• T-scores are ‘Transformed Scores’ used to standardise raw scores across the level or cohort.
• T-scores give the relative rank or position of a pupil’s performance compared to all the other pupils in that subject in the same exam.
• T-scores can be computed for individual subjects and then summed up as a single aggregate T-score, say in the case of PSLE.
• T-scores allow pupils to be ranked fairly.
How are T-Scores calculated in PSLE?
• As mentioned, T-score is the transformed or adjusted score a student will get for a subject, after factoring in the level or cohort’s mean and SD for that subject.
• Formula for T-Score
X = Raw score of student in the subject
Y = Average or Mean Score of the level or cohort
Z = Standard Deviation (SD) of the level or cohort Standard Deviation (SD) is the spread of the marks around the average.
Why Standard Deviation (SD) matters?
• Here is an example to illustrate that with the same mean, SD
or the spread of marks can vary.
• Example 1 –
Allan, Bernard and Charles have $45, $50 and $55 respectively. They have an average of $50 each.
Example 2 –
Dan, Edward and Frank have $10, $50 and $90 respectively. They also have an average of $50 each.
• In Example 1, the spread (from $45 and $55 to average of
$50) is smaller than the spread
• in Example 2 (from $10 and $90 to average of $50)
• Conclusion: Despite having the same mean, Example 1’s data have a smaller SD or “spread from the mean” as compared to that of Example 2