Chapter 6: Statistical Diagnostics
Model: The residual associated with each yi is
yi = 0 + 1x1i + 2x2i + + kxki + i.
Basic assumptions:
(1) Model is correct
(2) Errors is are uncorrelated
(3) E(i) =
STAT 2110: Assignment 3
Due date: 7-th December, 2011
NOTE: Please drop your assignment to the mailbox
STAT2110 (NOT my mailbox)!
1. The following data contain the rent and other characteristics for 3
STAT 2110: Assignment 2
Due date: 22nd November, 2011
Do ALL programmings in SAS.
1.
The age y of a clay as a function of the amount (in units) x of a certain mineral is
given by the model y = 0 + 1x
STAT2120 CDA/28.Mar.2013
Weekly Review 10
We nished Chapter 5 this week and Assignment 4 consists of 5.3, 5.10, 5.15, 5.16, 5.18,
5.27 and 5.28; the due date is April 15. Enjoy it!
Chapter 5 continues
STAT2120 CDA/18.April.2013
Weekly Review 12
This review for Chapter 8 will not be as details as those for previous chapters because we
already had another pdf le that summarizes the key issues. Howeve
STAT2120 CDA/22.Mar.2013
Weekly Review 9
Because of the mid-term test, this week we had only two hours for discussion and we
nished Chapter 4. Assignment 3 consists of 4.5, 4.7a, 4.7c, 4.12, 4.13, 4.1
STAT2120 CDA/15.Mar.2013
Weekly Review 8
In the last review we discussed the following table:
Table 4.4: Development of AIDS symptoms by AZT use and race
Race
White
Black
AZT use
Yes
No
Yes
No
Symptom
STAT2120 CDA/7.Feb.2013
Weekly Review 4
In the last review I introduced the following problem. A person claimed that he was able
to distinguish Coke and Pepsi. We gave him a glasses of Coke and b glas
STAT2120 CDA/7.Mar.2013
Weekly Review 7
We nished more than a half of this course and we have six more teaching weeks. Chapter
3 was done on Monday and then we started our deeper discussions of variou
STAT2120 CDA/22.Feb.2013
Weekly Review 5
Because of the Chinese New Year holiday, we had only two hours this week, during which
we nished Chapter 2 and started Chapter 3.
Let us consider three-way tab
STAT2120 CDA/11.April.2013
Weekly Review 11
In this week we started and nished Chapter 7 (up to Section 7.3) this week. Here is
Assignment 5: problems 7.1, 7.3, 7.4, 7.6, 7.7, 7.10 and 7.16. The due d
The SAS System
14:06 Thursday, January 31, 2013
The FREQ Procedure
Table of poured by guess
poured
guess
Frequency
Percent
Row Pct
Col Pct
1
2 Total
1
3
1
4
37.50 12.50 50.00
75.00 25.00
75.00
The SAS System
1
16:27 Wednesday, February 20, 2013
The GENMOD Procedure
Model Information
Data Set
Distribution
Link Function
Response Variable (Events)
Response Variable (Trials)
Number
Number
Numbe
The SAS System
14:06 Thursday, January 31, 2013
The FREQ Procedure
Table of gender by party
gender
party
Frequency
Expected
Percent
Row Pct
Col Pct
1
2
3 Total
1
762
327
468
1557
703.67 319.65
The SAS System
14:06 Thursday, January 31, 2013
The FREQ Procedure
Table of group by mi
group
mi
Frequency
Expected
Percent
Row Pct
Col Pct
1
2 Total
1
189 10845 11034
146.48 10888
0.86 49.14 49
The SAS System
14:06 Thursday, January 31, 2013
The FREQ Procedure
Table of malform by alcohol
malform
alcohol
Frequency
Percent
Row Pct
Col Pct
0
0.5
1.5
4
7 Total
1 17066 14464
788
126
37 3248
The SAS System
17:29 Friday, February 22, 2013
The GENMOD Procedure
Model Information
Data Set
Distribution
Link Function
Dependent Variable
WORK.CRAB
Poisson
Log
satell
Number of Observations Read
Nu
Review
The purpose of this review is to summarize the main issues that we have discussed.
Nevertheless, it is not exhaustive.
1. Contingency Tables
(a) A 2 2 Table
Gender
Female
Male
Total
Yes
n11
n21
STAT2120 CDA/11.April.2013
Chapter 8.
Models for Matched Pairs
Consider Table 8.1:
Pay higher
taxes
Yes
No
Total
Cut living standards
Yes
No
227
132
107
678
334
810
Total
359
785
1144
Our interest i
STAT2120 CDA/1.Mar.2013
Weekly Review 6
In the last review we introduced the probit model, which was once a very popular model.
However, nowadays, its dominance has been taken over by another model, w
STAT2120 CDA/31.Jan.2013
Weekly Review 3
Let us consider again Table 2.5 on page 38:
Table 2.5: Cross classication of Party identication by gender
Gender
Female
Male
Total
Democrat
762
484
1246
Party
STAT 2110 REGRESSION ANALYSIS
Instructor:
Tang, Man-Lai
e-mail: [email protected]
Office: FSC 1201
Prerequisite:
STAT1131-2 Probability & Statistics I & II and
MATH1121 Linear Algebra I
Time & P
Chapter 5: Model Building
1. Polynomial regression
Case 1. Suppose we have only one regressor/independent
variable, x.
If we observe a nonlinear relationship between x and y, we
may consider the fol
Chapter 3: The Simple Linear Regression Model
Part II
1. Simple regression with fixed intercept
Suppose we observe a set of n pairs of observations (x1, y1), ,
(xn, yn).
Suppose the intercept 0 is
Chapter 1
Introduction: Matrix Algebra and Some Useful
Distributions
1. Matrix arithmetic
A matrix (over the real line ) is a rectangular array of elements from .
A matrix with m rows and n columns
Regression Analysis
Assignment 3
Ex 1.
(a) From the correlation matrix, Rent is highly correlated with Size, N Bed and
Age, and N Bed is highly correlated with Size. As we can see from the scatter
plo
Chapter 2: The Simple Linear Regression Model
Part I
1. What is regression?
The word was originally used by an English statistician Galton.
In his 1885 paper to Royal Anthropological Institute, he
STAT 2110 Regression Analysis: Assignment 1
Due date: 19 October, 2011
1. (Regression without an intercept). As discussed in class we almost always include
an intercept. It is possible however to carr
Regression Analysis
Assignment 2
Ex 1. The least squares regression line is
y = 905.47619 42.85714 x.
(a) The prediction for the age of the last day is y3 = 476.9048. The error in
prediction is 3 = 3.
Chapter 7: Nonlinear Regression
7.1 Introduction
Basic idea: Like linear regression (model), nonlinear regression
tries to relate a response y to a vector of predictor variables x =
(x1, x2, , xk)t.
F