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I) Analyzing and interpreting data

Dr. Fuller wanted to study whether Latino children's English ability affects their learning outcomes inkindergarten.

For this study Dr. Fuller analyzed data from the Early Childhood Longitudinal Study (ECLS-K) Kindergarten Class of 1998-99, sponsored by the National Center of Education Statistics..Using a multistage probabilistic sampling design, the ECLS-K is based on a nationally representative sample of approximately 20,000 kindergarteners. Dr. Fuller analyzed a randomly selected subsample of Latino children.

The variables analyzed are the following:

1) Math test score in kindergarten:  Range from 6 to 84 points. Math tests are curriculum-based assessments based on the National Assessment of Educational Progress framework of content areas and domains. 

2)  English ability (OLDS), whichwas measured by students' test scores on the English Oral Language Development Scale taken in the fall of kindergarten.  The ECLS-K study used the OLDS to determine whether students from non-English speaking homes had the necessary minimum English skills to take cognitive assessments in English. The OLDS scores range from 0-60 points.

Given that socioeconomic status is such a strong predictor of learning outcomes, he decided to include this variable in his analyses.

3) Students' socioeconomic status (SES) isa standardized measure with a mean of 0 and astandard deviation of 1.  It represents student families'socioeconomic status based on mothers' and fathers' education, mothers' and fathers'occupational status, and householdincome, measured in the fall of kindergarten and in thespring of first grade. 

Dr Fuller gave you the following tables/analyses and went traveling with his son to Turkey. You are responsible for finishing the required computations and reporting the mainresults of his study. He ran several analyses, including descriptive statistics, bivariate correlations, and several regression models (shown in the next page).

Table 1:Descriptive Information

Variable

Obs

Mean

Std. Dev

Min

Max

Math score

 2108

17.57009

7.313663

6.24

71

SES

 2108

-.4145897

.7070371

-3.515

2.785

OLDS

 2108

36.42884

18.71745

0

60

Table 2: Bivariate correlation(obs=2108)

 

Math score

SES

OLDS

Math score

1.0000

 

 

SES

 0.4711

1.0000

 

OLDS

0.3639

0.4807

1.0000

Model 1: English ability effects on Math Achievement

Source

Sum of Squares

Df

Mean Square

 

Number of obs =    2108

F(1,  2106) =  321.37

Model

14921.361

  1

14921.361

 

Prob> F  =  0.0000

Residual

97781.3687 

2106

46.4298997

 

R-squared     =  0.1324

Total

112702.73

2107

53.4896676

 

 

Math Score

Coefficient

Std Err.

T

P>|t|

OLDS

.1421757

.0079309

17.93

0.000

Constant

12.39079

.3248009

38.15

0.000  

 

 

 

 

 

Model 2: SES effects on Math Achievement

Source

Sum of Squares

Df

Mean Square

 

 

 

Model

25008.6541

1

25008.6541

 

 

 

Residual

87694.0755

2106

41.6401118

 

 

 

Total

112702.73

2107

53.4896676

 

 

 

Math Score

Coefficient

Std Err.

T

P>|t|

SES

4.872712  

.1988298   

24.51

0.000    

Constant

19.59027  

.1629372  

120.23  

0.000    

Model 3: Socioeconomic Status and English ability effects on Math Achievement

Source

Sum of Squares

Df

Mean Square

 

Number of obs =   2108

F(2,  2105) =  344.23

 

Model

27776.0744

2

13888.0372

 

Prob> F =  0.0000

 

Residual

84926.6553

2105

40.3452044

 

R-squared =  0.2465

Total

112702.73

2107

53.4896676

 

 









Math Score

Coefficient

Std Err.

T

P>|t|

 

OLDS

.0698275

.0084311

17.85

0.000

 

SES

3.984045

.2231973

   8.28

0.000

 

Constant

16.6781

.3864713

43.15

0.000  

 

 

 

 

 

 

 

Please respond to the following questions

3) What proportion of variance is explained by Model 2?

4) Write the regression equation of Model 3 and explain each of its parts. No need to describe results yet.

5) Based on Model 3, compute the standardized slopesfor SES and English ability; interpret them, and specify what additional information is learned from the standardized slopes that cannot be learned from the unstandardized slopes.

6) Describe in one or two paragraphs the importance of using multiple regression analysis(instead of only using bivariate regression) for studying the relationship between children's language ability and math score. What additional information is learned from multiple regression that cannot be learned from the simple bivariate regression?

7) Explain in two paragraphs the main results of Model 3.

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