMEWORK 7
SOLUTIONS
1. (a) The following is a scatter plot with campaign spending on the x-axis and average income
on the y-axis:
(b) Using Excel to obtain the line for the least squares regression where xi is the amount of
campaign spending in a s

Linear Regression
Regression Statistics
R
R Square
Adjusted R Square
S
Total number of observation
0.81158
0.65866
0.65267
41.81825
59
110 = 77.4340 + 4.8512 * 10
ANOVA
d.f.
Regression
Residual
Total
SS
1
#
57 99,679.67222
58
#
MS
192,341.05904
1,748.7661