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irish

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ARFF
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Irish Educational Transitions Data
Below are shown data on educational transitions for a sample of 500
Irish schoolchildren aged 11 in 1967. The data were collected by
Greaney and Kelleghan (1984), and reanalyzed by Raftery and Hout (1985, 1993).
The data were also used, in a simplified form, as an example to illustrate
Bayesian model selection methods by Raftery (1988) and Kass and Raftery (1993).
In that simplified form, primary terminal leavers and cases with any missing
data were removed, leaving 441 cases. The Leaving Certificate variable
was used as the dependent variable in a logistic regression analysis.
The variables shown are as follows:
1. Sex: 1=male; 2=female.
2. DVRT (Drumcondra Verbal Reasoning Test Score).
3. Educational level attained:
1 Primary terminal leaver
2 Junior cycle incomplete: vocational school
3 Junior cycle incomplete: secondary school
4 Junior cycle terminal leaver: vocational school
5 Junior cycle terminal leaver: secondary school
6 Senior cycle incomplete: vocational school
7 Senior cycle incomplete: secondary school
8 Senior cycle terminal leaver: vocational school
9 Senior cycle terminal leaver: secondary school
10 3rd level incomplete
11 3rd level complete
4. Leaving Certificate. 1 if Leaving Certificate not taken; 2 if taken.
5. Prestige score for father's occupation
(calculated by Raftery and Hout, 1985). 0 if missing.
6. Type of school: 1=secondary; 2=vocational; 9=primary terminal leaver.
REFERENCES
Greaney, V. and Kelleghan, T. (1984). Equality of Opportunity in Irish
Schools. Dublin: Educational Company.
Kass, R.E. and Raftery, A.E. (1993). Bayes factors and model uncertainty.
Technical Report no. 254, Department of Statistics, University of Washington.
Revised version to appear in Journal of the American Statistical
Association.
Raftery, A.E. (1988). Approximate Bayes factors for generalized linear models.
Technical Report no. 121, Department of Statistics, University of Washington.
Raftery, A.E. and Hout, M. (1985). Does Irish education approach the
meritocratic ideal? A logistic analysis.
Economic and Social Review, 16, 115-140.
Raftery, A.E. and Hout, M. (1993). Maximally maintained inequality:
Expansion, reform and opportunity in Irish schools.
Sociology of Education, 66, 41-62.
OWNERSHIP STATEMENT
This data belongs to Vincent Greaney and Thomas Kelleghan,
Educational Research Centre, St. Patrick's College, Drumcondra,
Dublin 9, Ireland, who retain the copyright.
In the form given here, it may be used solely as an example for research
on the development of statistical methods. For any other use of the data,
permission must be obtained from the owners. Subject to this statement,
permission is hereby given to StatLib to distribute this data freely.
Submitted by Adrian Raftery (raftery@stat.washington.edu).
Copyright 1984 Vincent Greaney and Thomas Kelleghan.
Information about the dataset
CLASSTYPE: nominal
CLASSINDEX: 4

Leaving_Certificate (target) | nominal | 2 unique values 0 missing | |

Sex | nominal | 2 unique values 0 missing | |

DVRT | numeric | 68 unique values 0 missing | |

Educational_level | nominal | 10 unique values 6 missing | |

Prestige_score | numeric | 28 unique values 26 missing | |

Type_school | nominal | 3 unique values 0 missing |

0.9

Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3

1

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001

3.05

An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.

0

First quartile of mutual information between the nominal attributes and the target attribute.

1

Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

3.86

Standard deviation of the number of distinct values among attributes of the nominal type.

4.25

Average number of distinct values among the attributes of the nominal type.

-0.08

First quartile of skewness among attributes of the numeric type.

1

Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1

1

Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

15.33

First quartile of standard deviation of attributes of the numeric type.

1

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2

0

Error rate achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

1

Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

-0.45

Second quartile (Median) of kurtosis among attributes of the numeric type.

1

Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2

69.54

Second quartile (Median) of means among attributes of the numeric type.

1

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3

0.85

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump

0.31

Second quartile (Median) of mutual information between the nominal attributes and the target attribute.

0.13

Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump

0

Minimal mutual information between the nominal attributes and the target attribute.

0.18

Second quartile (Median) of skewness among attributes of the numeric type.

1

Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3

0.73

Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump

0.93

Maximum mutual information between the nominal attributes and the target attribute.

2

The minimal number of distinct values among attributes of the nominal type.

15.4

Second quartile (Median) of standard deviation of attributes of the numeric type.

0.96

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1

10

The maximum number of distinct values among attributes of the nominal type.

0.05

Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1

2.39

Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.

-0.4

Third quartile of kurtosis among attributes of the numeric type.

0.9

Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1

1

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001

1

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

0.96

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2

0.93

Third quartile of mutual information between the nominal attributes and the target attribute.

0

Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

0.05

Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2

1

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001

1

Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes

0.45

Third quartile of skewness among attributes of the numeric type.

1

Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

0.9

Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2

-0.5

First quartile of kurtosis among attributes of the numeric type.

15.46

Third quartile of standard deviation of attributes of the numeric type.

1

Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

0.96

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3

0.42

Average mutual information between the nominal attributes and the target attribute.

1

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1

0

Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

0.05

Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3