All About T-Score
-
Now that you have estimated T score, it is about time to look for a school that fits this. Please go to this site http://app.sis.moe.gov.sg/schinfo/SIS_AdvSearch.asp, just key in the score in the last box, a list of suitable school will be shown
-
[quote]So now you have to use Skewed Gaussian, but by how much. [/quote]
Hi crazydad , can you help this suaku parent to put it in more layman's term. :oops:
Do you mean first T score formula shall apply using their raw score, then Skewed Gaussian will apply to moderate the T score further if the whole cohort don't do well, the Skewed Gaussian is used to push up the marks of the whole cohort ?
Thank you. -
justsay:
[quote]So now you have to use Skewed Gaussian, but by how much.
Hi crazydad , can you help this suaku parent to put it in more layman's term. :oops:
Do you mean first T score formula shall apply using their raw score, then Skewed Gaussian will apply to moderate the T score further if the whole cohort don't do well, the Skewed Gaussian is used to push up the marks of the whole cohort ?
Thank you.[/quote]Statistically, the mean score and the standard deviation are already a moderating tools. What i can say about the T-Score for Chinese (with 80% scoring A and A*) is that, the mean score is VERY high at least 82 and the SD is about 7-8 marks. It means that your child has to score above 82 before he can obtain a T-score of 50 and above. Any marks below the mean score would result in score below 50 for Chinese. I am sure alot of parents dont realise that, thinking that as long as my child score 75 marks would be sufficient. That was why a student who scored 3A* and 1A (chinese) would get a score of 244. The A for Chinese would have given him a T-score of 41 if he scores only 75 marks. -
[quote]Hi All,
Base on the feedback from all parents and using the result from 2007. 2007 PSLE is pretty similar to 2009; very difficult math, easy Chinese and some tricky Science questions.
I have estimated the parameter to calculate the T score as followed;
CL: Mean = 78, StdDev = 10
EL: Mean = 73, StdDev = 11
Math : Mean = 63, StdDev = 9
Sci : Mean = 67, StdDev = 12
Use the formula : 50 - 10 * (your score - Mean)/StdDev
for each subject. Sum them up, you should get a glimps.
:xedfingers:[/quote]For EL and CL, need to divide the total score by 2
Shouldn't the mean for Eng and MT be around 100+ since the total score is 200 respectively? -
justsay:
[quote]So now you have to use Skewed Gaussian, but by how much.
Hi crazydad , can you help this suaku parent to put it in more layman's term. :oops:
Do you mean first T score formula shall apply using their raw score, then Skewed Gaussian will apply to moderate the T score further if the whole cohort don't do well, the Skewed Gaussian is used to push up the marks of the whole cohort ?
Thank you.[/quote]Layman Term as followed;
For example, base on CL raw score in 2007, 2% of students has less than 50 mark and 81% of student has more than 75 mark.
if the cohort has 50,000 student, then 1000 student failed and 40,000 student score 75 mark or more. So average point should be close to 80 point right?
And everybody score are around 80, says from 75 to 90 mark. so the spread will be very narrow. -
P6boy-dad:
Statistically, the mean score and the standard deviation are already a moderating tools. What i can say about the T-Score for Chinese (with 80% scoring A and A*) is that, the mean score is VERY high at least 82 and the SD is about 7-8 marks. It means that your child has to score above 82 before he can obtain a T-score of 50 and above. Any marks below the mean score would result in score below 50 for Chinese. I am sure alot of parents dont realise that, thinking that as long as my child score 75 marks would be sufficient. That was why a student who scored 3A* and 1A (chinese) would get a score of 244. The A for Chinese would have given him a T-score of 41 if he scores only 75 marks.[/quote]totally agreejustsay:
[quote]So now you have to use Skewed Gaussian, but by how much.
Hi crazydad , can you help this suaku parent to put it in more layman's term. :oops:
Do you mean first T score formula shall apply using their raw score, then Skewed Gaussian will apply to moderate the T score further if the whole cohort don't do well, the Skewed Gaussian is used to push up the marks of the whole cohort ?
Thank you. -
CrazyDad:
Layman Term as followed;justsay:
[quote]So now you have to use Skewed Gaussian, but by how much.
Hi crazydad , can you help this suaku parent to put it in more layman's term. :oops:
Do you mean first T score formula shall apply using their raw score, then Skewed Gaussian will apply to moderate the T score further if the whole cohort don't do well, the Skewed Gaussian is used to push up the marks of the whole cohort ?
Thank you.
For example, base on CL raw score in 2007, 2% of students has less than 50 mark and 81% of student has more than 75 mark.
if the cohort has 50,000 student, then 1000 student failed and 40,000 student score 75 mark or more. So average point should be close to 80 point right?
And everybody score are around 80, says from 75 to 90 mark. so the spread will be very narrow.[/quote]Thanks for the explanation. What I actually want to know more is the Skewed Gaussian. Thanks.... :celebrate: -
Vikaesh:
:roll: Only time can tell, there are too many unknowns;CrazyDad:
Hi All,
Base on the feedback from all parents and using the result from 2007. 2007 PSLE is pretty similar to 2009; very difficult math, easy Chinese and some tricky Science questions.
I have estimated the parameter to calculate the T score as followed;
CL: Mean = 78, StdDev = 10
EL: Mean = 73, StdDev = 11
Math : Mean = 63, StdDev = 9
Sci : Mean = 67, StdDev = 12
Use the formula : 50 - 10 * (your score - Mean)/StdDev
for each subject. Sum them up, you should get a glimps.
How close will our PSLE results be to the score we get using yr estimations [e.g. plus OR minus 3]
:xedfingers:
1. the actual scores are unknown
2. the parameters estimated base on even more unknown
get the picture? -
justsay:
Thanks for the explanation. What I actually want to know more is the Skewed Gaussian. Thanks.... :celebrate:[/quote]
Layman Term as followed;CrazyDad:
[quote=\"justsay\"]
Hi crazydad , can you help this suaku parent to put it in more layman's term. :oops:
Do you mean first T score formula shall apply using their raw score, then Skewed Gaussian will apply to moderate the T score further if the whole cohort don't do well, the Skewed Gaussian is used to push up the marks of the whole cohort ?
Thank you.
For example, base on CL raw score in 2007, 2% of students has less than 50 mark and 81% of student has more than 75 mark.
if the cohort has 50,000 student, then 1000 student failed and 40,000 student score 75 mark or more. So average point should be close to 80 point right?
And everybody score are around 80, says from 75 to 90 mark. so the spread will be very narrow.
Long story...
can check out Wikipedia for the glory details though... -
CrazyDad:
Thanks for the explanation. What I actually want to know more is the Skewed Gaussian. Thanks.... :celebrate:justsay:
[quote=\"CrazyDad\"]
Layman Term as followed;
For example, base on CL raw score in 2007, 2% of students has less than 50 mark and 81% of student has more than 75 mark.
if the cohort has 50,000 student, then 1000 student failed and 40,000 student score 75 mark or more. So average point should be close to 80 point right?
And everybody score are around 80, says from 75 to 90 mark. so the spread will be very narrow.
Long story...
can check out Wikipedia for the glory details though...[/quote]Please go to Wikipedia and search for \"skewed normal distribution\"
:lol:
Hello! It looks like you're interested in this conversation, but you don't have an account yet.
Getting fed up of having to scroll through the same posts each visit? When you register for an account, you'll always come back to exactly where you were before, and choose to be notified of new replies (either via email, or push notification). You'll also be able to save bookmarks and upvote posts to show your appreciation to other community members.
With your input, this post could be even better π
Register Login