Docsity
Docsity
Prepare for your exams
Prepare for your exams

Study with the several resources on Docsity

Earn points to download
Earn points to download

Earn points by helping other students or get them with a premium plan

Guidelines and tips
Guidelines and tips
Sell on Docsity
Sell on Docsity
Docsity AI
Docsity AI
Log inSign up

Prepare for your exams

Study with the several resources on Docsity

Find documents

Prepare for your exams with the study notes shared by other students like you on Docsity

Search for your university

Find the specific documents for your university's exams

Docsity AINEW

Summarize your documents, ask them questions, convert them into quizzes and concept maps

Explore questions

Clear up your doubts by reading the answers to questions asked by your fellow students

Earn points to download

Earn points by helping other students or get them with a premium plan

Share documents
download point icon20 Points

For each uploaded document

Answer questions
download point icon5 Points

For each given answer (max 1 per day)

All the ways to get free points
Get points immediately

Choose a premium plan with all the points you need

Study Opportunities

Choose your next study program

Get in touch with the best universities in the world. Search through thousands of universities and official partners

Community

Ask the community

Ask the community for help and clear up your study doubts

Free resources

Our save-the-student-ebooks!

Download our free guides on studying techniques, anxiety management strategies, and thesis advice from Docsity tutors

Example D10: SAS Program - Assignment 10 | STAT 479, Assignments of Statistics

Iowa State University (ISU)Statistics
Prof. Mervyn G. Marasinghe

Material Type: Assignment; Professor: Marasinghe; Class: CMPTR PROCESSG DATA; Subject: STATISTICS; University: Iowa State University; Term: Unknown 1995;

Typology: Assignments

Pre 2010

Uploaded on 09/02/2009

koofers-user-7ya
koofers-user-7ya 🇺🇸

10 documents

1 / 9

Toggle sidebar

This page cannot be seen from the preview

Don't miss anything!

bg1
EXAMPLE D10
SAS Program
data cement;
input x1-x4 y;
cards;
7 26 6 60 78.5
1 29 15 52 74.3
11 56 8 20 104.3
11 31 8 47 87.6
7 52 6 33 95.9
11 55 9 22 109.2
3 71 17 6 102.7
1 31 22 44 72.5
2 54 18 22 93.1
21 47 4 26 115.9
1 40 23 34 83.8
11 66 9 12 113.3
10 68 8 12 109.4
; run;
proc reg corr ;
model y = x1-x4/selection=stepwise sle=.15 sls=.15 details=all;
title 'Regression : Variable Subset Selection Techniques';
run;
pf3
pf4
pf5
pf8
pf9

Partial preview of the text

Download Example D10: SAS Program - Assignment 10 | STAT 479 and more Assignments Statistics in PDF only on Docsity!

EXAMPLE D10SAS Program data

cement;

input

x1-x4 y;

cards;

run

proc

reg

corr

model

y = x1-x4/selection=stepwise

sle=

sls=

details=all;

title

'Regression : Variable Subset Selection Techniques';

run

Regression :

Variable

Subset

Selection

Techniques

The

REG Procedure

Number

of Observations Read

Number

of Observations Used

Correlation

Variable

x

x

x

x

y

x

x

x

x

y

Regression

: Variable

Subset

Selection

Techniques

The

REG Procedure Model: MODEL

Dependent Variable: y

Number

of Observations Read

Number

of Observations Used

Regression :

Variable

Subset

Selection

Techniques

The

REG Procedure

Dependent Variable: y Stepwise Selection:

Step

Statistics

for

Entry

DF

Model

Variable

Tolerance

R-Square

F

Value

Pr

> F

x

x

x

Variable

x

Entered: R-Square

and

C(p) =

Analysis of

Variance

Sum

of

Mean

Source

DF

Squares

Square

F

Value

Pr >

F

Model

Error

Corrected

Total

Parameter

Standard

Variable

Estimate

Error

Type II SS

F Value

Pr >

F

Intercept

x

x

Bounds on condition number:

Regression :

Variable

Subset

Selection

Techniques

The

REG Procedure Model: MODEL

Dependent Variable: y Stepwise Selection:

Step

Statistics for

Removal

DF

Partial

Model

Variable

R-Square

R-Square

F

Value

Pr >

F

x

x

Statistics

for

Entry

DF =

Model

Variable

Tolerance

R-Square

F

Value

Pr

> F

x

x

Variable

x

Entered: R-Square

and

C(p) =

Stepwise Selection:

Step

Statistics for

Removal

DF =

Partial

Model

Variable

R-Square

R-Square

F

Value

Pr >

F

x

x

x

Statistics

for

Entry

DF =

Model

Variable

Tolerance

R-Square

F

Value

Pr

> F

x

Variable

x

Removed: R-Square

and

C(p) =

Analysis of

Variance

Sum

of

Mean

Source

DF

Squares

Square

F

Value

Pr >

F

Model

Error

Corrected

Total

Regression :

Variable

Subset

Selection

Techniques

The

REG Procedure Model: MODEL

Dependent Variable: y Stepwise Selection:

Step

Parameter

Standard

Variable

Estimate

Error

Type II SS

F Value

Pr >

F

Intercept

x

x

Bounds on condition number:

Stepwise Selection:

Step

Statistics for

Removal

DF

Partial

Model

Variable

R-Square

R-Square

F

Value

Pr >

F

x

x

Statistics

for

Entry

DF =