statistics interpret data

I need you to interpret these data and graph from my output (tell me what they mean). you just need to write some sentences to describe each page and please define each abreviated word and explain them as well (such as: df= degree of freedom is……..)  b/c they are some terms i do not understand. I’ve attached the SAS programming as well as if it can help. The doc to interpret is named “interpreting data stats” . 

Please be concise

Bachlors or Higher by Race

The UNIVARIATE Procedure

Variable: LessThanHighSchool

Moments

N

8

Sum Weights

8

Mean

24.

1

97375

Sum Observations

193.579

Std Deviation

8.89374775

Variance

79.0987491

Skewness

0.576002

Kurtosis

0.15540294

Uncorrected SS

5237.7949

Corrected SS

553.691244

Coeff Variation

36.7550106

Std Error Mean

3.14441467

Basic Statistical Measures

Location

Variability

Mean

24.19738

Std Deviation

8.89375

Median

21.87450

Variance

79.09875

Mode

.

Range

27.86400

Interquartile Range

9.42000

Tests for Location: Mu0=0

Test

Statistic

p Value

Student’s t

t

7.695351

Pr > |t|

0.0001

Sign

M

4

Pr >= |M|

0.0078

Signed Rank

S

18

Pr >= |S|

0.0078

Quantiles (Definition 5)

Quantile

Estimate

100% Max

38.9360

99%

38.9360

95%

38.9360

90%

38.9360

75% Q3

29.6655

50% Median

21.8745

25% Q1

20.2455

10%

11.0720

5%

11.0720

1%

11.0720

0% Min

11.0720

Extreme Observations

Lowest

Highest

Value

Obs

Value

Obs

11.072

1

21.736

5

19.753

2

22.013

4

20.738

7

24.105

3

21.736

5

35.226

8

22.013

4

38.936

6

Bachlors or Higher by Race

The UNIVARIATE Procedure

Variable: HighSchoolOrEquiv

Moments

N

8

Sum Weights

8

Mean

27.01075

Sum Observations

216.086

Std Deviation

4.24131805

Variance

17.9887788

Skewness

-1.6798523

Kurtosis

2.9906547

Uncorrected SS

5962.56638

Corrected SS

125.921452

Coeff Variation

15.7023335

Std Error Mean

1.49953238

Basic Statistical Measures

Location

Variability

Mean

27.01075

Std Deviation

4.24132

Median

28.16950

Variance

17.98878

Mode

.

Range

13.16700

Interquartile Range

3.90300

Tests for Location: Mu0=0

Test

Statistic

p Value

Student’s t

t

18.01278

Pr > |t|

<.0001 Sign M 4 Pr >= |M|

0.0078

Signed Rank

S

18

Pr >= |S|

0.0078

Quantiles (Definition 5)

Quantile

Estimate

100% Max

31.0410

99%

31.0410

95%

31.0410

90%

31.0410

75% Q3

29.6595

50% Median

28.1695

25% Q1

25.7565

10%

17.8740

5%

17.8740

1%

17.8740

0% Min

17.8740

Extreme Observations

Lowest

Highest

Value

Obs

Value

Obs

17.874

4

28.134

6

24.126

7

28.205

1

27.387

8

28.947

5

28.134

6

30.372

3

28.205

1

31.041

2

Data Stats

The REG Procedure

Model: MODEL1

Dependent Variable: Race

Number of Observations Read

8

Number of Observations Used

8

Analysis of Variance

Source

DF

Sum of
Squares

Mean
Square

F Value

Pr > F

Model

1

21.50094

21.50094

6.29

0.0460

Error

6

20.49906

3.41651

Corrected Total

7

42.00000

Root MSE

1.84838

R-Square

0.5119

Dependent Mean

4.50000

Adj R-Sq

0.4306

Coeff Var

41.07512

Parameter Estimates

Variable

DF

Parameter
Estimate

Standard
Error

t Value

Pr > |t|

Intercept

1

-0.26830

2.00996

-0.13

0.8982

LessThanHighSchool

1

0.19706

0.07855

2.51

0.0460

Data Stats

The REG Procedure
Model: MODEL1
Dependent Variable: Race

Data Stats

The REG Procedure
Model: MODEL1
Dependent Variable: Race

Number of Observations Read

8

Number of Observations Used

8

Analysis of Variance

Source

DF

Sum of
Squares

Mean
Square

F Value

Pr > F

Model

1

2.56475

2.56475

0.39

0.5552

Error

6

39.43525

6.57254

Corrected Total

7

42.00000

Root MSE

2.56370

R-Square

0.0611

Dependent Mean

4.50000

Adj R-Sq

-0.0954

Coeff Var

56.97104

Parameter Estimates

Variable

DF

Parameter
Estimate

Standard
Error

t Value

Pr > |t|

Intercept

1

8.35486

6.23718

1.34

0.2289

HighSchoolOrEquiv

1

-0.14272

0.22846

-0.62

0.5552

Data Stats

The REG Procedure
Model: MODEL1
Dependent Variable: Race

1

data newyorkeducationalachievement

;

input Race LessThanHighSchool HighSchoolOrEquiv SomeCollegeOrAssociates BachelorsOrHigher;

datalines;

1 11.072 28.205 24.961 35.762

2 19.753 31.041 28.632 20.574

3 24.105 30.372 29.189 16.334

4 22.013 17.874 14.312 45.802

5 21.736 28.947 21.993 27.324

6 38.936 28.134 19.999 12.931

7 20.738 24.126 25.859 29.276

8 35.226 27.387 21.495 15.893

;

run;

symbol v=none i=box00f co=black cv=black bwidth=2;

TITLE ‘Less Than High School by Race’;

PROC gplot DATA=newyorkeducationalachievement;

plot LessThanHighSchool*Race;

run;
symbol v=none i=box00f co=black cv=black bwidth=2;

TITLE ‘High School or Equivalent by Race’;

PROC gplot DATA=newyorkeducationalachievement;

plot HighSchoolOrEquiv*Race;

run;
symbol v=none i=box00f co=black cv=black bwidth=2;

TITLE ‘Some College or Associates by Race’;

PROC gplot DATA=newyorkeducationalachievement;

plot SomeCollegeOrAssociates*Race;

run;
symbol v=none i=box00f co=black cv=black bwidth=2;

TITLE ‘Bachlors or Higher by Race’;

PROC gplot DATA=newyorkeducationalachievement;

plot BachelorsOrHigher*Race;

run;

proc univariate data=newyorkeducationalachievement;

var LessThanHighSchool HighSchoolOrEquiv SomeCollegeOrAssociates BachelorsOrHigher;

run;

PROC REG DATA = newyorkeducationalachievement;

TITLE “Data Stats”;

MODEL Race = LessThanHighSchool;

run;

PROC REG DATA = newyorkeducationalachievement;

TITLE “Data Stats”;

MODEL Race = HighSchoolOrEquiv;

run;
PROC REG DATA = newyorkeducationalachievement;
TITLE “Data Stats”;

MODEL Race = SomeCollegeOrAssociates;

run;
PROC REG DATA = newyorkeducationalachievement;
TITLE “Data Stats”;

MODEL Race = BachelorsOrHigher;

run;

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