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SASRegressionSoln.zip

SAS Regression Soln/Program 1-results(2).rtf

Tuesday, November 14, 2017 06:50:21 PM

The CONTENTS Procedure

Data Set Name

WORK.IMPORT

Observations

51

Member Type

DATA

Variables

9

Engine

V9

Indexes

0

Created

11/14/2017 18:50:22

Observation Length

88

Last Modified

11/14/2017 18:50:22

Deleted Observations

0

Protection

Compressed

NO

Data Set Type

Sorted

NO

Label

Data Representation

SOLARIS_X86_64, LINUX_X86_64, ALPHA_TRU64, LINUX_IA64

Encoding

utf-8 Unicode (UTF-8)

Engine/Host Dependent Information

Data Set Page Size

65536

Number of Data Set Pages

1

First Data Page

1

Max Obs per Page

743

Obs in First Data Page

51

Number of Data Set Repairs

0

Filename

/tmp/SAS_work93340000368B_localhost.localdomain/SAS_workEB5F0000368B_localhost.localdomain/import.sas7bdat

Release Created

9.0401M4

Host Created

Linux

Inode Number

271800

Access Permission

rw-rw-r--

Owner Name

sasdemo

File Size

128KB

File Size (bytes)

131072

Alphabetic List of Variables and Attributes

#

Variable

Type

Len

Format

Informat

Label

4

GunMurders

Num

8

BEST.

GunMurders

5

GunOwnership

Num

8

BEST.

GunOwnership

3

Murders

Num

8

BEST.

Murders

9

Per_capita_Income

Num

8

BEST.

Per capita Income

2

Population

Num

8

BEST.

Population

7

Poverty_rate_by_house_hold_incom

Num

8

BEST.

Poverty rate by house hold income

1

State

Char

20

$20.

$20.

State

8

Undergrad

Num

8

BEST.

Undergrad

6

VAR6

Num

8

BEST.

Murder Rate (per 100,000)

Tuesday, November 14, 2017 06:50:22 PM

Murder Rate regression using Gun Murders per Population

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

Number of Observations Read

51

Number of Observations Used

51

Analysis of Variance

Source

DF

Sum of Squares

Mean Square

F Value

Pr > F

Model

1

30.14497

30.14497

3.22

0.0787

Error

49

458.10948

9.34917

Corrected Total

50

488.25445

Root MSE

3.05764

R-Square

0.0617

Dependent Mean

4.18523

Adj R-Sq

0.0426

Coeff Var

73.05790

Parameter Estimates

Variable

Label

DF

Parameter Estimate

Standard Error

t Value

Pr > |t|

Intercept

Intercept

1

3.57895

0.54527

6.56

<.0001

GunMurders

GunMurders

1

0.00329

0.00183

1.80

0.0787

Tuesday, November 14, 2017 06:50:22 PM

Murder Rate regression using Gun Murders per Population

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

file_0.emf

file_1.emf

file_2.emf

Tuesday, November 14, 2017 06:50:31 PM

Murder Rate regression by Gun Ownership per Population

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

Number of Observations Read

51

Number of Observations Used

51

Analysis of Variance

Source

DF

Sum of Squares

Mean Square

F Value

Pr > F

Model

1

56.84932

56.84932

6.46

0.0143

Error

49

431.40513

8.80419

Corrected Total

50

488.25445

Root MSE

2.96718

R-Square

0.1164

Dependent Mean

4.18523

Adj R-Sq

0.0984

Coeff Var

70.89657

Parameter Estimates

Variable

Label

DF

Parameter Estimate

Standard Error

t Value

Pr > |t|

Intercept

Intercept

1

6.98688

1.17823

5.93

<.0001

GunOwnership

GunOwnership

1

-7.58326

2.98427

-2.54

0.0143

Tuesday, November 14, 2017 06:50:34 PM

Murder Rate regression by Gun Ownership per Population

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

file_3.emf

file_4.emf

file_5.emf

Tuesday, November 14, 2017 06:50:45 PM

Murder Rate regression by Poverty Rate

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

Number of Observations Read

51

Number of Observations Used

51

Analysis of Variance

Source

DF

Sum of Squares

Mean Square

F Value

Pr > F

Model

1

98.91106

98.91106

12.45

0.0009

Error

49

389.34340

7.94578

Corrected Total

50

488.25445

Root MSE

2.81883

R-Square

0.2026

Dependent Mean

4.18523

Adj R-Sq

0.1863

Coeff Var

67.35176

Parameter Estimates

Variable

Label

DF

Parameter Estimate

Standard Error

t Value

Pr > |t|

Intercept

Intercept

1

-2.62843

1.97112

-1.33

0.1885

Poverty_rate_by_house_hold_incom

Poverty rate by house hold income

1

0.45856

0.12997

3.53

0.0009

Tuesday, November 14, 2017 06:50:46 PM

Murder Rate regression by Poverty Rate

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

file_6.emf

file_7.emf

file_8.emf

Tuesday, November 14, 2017 06:50:52 PM

Murder Rate regression by the Literacy Rate

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

Number of Observations Read

51

Number of Observations Used

51

Analysis of Variance

Source

DF

Sum of Squares

Mean Square

F Value

Pr > F

Model

1

49.33489

49.33489

5.51

0.0230

Error

49

438.91956

8.95754

Corrected Total

50

488.25445

Root MSE

2.99292

R-Square

0.1010

Dependent Mean

4.18523

Adj R-Sq

0.0827

Coeff Var

71.51136

Parameter Estimates

Variable

Label

DF

Parameter Estimate

Standard Error

t Value

Pr > |t|

Intercept

Intercept

1

-0.71528

2.12978

-0.34

0.7384

Undergrad

Undergrad

1

0.17745

0.07561

2.35

0.0230

Tuesday, November 14, 2017 06:50:53 PM

Murder Rate regression by the Literacy Rate

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

file_9.emf

file_10.emf

file_11.emf

Tuesday, November 14, 2017 06:50:57 PM

Murder Rate regression by the Income Levels

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

Number of Observations Read

51

Number of Observations Used

51

Analysis of Variance

Source

DF

Sum of Squares

Mean Square

F Value

Pr > F

Model

1

232.25614

232.25614

44.46

<.0001

Error

49

255.99831

5.22446

Corrected Total

50

488.25445

Root MSE

2.28571

R-Square

0.4757

Dependent Mean

4.18523

Adj R-Sq

0.4650

Coeff Var

54.61364

Parameter Estimates

Variable

Label

DF

Parameter Estimate

Standard Error

t Value

Pr > |t|

Intercept

Intercept

1

-1.28882

0.88119

-1.46

0.1500

Per_capita_Income

Per capita Income

1

0.00011256

0.00001688

6.67

<.0001

Tuesday, November 14, 2017 06:50:58 PM

Murder Rate regression by the Income Levels

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

file_12.emf

file_13.emf

file_14.emf

SAS Regression Soln/Program 1.sas

/* Generated Code (IMPORT) */ /* Source File: MURDER RATE.xlsx */ /* Source Path: /folders/myshortcuts/workspace */ /* Code generated on: 11/14/17, 6:16 PM */ %web_drop_table(WORK.IMPORT); FILENAME REFFILE '/folders/myshortcuts/workspace/MURDER RATE.xlsx'; PROC IMPORT DATAFILE=REFFILE DBMS=XLSX OUT=WORK.IMPORT; GETNAMES=YES; RUN; PROC CONTENTS DATA=WORK.IMPORT; RUN; PROC REG; TITLE 'Murder Rate regression using Gun Murders per Population'; MODEL VAR6 = GunMurders; Run; Proc REG; TITLE 'Murder Rate regression by Gun Ownership per Population'; MODEL VAR6 = GunOwnership; RUN; PROC REG; TITLE 'Murder Rate regression by Poverty Rate'; model VAR6 = Poverty_rate_by_house_hold_incom; RUN; PROC REG; TITLE 'Murder Rate regression by the Literacy Rate'; MODEL VAR6 = Undergrad; RUN; PROC REG; TITLE 'Murder Rate regression by the Income Levels'; MODEL VAR6 = Per_capita_Income; RUN; %web_open_table(WORK.IMPORT);

SAS Regression Soln/Program1-results.pdf

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1 . 5

2 . 0

C oo

k' s

D 0 5 1 0 1 5 2 0

P r e d i c t e d V a l u e

0

5

1 0

1 5

2 0

O bs

er ve

d

- 2 - 1 0 1 2

Q u a n t i l e

- 5

0

5

1 0

1 5

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id ua

l

0 . 0 2 5 0 . 0 7 5 0 . 1 2 5

L e v e r a g e

- 2

0

2

4

6

8

R S

tu de

nt

3 4 5 6 7

P r e d i c t e d V a l u e

- 2

0

2

4

6

8

R S

tu de

nt 3 4 5 6 7

P r e d i c t e d V a l u e

- 5

0

5

1 0

1 5

R es

id ua

l

M u r d e r R a t e r e g r e s s i o n b y G u n O w n e r s h i p p e r P o p u l a t i o n T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 9

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

0 . 1 0 . 2 0 . 3 0 . 4 0 . 5 0 . 6

G u n O w n e r s h i p

- 5

0

5

1 0

1 5

R e

si du

a l

R e s i d u a l s f o r V A R 6

M u r d e r R a t e r e g r e s s i o n b y G u n O w n e r s h i p p e r P o p u l a t i o n T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 1 0

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

0 . 1 0 . 2 0 . 3 0 . 4 0 . 5 0 . 6

G u n O w n e r s h i p

- 5

0

5

1 0

1 5

2 0

M ur

de r

R a

te (

pe r

1 0

0 ,0

0 0

)

9 5 % P r e d i c t i o n L i m i t s9 5 % C o n f i d e n c e L i m i t sF i t

0 . 0 9 8 4A d j R - S q u a r e 0 . 1 1 6 4R - S q u a r e 8 . 8 0 4 2M S E

4 9E r r o r D F 2P a r a m e t e r s

5 1O b s e r v a t i o n s

F i t P l o t f o r V A R 6

M u r d e r R a t e r e g r e s s i o n b y P o v e r t y R a t e T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 1 1

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

M u r d e r R a t e r e g r e s s i o n b y P o v e r t y R a t e T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 1 1

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

N u m b e r o f O b s e r v a t i o n s R e a d 5 1

N u m b e r o f O b s e r v a t i o n s U s e d 5 1

A n a l y s i s o f V a r i a n c e

S o u r c e D F S u m o f

S q u a r e s M e a n

S q u a r e F V a l u e P r > F

M o d e l 1 9 8 . 9 1 1 0 6 9 8 . 9 1 1 0 6 1 2 . 4 5 0 . 0 0 0 9

E r r o r 4 9 3 8 9 . 3 4 3 4 0 7 . 9 4 5 7 8

C o r r e c t e d T o t a l 5 0 4 8 8 . 2 5 4 4 5

R o o t M S E 2 . 8 1 8 8 3 R - S q u a r e 0 . 2 0 2 6

D e p e n d e n t M e a n 4 . 1 8 5 2 3 A d j R - S q 0 . 1 8 6 3

C o e f f V a r 6 7 . 3 5 1 7 6

P a r a m e t e r E s t i m a t e s

V a r i a b l e L a b e l D F P a r a m e t e r

E s t i m a t e S t a n d a r d

E r r o r t V a l u e P r > | t |

I n t e r c e p t I n t e r c e p t 1 - 2 . 6 2 8 4 3 1 . 9 7 1 1 2 - 1 . 3 3 0 . 1 8 8 5

P o v e r t y _ r a t e _ b y _ h o u s e _ h o l d _ i n c o m P o v e r t y r a t e b y h o u s e h o l d i n c o m e 1 0 . 4 5 8 5 6 0 . 1 2 9 9 7 3 . 5 3 0 . 0 0 0 9

M u r d e r R a t e r e g r e s s i o n b y P o v e r t y R a t e T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 1 2

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

M u r d e r R a t e r e g r e s s i o n b y P o v e r t y R a t e T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 1 2

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

F i t D i a g n o s t i c s f o r V A R 6

0 . 1 8 6 3A d j R - S q u a r e 0 . 2 0 2 6R - S q u a r e 7 . 9 4 5 8M S E

4 9E r r o r D F 2P a r a m e t e r s

5 1O b s e r v a t i o n s

P r o p o r t i o n L e s s 0 . 0 0 . 4 0 . 8

R e s i d u a l

0 . 0 0 . 4 0 . 8

F i t – M e a n

0

5

1 0

1 5

- 9 - 3 3 9 1 5

R e s i d u a l

0

2 0

4 0

6 0

P er

ce nt

0 1 0 2 0 3 0 4 0 5 0

O b s e r v a t i o n

0 . 0

0 . 2

0 . 4

0 . 6

0 . 8

C oo

k' s

D 0 5 1 0 1 5 2 0

P r e d i c t e d V a l u e

0

5

1 0

1 5

2 0

O bs

er ve

d

- 2 - 1 0 1 2

Q u a n t i l e

- 5

0

5

1 0

1 5

R es

id ua

l

0 . 0 2 5 0 . 0 7 5 0 . 1 2 5

L e v e r a g e

- 2 . 5

0 . 0

2 . 5

5 . 0

7 . 5

1 0 . 0

R S

tu de

nt

2 4 6 8

P r e d i c t e d V a l u e

- 2 . 5

0 . 0

2 . 5

5 . 0

7 . 5

1 0 . 0

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tu de

nt 2 4 6 8

P r e d i c t e d V a l u e

0

5

1 0

1 5

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id ua

l

M u r d e r R a t e r e g r e s s i o n b y P o v e r t y R a t e T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 1 3

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

1 0 . 0 1 2 . 5 1 5 . 0 1 7 . 5 2 0 . 0 2 2 . 5

P o v e r t y r a t e b y h o u s e h o l d i n c o m e

0

5

1 0

1 5

R e

si du

a l

R e s i d u a l s f o r V A R 6

M u r d e r R a t e r e g r e s s i o n b y P o v e r t y R a t e T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 1 4

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

1 0 . 0 1 2 . 5 1 5 . 0 1 7 . 5 2 0 . 0 2 2 . 5

P o v e r t y r a t e b y h o u s e h o l d i n c o m e

- 5

0

5

1 0

1 5

2 0

M ur

de r

R a

te (

pe r

1 0

0 ,0

0 0

)

9 5 % P r e d i c t i o n L i m i t s9 5 % C o n f i d e n c e L i m i t sF i t

0 . 1 8 6 3A d j R - S q u a r e 0 . 2 0 2 6R - S q u a r e 7 . 9 4 5 8M S E

4 9E r r o r D F 2P a r a m e t e r s

5 1O b s e r v a t i o n s

F i t P l o t f o r V A R 6

M u r d e r R a t e r e g r e s s i o n b y t h e L i t e r a c y R a t e T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 1 5

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

M u r d e r R a t e r e g r e s s i o n b y t h e L i t e r a c y R a t e T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 1 5

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

N u m b e r o f O b s e r v a t i o n s R e a d 5 1

N u m b e r o f O b s e r v a t i o n s U s e d 5 1

A n a l y s i s o f V a r i a n c e

S o u r c e D F S u m o f

S q u a r e s M e a n

S q u a r e F V a l u e P r > F

M o d e l 1 4 9 . 3 3 4 8 9 4 9 . 3 3 4 8 9 5 . 5 1 0 . 0 2 3 0

E r r o r 4 9 4 3 8 . 9 1 9 5 6 8 . 9 5 7 5 4

C o r r e c t e d T o t a l 5 0 4 8 8 . 2 5 4 4 5

R o o t M S E 2 . 9 9 2 9 2 R - S q u a r e 0 . 1 0 1 0

D e p e n d e n t M e a n 4 . 1 8 5 2 3 A d j R - S q 0 . 0 8 2 7

C o e f f V a r 7 1 . 5 1 1 3 6

P a r a m e t e r E s t i m a t e s

V a r i a b l e L a b e l D F P a r a m e t e r

E s t i m a t e S t a n d a r d

E r r o r t V a l u e P r > | t |

I n t e r c e p t I n t e r c e p t 1 - 0 . 7 1 5 2 8 2 . 1 2 9 7 8 - 0 . 3 4 0 . 7 3 8 4

U n d e r g r a d U n d e r g r a d 1 0 . 1 7 7 4 5 0 . 0 7 5 6 1 2 . 3 5 0 . 0 2 3 0

M u r d e r R a t e r e g r e s s i o n b y t h e L i t e r a c y R a t e T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 1 6

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

M u r d e r R a t e r e g r e s s i o n b y t h e L i t e r a c y R a t e T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 1 6

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

F i t D i a g n o s t i c s f o r V A R 6

0 . 0 8 2 7A d j R - S q u a r e 0 . 1 0 1R - S q u a r e

8 . 9 5 7 5M S E 4 9E r r o r D F

2P a r a m e t e r s 5 1O b s e r v a t i o n s

P r o p o r t i o n L e s s 0 . 0 0 . 4 0 . 8

R e s i d u a l

0 . 0 0 . 4 0 . 8

F i t – M e a n

- 5

0

5

1 0

1 5

- 7 . 5 - 1 . 5 4 . 5 1 0 . 5

R e s i d u a l

0

1 0

2 0

3 0

4 0

P er

ce nt

0 1 0 2 0 3 0 4 0 5 0

O b s e r v a t i o n

0

2

4

6

C oo

k' s

D 0 5 1 0 1 5 2 0

P r e d i c t e d V a l u e

0

5

1 0

1 5

2 0

O bs

er ve

d

- 2 - 1 0 1 2

Q u a n t i l e

- 5

0

5

1 0

1 5

R es

id ua

l

0 . 0 5 0 . 1 5 0 . 2 5

L e v e r a g e

- 2

0

2

4

6

8

R S

tu de

nt

3 4 5 6 7 8

P r e d i c t e d V a l u e

- 2

0

2

4

6

8

R S

tu de

nt 3 4 5 6 7 8

P r e d i c t e d V a l u e

- 5

0

5

1 0

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R es

id ua

l

M u r d e r R a t e r e g r e s s i o n b y t h e L i t e r a c y R a t e T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 1 7

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

2 0 3 0 4 0 5 0

U n d e r g r a d

- 5

0

5

1 0

1 5

R e

si du

a l

R e s i d u a l s f o r V A R 6

M u r d e r R a t e r e g r e s s i o n b y t h e L i t e r a c y R a t e T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 1 8

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

2 0 3 0 4 0 5 0

U n d e r g r a d

- 5

0

5

1 0

1 5

2 0

M ur

de r

R a

te (

pe r

1 0

0 ,0

0 0

)

9 5 % P r e d i c t i o n L i m i t s9 5 % C o n f i d e n c e L i m i t sF i t

0 . 0 8 2 7A d j R - S q u a r e 0 . 1 0 1R - S q u a r e

8 . 9 5 7 5M S E 4 9E r r o r D F

2P a r a m e t e r s 5 1O b s e r v a t i o n s

F i t P l o t f o r V A R 6

M u r d e r R a t e r e g r e s s i o n b y t h e I n c o m e L e v e l s T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 1 9

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

M u r d e r R a t e r e g r e s s i o n b y t h e I n c o m e L e v e l s T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 1 9

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

N u m b e r o f O b s e r v a t i o n s R e a d 5 1

N u m b e r o f O b s e r v a t i o n s U s e d 5 1

A n a l y s i s o f V a r i a n c e

S o u r c e D F S u m o f

S q u a r e s M e a n

S q u a r e F V a l u e P r > F

M o d e l 1 2 3 2 . 2 5 6 1 4 2 3 2 . 2 5 6 1 4 4 4 . 4 6 < . 0 0 0 1

E r r o r 4 9 2 5 5 . 9 9 8 3 1 5 . 2 2 4 4 6

C o r r e c t e d T o t a l 5 0 4 8 8 . 2 5 4 4 5

R o o t M S E 2 . 2 8 5 7 1 R - S q u a r e 0 . 4 7 5 7

D e p e n d e n t M e a n 4 . 1 8 5 2 3 A d j R - S q 0 . 4 6 5 0

C o e f f V a r 5 4 . 6 1 3 6 4

P a r a m e t e r E s t i m a t e s

V a r i a b l e L a b e l D F P a r a m e t e r

E s t i m a t e S t a n d a r d

E r r o r t V a l u e P r > | t |

I n t e r c e p t I n t e r c e p t 1 - 1 . 2 8 8 8 2 0 . 8 8 1 1 9 - 1 . 4 6 0 . 1 5 0 0

P e r _ c a p i t a _ I n c o m e P e r c a p i t a I n c o m e 1 0 . 0 0 0 1 1 2 5 6 0 . 0 0 0 0 1 6 8 8 6 . 6 7 < . 0 0 0 1

M u r d e r R a t e r e g r e s s i o n b y t h e I n c o m e L e v e l s T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 2 0

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

M u r d e r R a t e r e g r e s s i o n b y t h e I n c o m e L e v e l s T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 2 0

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

F i t D i a g n o s t i c s f o r V A R 6

0 . 4 6 5A d j R - S q u a r e 0 . 4 7 5 7R - S q u a r e 5 . 2 2 4 5M S E

4 9E r r o r D F 2P a r a m e t e r s

5 1O b s e r v a t i o n s

P r o p o r t i o n L e s s 0 . 0 0 . 4 0 . 8

R e s i d u a l

0 . 0 0 . 4 0 . 8

F i t – M e a n

- 5

0

5

1 0

- 7 - 5 - 3 - 1 1 3 5 7

R e s i d u a l

0

1 0

2 0

3 0

P er

ce nt

0 1 0 2 0 3 0 4 0 5 0

O b s e r v a t i o n

0

1 0

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k' s

D 0 5 1 0 1 5 2 0

P r e d i c t e d V a l u e

0

5

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2

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5 1 0 1 5

P r e d i c t e d V a l u e

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0

2

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tu de

nt 5 1 0 1 5

P r e d i c t e d V a l u e

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M u r d e r R a t e r e g r e s s i o n b y t h e I n c o m e L e v e l s T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 2 1

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

2 5 0 0 0 5 0 0 0 0 7 5 0 0 0 1 0 0 0 0 0 1 2 5 0 0 0 1 5 0 0 0 0 1 7 5 0 0 0

P e r c a p i t a I n c o m e

- 4

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0

2

4

6

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M u r d e r R a t e r e g r e s s i o n b y t h e I n c o m e L e v e l s T u e s d a y , N o v e m b e r 1 4 , 2 0 1 7 0 6 : 5 0 : 2 1 P M 2 2

T h e R E G P r o c e d u r e M o d e l : M O D E L 1

D e p e n d e n t V a r i a b l e : V A R 6 M u r d e r R a t e ( p e r 1 0 0 , 0 0 0 )

2 5 0 0 0 5 0 0 0 0 7 5 0 0 0 1 0 0 0 0 0 1 2 5 0 0 0 1 5 0 0 0 0 1 7 5 0 0 0

P e r c a p i t a I n c o m e

0

5

1 0

1 5

2 0

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9 5 % P r e d i c t i o n L i m i t s9 5 % C o n f i d e n c e L i m i t sF i t

0 . 4 6 5A d j R - S q u a r e 0 . 4 7 5 7R - S q u a r e 5 . 2 2 4 5M S E

4 9E r r o r D F 2P a r a m e t e r s

5 1O b s e r v a t i o n s

F i t P l o t f o r V A R 6

  • The Contents Procedure
    • WORK.IMPORT
      • Attributes
      • Engine/Host Information
      • Variables
  • The Reg Procedure
    • MODEL1
      • Fit
        • VAR6
          • Number of Observations
          • Analysis of Variance
          • Fit Statistics
          • Parameter Estimates
      • Observation-wise Statistics
        • VAR6
          • Diagnostic Plots
            • Fit Diagnostics
          • Residual Plots
            • GunMurders
          • Fit Plot
  • The Reg Procedure
    • MODEL1
      • Fit
        • VAR6
          • Number of Observations
          • Analysis of Variance
          • Fit Statistics
          • Parameter Estimates
      • Observation-wise Statistics
        • VAR6
          • Diagnostic Plots
            • Fit Diagnostics
          • Residual Plots
            • GunOwnership
          • Fit Plot
  • The Reg Procedure
    • MODEL1
      • Fit
        • VAR6
          • Number of Observations
          • Analysis of Variance
          • Fit Statistics
          • Parameter Estimates
      • Observation-wise Statistics
        • VAR6
          • Diagnostic Plots
            • Fit Diagnostics
          • Residual Plots
            • Poverty_rate_by_house_hold_incom
          • Fit Plot
  • The Reg Procedure
    • MODEL1
      • Fit
        • VAR6
          • Number of Observations
          • Analysis of Variance
          • Fit Statistics
          • Parameter Estimates
      • Observation-wise Statistics
        • VAR6
          • Diagnostic Plots
            • Fit Diagnostics
          • Residual Plots
            • Undergrad
          • Fit Plot
  • The Reg Procedure
    • MODEL1
      • Fit
        • VAR6
          • Number of Observations
          • Analysis of Variance
          • Fit Statistics
          • Parameter Estimates
      • Observation-wise Statistics
        • VAR6
          • Diagnostic Plots
            • Fit Diagnostics
          • Residual Plots
            • Per_capita_Income
          • Fit Plot

SAS Regression Soln/SASSolutionprint.xps

Results: Program 1

http://192.168.192.128/SASStudio/36/sasexec/submissions/27faf341-47f...

The CONTENTS Procedure

Data Set Name

Observations

WORK.IMPORT51

Member Type

Variables

DATA9

Engine

Indexes

V90

Created

Observation Length

11/14/2017 18:50:2288

Last Modified

Deleted Observations

11/14/2017 18:50:220

ProtectionCompressed

NO

Data Set TypeSorted

NO

Label

Data Representation

SOLARIS_X86_64, LINUX_X86_64, ALPHA_TRU64, LINUX_IA64

Encoding

utf-8 Unicode (UTF-8)

Engine/Host Dependent Information

Data Set Page Size

65536

Number of Data Set Pages

1

First Data Page

1

Max Obs per Page

743

Obs in First Data Page

51

Number of Data Set Repairs

0

Filename

/tmp/SAS_work93340000368B_localhost.localdomain/SAS_workEB5F0000368B_localhost.localdomain/import.sas7bdat

Release Created

9.0401M4

Host Created

Linux

Inode Number

271800

Access Permission

rw-rw-r--

Owner Name

sasdemo

File Size

128KB

File Size (bytes)

131072

Alphabetic List of Variables and Attributes

#VariableTypeLenFormatInformatLabel

4

GunMurdersNum8BEST.GunMurders

Murder Rate regression using Gun Murders per Population

5

GunOwnershipNum8BEST.GunOwnership

3

MurdersNum8BEST.Murders

9

Per_capita_IncomeNum8BEST.Per capita Income

2

PopulationNum8BEST.Population

7

Poverty_rate_by_house_hold_incomNum8BEST.Poverty rate by house hold income

1

StateChar20$20.$20.State

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8

UndergradNum8BEST.Undergrad

6

VAR6Num8BEST.Murder Rate (per 100,000)

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

Results: Program 1

http://192.168.192.128/SASStudio/36/sasexec/submissions/27faf341-47f...

Number of Observations Read

51

Number of Observations Used

51

Analysis of Variance

Sum of

Mean

SourceDFSquaresSquareF ValuePr > F

Model

130.1449730.144973.220.0787

Error

49458.109489.34917

Corrected Total

50488.25445

Root MSE

R-Square

3.057640.0617

Dependent Mean

Adj R-Sq

4.185230.0426

Coeff Var

73.05790

Parameter Estimates

Parameter

Standard

Murder Rate regression using Gun Murders per Population

VariableLabelDFEstimateErrort ValuePr > |t|

Intercept

Intercept13.578950.545276.56<.0001

GunMurders

GunMurders10.003290.001831.800.0787

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

2 of 1711/14/2017 6:53 PM

Results: Program 1http://192.168.192.128/SASStudio/36/sasexec/submissions/27faf341-47f...

3 of 1711/14/2017 6:53 PM

Results: Program 1http://192.168.192.128/SASStudio/36/sasexec/submissions/27faf341-47f...

4 of 1711/14/2017 6:53 PM

Results: Program 1

http://192.168.192.128/SASStudio/36/sasexec/submissions/27faf341-47f...

Murder Rate regression by Gun Ownership per Population

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

Number of Observations Read

51

Number of Observations Used

51

Analysis of Variance

Sum of

Mean

SourceDFSquaresSquareF ValuePr > F

5 of 17

11/14/2017 6:53 PM

Model

156.8493256.849326.460.0143

Error

49431.405138.80419

Corrected Total

50488.25445

Root MSE

R-Square

2.967180.1164

Dependent Mean

Adj R-Sq

4.185230.0984

Coeff Var

70.89657

Parameter Estimates

Parameter

Standard

VariableLabelDFEstimateErrort ValuePr > |t|

Intercept

Intercept16.986881.178235.93<.0001

Results: Program 1

http://192.168.192.128/SASStudio/36/sasexec/submissions/27faf341-47f...

Parameter Estimates

Parameter

Standard

VariableLabelDFEstimateErrort ValuePr > |t|

GunOwnership

GunOwnership1-7.583262.98427-2.540.0143

Murder Rate regression by Gun Ownership per Population

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

6 of 1711/14/2017 6:53 PM

Results: Program 1http://192.168.192.128/SASStudio/36/sasexec/submissions/27faf341-47f...

7 of 1711/14/2017 6:53 PM

Results: Program 1

http://192.168.192.128/SASStudio/36/sasexec/submissions/27faf341-47f...

Murder Rate regression by Poverty Rate

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

Number of Observations Read

51

Number of Observations Used

51

Analysis of Variance

Sum of

Mean

SourceDFSquaresSquareF ValuePr > F

8 of 17

11/14/2017 6:53 PM

Model

198.9110698.9110612.450.0009

Error

49389.343407.94578

Corrected Total

50488.25445

Root MSE

R-Square

2.818830.2026

Dependent Mean

Adj R-Sq

4.185230.1863

Coeff Var

67.35176

Parameter Estimates

Parameter

Standard

VariableLabelDFEstimateErrort ValuePr > |t|

Intercept

Intercept1-2.628431.97112-1.330.1885

Results: Program 1

http://192.168.192.128/SASStudio/36/sasexec/submissions/27faf341-47f...

Parameter Estimates

Parameter

Standard

VariableLabelDFEstimateErrort ValuePr > |t|

Poverty_rate_by_house_hold_incom

Poverty rate by house hold income10.458560.129973.530.0009

Murder Rate regression by Poverty Rate

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

9 of 1711/14/2017 6:53 PM

Results: Program 1http://192.168.192.128/SASStudio/36/sasexec/submissions/27faf341-47f...

10 of 1711/14/2017 6:53 PM

Results: Program 1

http://192.168.192.128/SASStudio/36/sasexec/submissions/27faf341-47f...

Murder Rate regression by the Literacy Rate

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

Number of Observations Read

51

Number of Observations Used

51

Analysis of Variance

Sum of

Mean

SourceDFSquaresSquareF ValuePr > F

11 of 17

11/14/2017 6:53 PM

Model

149.3348949.334895.510.0230

Error

49438.919568.95754

Corrected Total

50488.25445

Root MSE

R-Square

2.992920.1010

Dependent Mean

Adj R-Sq

4.185230.0827

Coeff Var

71.51136

Parameter Estimates

Parameter

Standard

VariableLabelDFEstimateErrort ValuePr > |t|

Intercept

Intercept1-0.715282.12978-0.340.7384

Results: Program 1

http://192.168.192.128/SASStudio/36/sasexec/submissions/27faf341-47f...

Parameter Estimates

Parameter

Standard

VariableLabelDFEstimateErrort ValuePr > |t|

Undergrad

Undergrad10.177450.075612.350.0230

Murder Rate regression by the Literacy Rate

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

12 of 1711/14/2017 6:53 PM

Results: Program 1http://192.168.192.128/SASStudio/36/sasexec/submissions/27faf341-47f...

13 of 1711/14/2017 6:53 PM

Results: Program 1

http://192.168.192.128/SASStudio/36/sasexec/submissions/27faf341-47f...

Murder Rate regression by the Income Levels

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

Number of Observations Read

51

Number of Observations Used

51

Analysis of Variance

Sum of

Mean

SourceDFSquaresSquareF ValuePr > F

14 of 17

11/14/2017 6:53 PM

Model

1232.25614232.2561444.46<.0001

Error

49255.998315.22446

Corrected Total

50488.25445

Root MSE

R-Square

2.285710.4757

Dependent Mean

Adj R-Sq

4.185230.4650

Coeff Var

54.61364

Parameter Estimates

Parameter

Standard

VariableLabelDFEstimateErrort ValuePr > |t|

Intercept

Intercept1-1.288820.88119-1.460.1500

Results: Program 1

http://192.168.192.128/SASStudio/36/sasexec/submissions/27faf341-47f...

Parameter Estimates

Parameter

Standard

VariableLabelDFEstimateErrort ValuePr > |t|

Per_capita_Income

Per capita Income10.000112560.000016886.67<.0001

Murder Rate regression by the Income Levels

The REG Procedure

Model: MODEL1

Dependent Variable: VAR6 Murder Rate (per 100,000)

15 of 1711/14/2017 6:53 PM

Results: Program 1http://192.168.192.128/SASStudio/36/sasexec/submissions/27faf341-47f...

16 of 1711/14/2017 6:53 PM

Results: Program 1http://192.168.192.128/SASStudio/36/sasexec/submissions/27faf341-47f...

17 of 1711/14/2017 6:53 PM