Simple Linear Regression
CHAPTER 13: SIMPLE LINEAR REGRESSION
1. The Y intercept (b0) represents the
a) predicted value of Y when X = 0.
b) change in estimated average Y per unit change in X.
c) predicted value of Y.
d) variation around the sample regress
Chapter 13 - Simple Linear Regression Analysis
CHAPTER 13Simple Linear Regression Analysis
13.1
When there appears to be a linear relationship between y and x
13.2
The best line that can be fitted to the observed data. The slope and the intercept of the
l
Resume of Tania Smith (example)
PERSONAL DETAILS:
Name:
Date of Birth:
Address:
Telephone:
Mobile:
Email Address:
Nationality:
Visa:
Ms Tania SMITH
17 June 1980
66 Greentree St, Islington, London, QLD, 4000
12345 67890
0220123 456
tania987smith@veryhotmai
Practice Exam
Chapter 3 - Numerical Descriptive Measures
SECTION
I :M ULTIPLE -CHOICE
1. Which of the following statistics is not a measure of central
tendency?
a) Arithmetic mean.
b) Median.
c) Mode.
d) Q3.
2. Which of the arithmetic mean, median, and mo
STAT 515 - Chapter 5: Continuous Distributions
Probability distributions are used a bit differently for
continuous r.v.s than for discrete r.v.s.
Continuous distributions typically are represented by a
probability density function (pdf), or density curve.
Chapter 3
Numerical Descriptive Measures
Last (Family) Name: _.
First (Given) Name: _
INTRODUCTION
FROM PREVIOUS CHAPTERS:
A parameter is a numerical measure that describes a characteristic of a population.
A statistic is a numerical measure that describe
Stat 160 Final Review
Chapter 7 Confidence Intervals for a Single Sample Confidence Intervals for Means s s , x + 1.96 o 95% CI for the true mean is x 1.96 n n Confidence Intervals for Proportions p(1 p) p (1 p ) , p + 1.96 o 95% CI for the true proportio
Advanced Applied Econometrics
Fall 2011
Instructor: Dr. Caiping Zhang
Phone: 13552642249
e-mail: caipingzhang@gmail.com
Office Hours: by appointment
Textbook:
Applied Linear Statistical Models, Kutner, Nachtsheim and Neter and Li, 5th ed., McGraw Hill Irw