Assignment 1b PH1820 Fall 2016 Due Tuesday September 6, 2016 at 11:59 pm.
These exercises use a dataset consisting of measurements of arsenic in well water and in the toenails of
people drinking it. The data were downloaded from StatLib, a collection of d
Assignment 6 PH1820 Fall 2016 Due by 11:59pm Tuesday October 18, 2016
Instructions: Please show all work. Write equations as requested by the book or the problem.
(Hypotheses, critical regions, estimated regression equation, matrix equations.) Upload the
Assignment 3 PH1820 Fall 2016 Due by 11:59pm Tuesday, September 20, 2016
Instructions: Please show all work. When using SAS for computations, please list\write the equations
you would use if you were doing it by hand. Upload the completed assignment to Ca
Assignment 4 PH1820 Fall 2016 Due by 11:59pm Tuesday, October 4, 2016
Instructions: Please show all work. When using SAS for computations, please list\write the equations
you would use if you were doing it by hand. Upload the completed assignment to Canva
Assignment 5 PH1820 Fall 2016 Due by 11:59pm Tuesday, October 11, 2016
Instructions: Please show all work. When using SAS for computations, please list\write the equations
you would use if you were doing it by hand. Upload the completed assignment to Canv
Assignment 2 PH1820 Fall 2016 Due by 11:59 pm Tuesday, September 13, 2016
29 points
Instructions: Please show all work and upload the completed assignment to Canvas. .pdf files are also
acceptable. You can find the dataset on Canvas, attached with this as
Assignment 7 PH1820 Fall 2016 Due by 11:59pm Tuesday, November 1, 2016
Instructions: Please show all work. Upload the completed assignment to Canvas. .pdf files are also
acceptable.
We recommend SAS as the computer package to use for the computations, but
Linear model 1 (PH1915)
Hyunkyoung Kim (ID:2060071)
Linear model 1 (PH1915)
Hyunkyoung Kim (ID:2060071)
Linear model 1 (PH1915)
Hyunkyoung Kim (ID:2060071)
3. Conduct a simulation study to assess the sensitivity of the normal linear regression model to
ov
ISE 2: PROBABILITY and STATISTICS
Lecturer
Dr Emma McCoy,
Room 522, Department of Mathematics, Huxley Building.
Phone: X 48553
email: e.mccoy@ic.ac.uk
WWW: http:/www.ma.ic.ac.uk/ejm/ISE.2.6/
Course Outline
1. Random experiments
2. Probability
axioms of p
3.1 Creating and Redefining Variables
You can create and redefine variables with
assignment statements using this basic form:
Variable = expression;
Examples:
3.1 Creating and Redefining
Variables
Practice!
[Program]
[Data]
3.1 Creating and Redefining
6.1 Modifying a Data Set Using the SET
Statement
Use an existing SAS data set to do data
managements.
Syntax:
DATA new-data-set;
SET data-set;
.
RUN;
Note: If new-data-set is the same as data-set, you
need to make sure data-set is not opened before
run
3.8 Working with SAS Dates
Practice!
[Program]
[Output]
[Data]
3.8 Working with SAS Dates
Age = INT(YRDIF(Birthday, Today(), Actual);
INT(argument)
YRDIF(date1, date2, argument)
Today()
1.
2.
3.
4.
Optional arguments:
ACT/ACT (or Actual)
30/360
ACT/360
3.5 Using IF-THEN Statements
Basic syntax:
IF condition THEN action
Basic comparison operators in condition:
3.5 Using IF-THEN Statements
Advanced syntax :
IF condition THEN DO;
Action1;
Action2;
END;
IF condition1 AND condition2 THEN action;
IF co
Lecture 3
CHAPTER 2
GETTING YOUR DATA
INTO SAS
1
Lecture 3
2.1 Methods for
Getting Your Data into
SAS
1. Entering data directly into SAS data sets
The Viewtable window (section 2.2)
SAS Enterprise Guide software (skip)
SAS/FSP software (skip)
2. Creati
Lecture 2
CHAPTER 1
GETTING STARTED
USING SAS SOFTWARE
1
Lecture 2
1.1 The SAS Language
Every SAS statement ends with a semicolon
SAS statements can be in upper- or lowercase.
(Ex: PROC MEANS = proc means)
Statements can continue on the next line (as long
Lecture 4
CHAPTER 2
GETTING YOUR DATA
INTO SAS
1
Lecture 4
2.7 Reading Raw Data
Not in Standard Format
Standard numeric data: numerals, decimal points,
minus signs, scientific notation (E)
Non-standard numeric data:
Numbers with commas and dollar signs
Lecture
6
CHAPTER 2
GETTING YOUR DATA
INTO SAS
1
Lecture
6
Additional materials
Statements in a data step:
Set: Read observations from one or more SAS data sets
Drop: Permanently remove unwanted variables
Keep: Permanently keep wanted variables
Rename: P
Lecture
5
CHAPTER 2
GETTING YOUR DATA
INTO SAS
1
Lecture 5
2.11 Reading Multiple
Lines of Raw Data per
Line pointerObservation
Slash (/) = go to the next line
Pound-n (#n) = go to the nth line
Data example:
The first line contains the city and state.
Lecture
6
CHAPTER 2
GETTING YOUR DATA
INTO SAS
1
Lecture
6 2.22
Listing the
Contents of a SAS Data
Set
PROC CONTENTS: Provide you all information of a
SAS data set
Syntax:
PROC CONTENTS DATA = data-set <OPTION>;
RUN;
Option
Task
DATA =
Specify the input