How to calculate your ATAR from trial/past paper marks (1 Viewer)

carrotsss

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What’s your favourite part about farming!
me personally ive never been on a farm so I wouldn’t know anything about the really cute potty lambs. they would be my favourite part if I was a farmer though but luckily I’m just a city slicker
 

carrotsss

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No wayyy you have lambs??? Do you feed them carrots
the lambs don’t really like carrots they’re more into grass (and the chickens food) but we feed the neighbour’s horses carrots! it’s so fun feeding them
 

carrotsss

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can u adopt me
I won’t even be living on the farm anymore in a few months because I have to move for uni :(

I rlly want to get myself a place like this when I’m older though and I guess I’ll still live here in holidays
 

Awesome8r

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I won’t even be living on the farm anymore in a few months because I have to move for uni :(

I rlly want to get myself a place like this when I’m older though and I guess I’ll still live here in holidays
what uni do you plan on going to?
 

ExtremelyBoredUser

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I inserted these equations using a simple IF() formula for whether a student is within that 25th percentile, with both MAX(x,0) and MIN(x,100) functions to prevent an extreme increase/decrease in ATAR although this shouldn't ever really be necessary notwithstanding any errors in the fairly manual data entry process. All of the English scaled marks are then split into individual units and placed in the B column below the calculator. From this list the sum of the best 2 units of English is determined through the sum of a =sortn function which finds the 2 greatest units of scaled marks. Then, for the remaining 8 units needed for calculation, a similar process of unit splitting occurs into column D, and to account for cases in which more than 2 units of English are counted, the worst 4 units out of the six available English units are added to the list using an ascending =sortn function. Similar to the process for English, the sum of the remaining best 8 units is determined through the sum of a =sortn function, which is then summed once more with the best 2 units of English to find the aggregate. Due to the use of =sum(sortn) functions, it isn't immediately visible which units were counted, so I got around this by using another =sortn function (without =sum) which creates a list of counted units in columns E and F (for names and marks respectively), by using two sortn functions (one for English and one for the rest) with an area that includes all of the names and marks for each subject, with the marks as the sorting column, in descending order. The 'Counted units' cell in row 6 for each subject then just employs a simple =COUNTIF check for how many times the name of the subject is included in this sorted list of the top 10 units, with a simple failsafe so that it is equal to 0 where the scaled mark is zero, and equal to 2 when above 2 are present (which can occur for English where less than 10 units are present and it is equal to 0 in some rare cases - unimportant for real calculations but nonetheless included for quality of life). There is also a simple detector for when a 0 is present in the top 10 units list using another =sortn function in ascending order (as a 0 will be the lowest value) which notifies the user that less than 10 units are present.

Finally, the conversion from aggregate to ATAR is percentile-based, so it could not directly be modelled through a quadratic - this produced extreme inaccuracies at high ATAR ranges. I got around this by calculating the quadratics in sections, and found that quadratic formulas were remarkably accurate within small ranges of ~5 data points. Because the UAC data does not extend below 50, I created a simple quadratic by equating an aggregate of 0 to an ATAR of 0 and including the 50 and 55 data points to provide a relatively realistic curve below 50. These equations were then inserted using a simple =IFS formula, with an integrated limitation to provide an * for marks below 30 (both to mirror the HSC and to prevent usage in an area where the calculator is inaccurate), which is then rounded to the nearest 0.05 using an =MROUND function. I considered using more intense rounding below certain ATAR points to remove the pretence of that level of accuracy at low ATARs, but ended up resolving against it to allow usage of the calculator as a tool to track progress. Each of the "ATAR equivalent" cells use this same formula, except with the scaled mark multiplied by 5 or 10 (for 2 and 1 unit subjects respectively) in place of the aggregate.

I definitely plan on adding more years in the future (with a dropdown for each subject), but given the time commitment needed to model each subject it just isn't really feasible, and at the end of the day last year's data is usually going to be the most relevant anyway. Adding more subjects isn't really possible due to the limited available data on rawmarks.info, because I've added every subject with sufficient data.

Some statistics on the aligned->ATAR conversion from some quick testing with some ATARs published on this website + conquer from last year (this is not native functionality, if you want to do this then go into advanced mode and enter them in the "unrounded aligned marks", and make sure you put a number for the raw mark of mx2 so that mx1 counts as 2 units):
- UAC ATAR Calculator had an average delta of 0.1 ATAR points (minimum of 0, maximum of 0.25)
- My ATAR Calculator had an average delta of 0.1 ATAR points (minimum of 0, maximum of 0.2)
- Matrix ATAR Caculator had an average delta of 0.25 ATAR points (minimum of 0.15, maximum of 0.45)

Keep in mind most of the ATARs used were quite high (95-99.5) but this is a bit unavoidable given the dataset on BoS/conquer. Obviously the aligned->ATAR conversion isn't the main part of my calculator but it's accuracy is nonetheless important. It's also just impressive that matrix, a major tutor company with limitless resources has a less accurate calculator than I made fairly easily in a few days.

These tests are outdated - I may retest at a later date as these calculations are significantly more accurate after some improvements.

If you made it this far then thanks for reading and I hope you enjoy the calculator :)

Also if you find any issues or errors please let me know so I can fix them!
Super good bro I did not see this before, good job 😍 You should def try coding an ATAR calc as a CS project. personally i found for ME that trial marks didnt really help as they didnt give an accurate prediction but that might just be bc im an anomaly
 

ExtremelyBoredUser

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hopefully usyd! it just seems like such a nice uni and will be super convenient walking distance to where I’ll be living

hbu?
commuting time is rlly important when choosing uni bc being close to a uni will save so much time and money over time. Jokes aside between USYD vs UNSW, both are v. good and you can't go wrong.

Good thumb of rule for choosing unis is IMO


Priority:
1. Degree choice/interest
2. commuting time + scholarships (IF POSSIBLE dw if u didnt get any)
3. faculty
4. cost
5. friends/social
 
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carrotsss

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Super good bro I did not see this before, good job 😍 You should def try coding an ATAR calc as a CS project. personally i found for ME that trial marks didnt really help as they didnt give an accurate prediction but that might just be bc im an anomaly
that’s the plan! :)

the trial marks aren’t meant to be an accurate prediction (low key just click bait lol) but it’s more of a prediction of where you’re at at that point like what you’d get if your trials was your hsc if that makes sense
 

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