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Es wird empfohlen, sich mit der rank()-Funktion vertraut zu machen, bevor Sie mit diesem Tutorial fortfahren. |
Für dieses Tutorial werden wir den Datensatz verwenden, der mit den Untersuchungsergebnissen geladen ist.
Der Datensatz enthält zwei Spalten: Percentiles| Info |
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Percentile (or centile) is the value of a variable below which a certain percent of observations fall. For example, the 20th percentile is the value (or score) below which 20 percent of the observations may be found. |
You desire to create table showing percentile next to score for each student. - Create new table with student ID drill-down and Score indicator.
- Create new indicator - Percentile.
- Add following formula into Indicators settings.
- Setup percentage to Unit and associate it with appropriate Format.
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int records = aggregatePrevLevel(1){L_ID_COUNT}
int rank = rank() {M_SCORE}
double percentile = 1-(rank/records)
return percentile
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- line: Store the number of total records (students). Since, student drill-down is used, aggregation one level up is needed.
- line: Obtain rank for each record.
- line: Recalculate rank to percentile. For example, if rank is 5 from 100 students, the percentile will be: 1-(5/100) = 95%.
Quantiles| Info |
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A value which divides a set of data into equal proportions. Examples are median, quartile and decile. |
You desire to create KPI label showing the median of exam scores. - Create new KPI label.
- Create new indicator - Quantile.
- Add following formula into Indicators settings.
- Create quantile variable, to be able to dynamically change observed quantile.
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int records = L_ID_COUNT
double groups = 100/@quantile
int key = round(records-records/groups)
double median = 0
membersSum('L_ID'){
rank = rank(){M_SCORE}
if (rank == key){
median = M_SCORE
}
}
return median
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- Use first three lines to convert provided quantile variable and find the corresponding position within the set of scores.
- Obtain rank for each score, aggregated to the level of student's ID.
- If the current rank equals the position, store score to the median variable.
Next Steps |