I’ve notice that once again it doesn’t “feel” like you need to have alacrity set to use specific break points to get 1.4, 1.3 or 1.2 GCD. Yes you still need them to be exactly at those, but it seems the 0.1 decimal points aren’t rounding up or down anymore.

As an example, if you have an activation time of 18 with zero alacrity and 17.7 with 1.15% alacrity, it seems to actually activate correctly.

I could be completely wrong, but has any of our number crunching members tested this out yet?

i thought it was only instant abilities that were affected by a floor function rounding of gcd...

channels and activations etc should reflect alacrity to .01 seconds..

you should be able to test with diagnostic scan and kolto probe and compare apm at different alacrity levels. you should be able to get a good estimate based on around 30 activations of each ability at each alacrity level.

http://www.swtor.com/community/showthread.php?t=966583

That’s not what Trixxie is asking. She is asking if the GCD is actually still rounded up, or if it is to three significant digits instead of two like on LIVE.

That’s not what Trixxie is asking. She is asking if the GCD is actually still rounded up, or if it is to three significant digits instead of two like on LIVE.

Pretty much.

I have a feeling the rounding has been entirely removed.

Only way to make sure is test on a instant hit abilitiy class like deception or concealment or auto attack dummy for many many minutes straight which is tedious to do. If channeling abilities were rounded/ affected they were always so in more minute steps...probably at .01 steps instead of .1 steps.

1.3 GCD is not realistic for dps with limited tertiary stats in 6.0 anyways except for lightning, maybe carnage and arsenal merc.

Only way to make sure is test on a instant hit abilitiy class like deception or concealment or auto attack dummy for many many minutes straight which is tedious to do. If channeling abilities were rounded/ affected they were always so in more minute steps...probably at .01 steps instead of .1 steps.

 

1.3 GCD is not realistic for dps with limited tertiary stats in 6.0 anyways except for lightning, maybe carnage and arsenal merc.

You still take a massive hit in damage with lightning or arsenal because you lose so much crit to get there,

I guess you could stack Augments, but I didn’t bring any kits over to test it out.

Haven't tested on the most recent PTS patch, so more testing may be needed, but as of a patch or two ago, the GCD appeared to still round up to the nearest tenth of a second.

Google sheet for testing

I have 1307 Alacrity on one of my sets and my cast times are 1.39 seconds.

Crit at 3161 which gives 42./13% and 69.41%

Accuracy at 1612 110.1%

3258 gives you 15.55% alacrity but only 1147 crit at 27.2 and 59.75%

Haven't tried to get any closer to the threshold

here are results for gcd casts. would be nice to have this data for channels (diagnostic scan/ lightning strike)

using data from https://docs.google.com/spreadsheets/d/1QDQ-kZ_fo5Em_lZLh1pQRXdcDRnLLphwFZjR0wDP9HQ/edit#gid=1526455495

summary:

https://pasteboard.co/IzZn0PG.png

Two-Sample T-Test and CI: 0, 862

Two-sample T for 0 vs 862

N Mean StDev SE Mean

0 20 1.5465 0.0500 0.011

862 20 1.4988 0.0170 0.0038

Difference = mu (0) - mu (862)

Estimate for difference: 0.0478

95% CI for difference: (0.0233, 0.0722)

T-Test of difference = 0 (vs not =): T-Value = 4.04 P-Value = 0.001 DF = 23

Boxplot of 0, 862

Two-Sample T-Test and CI: 0, 755

Two-sample T for 0 vs 755

N Mean StDev SE Mean

0 20 1.5465 0.0500 0.011

755 21 1.50029 0.00901 0.0020

Difference = mu (0) - mu (755)

Estimate for difference: 0.0463

95% CI for difference: (0.0226, 0.0699)

T-Test of difference = 0 (vs not =): T-Value = 4.08 P-Value = 0.001 DF = 20

Boxplot of 0, 755

Two-Sample T-Test and CI: 0, 1293

Two-sample T for 0 vs 1293

N Mean StDev SE Mean

0 20 1.5465 0.0500 0.011

1293 22 1.4120 0.0366 0.0078

Difference = mu (0) - mu (1293)

Estimate for difference: 0.1346

95% CI for difference: (0.1069, 0.1623)

T-Test of difference = 0 (vs not =): T-Value = 9.88 P-Value = 0.000 DF = 34

Two-Sample T-Test and CI: 0, 1294

Two-sample T for 0 vs 1294

N Mean StDev SE Mean

0 20 1.5465 0.0500 0.011

1294 22 1.4133 0.0341 0.0073

Difference = mu (0) - mu (1294)

Estimate for difference: 0.1333

95% CI for difference: (0.1062, 0.1604)

T-Test of difference = 0 (vs not =): T-Value = 10.00 P-Value = 0.000 DF = 33

Two-sample T for 0 vs 1724

N Mean StDev SE Mean

0 20 1.5465 0.0500 0.011

1724 22 1.4030 0.0213 0.0045

Difference = mu (0) - mu (1724)

Estimate for difference: 0.1435

95% CI for difference: (0.1187, 0.1683)

T-Test of difference = 0 (vs not =): T-Value = 11.90 P-Value = 0.000 DF = 25

Two-sample T for 0 vs 2155

N Mean StDev SE Mean

0 20 1.5465 0.0500 0.011

2155 22 1.4012 0.0222 0.0047

Difference = mu (0) - mu (2155)

Estimate for difference: 0.1453

95% CI for difference: (0.1203, 0.1703)

T-Test of difference = 0 (vs not =): T-Value = 11.97 P-Value = 0.000 DF = 25

Two-sample T for 862 vs 755

N Mean StDev SE Mean

862 20 1.4988 0.0170 0.0038

755 21 1.50029 0.00901 0.0020

Difference = mu (862) - mu (755)

Estimate for difference: -0.00149

95% CI for difference: (-0.01027, 0.00730)

T-Test of difference = 0 (vs not =): T-Value = -0.35 P-Value = 0.732 DF = 28

Two-sample T for 862 vs 1293

N Mean StDev SE Mean

862 20 1.4988 0.0170 0.0038

1293 22 1.4120 0.0366 0.0078

Difference = mu (862) - mu (1293)

Estimate for difference: 0.08685

95% CI for difference: (0.06912, 0.10457)

T-Test of difference = 0 (vs not =): T-Value = 10.01 P-Value = 0.000 DF = 30

Two-sample T for 862 vs 1724

N Mean StDev SE Mean

862 20 1.4988 0.0170 0.0038

1724 22 1.4030 0.0213 0.0045

Difference = mu (862) - mu (1724)

Estimate for difference: 0.09575

95% CI for difference: (0.08378, 0.10773)

T-Test of difference = 0 (vs not =): T-Value = 16.17 P-Value = 0.000 DF = 39

Two-sample T for 862 vs 2155

N Mean StDev SE Mean

862 20 1.4988 0.0170 0.0038

2155 22 1.4012 0.0222 0.0047

Difference = mu (862) - mu (2155)

Estimate for difference: 0.09757

95% CI for difference: (0.08527, 0.10988)

T-Test of difference = 0 (vs not =): T-Value = 16.05 P-Value = 0.000 DF = 38

Two-sample T for 862 vs 3017

N Mean StDev SE Mean

862 20 1.4988 0.0170 0.0038

3017 22 1.3983 0.0139 0.0030

Difference = mu (862) - mu (3017)

Estimate for difference: 0.10048

95% CI for difference: (0.09070, 0.11027)

T-Test of difference = 0 (vs not =): T-Value = 20.82 P-Value = 0.000 DF = 36

Two-sample T for 1293 vs 3017

N Mean StDev SE Mean

1293 22 1.4120 0.0366 0.0078

3017 22 1.3983 0.0139 0.0030

Difference = mu (1293) - mu (3017)

Estimate for difference: 0.01364

95% CI for difference: (-0.00350, 0.03078)

T-Test of difference = 0 (vs not =): T-Value = 1.64 P-Value = 0.114 DF = 26

Two-sample T for 1724 vs 3017

N Mean StDev SE Mean

1724 22 1.4030 0.0213 0.0045

3017 22 1.3983 0.0139 0.0030

Difference = mu (1724) - mu (3017)

Estimate for difference: 0.00473

95% CI for difference: (-0.00625, 0.01571)

T-Test of difference = 0 (vs not =): T-Value = 0.87 P-Value = 0.388 DF = 36

Two-sample T for 2155 vs 3017

N Mean StDev SE Mean

2155 22 1.4012 0.0222 0.0047

3017 22 1.3983 0.0139 0.0030

Difference = mu (2155) - mu (3017)

Estimate for difference: 0.00291

95% CI for difference: (-0.00843, 0.01425)

T-Test of difference = 0 (vs not =): T-Value = 0.52 P-Value = 0.606 DF = 35

Two-sample T for 2155 vs 3448

N Mean StDev SE Mean

2155 22 1.4012 0.0222 0.0047

3448 23 1.3080 0.0270 0.0056

Difference = mu (2155) - mu (3448)

Estimate for difference: 0.09327

95% CI for difference: (0.07843, 0.10811)

T-Test of difference = 0 (vs not =): T-Value = 12.68 P-Value = 0.000 DF = 42

So dipstik if I am reading your tables correctly, every time you compare an alacrity rating that is below and above our known thresholds for the 1.4s GCD (1212) or 1.3s GCD (3207) the p value is 0 indicating that the observation of different APM is unlikely to be the result of random chance. Every time you compare two alacrity ratings that are on the same side of a threshold I see the p-value much higher, suggesting the observed APM differences are much more likely to be the result of random chance.

This suggests to me that rounding is still occurring to two significant digits, at least as far as GCD is concerned.

here are results for gcd casts. would be nice to have this data for channels (diagnostic scan/ lightning strike)

 

using data from https://docs.google.com/spreadsheets/d/1QDQ-kZ_fo5Em_lZLh1pQRXdcDRnLLphwFZjR0wDP9HQ/edit#gid=1526455495

 

summary:

https://pasteboard.co/IzZn0PG.png

 

 

Two-Sample T-Test and CI: 0, 862

 

Two-sample T for 0 vs 862

 

N Mean StDev SE Mean

0 20 1.5465 0.0500 0.011

862 20 1.4988 0.0170 0.0038

 

 

Difference = mu (0) - mu (862)

Estimate for difference: 0.0478

95% CI for difference: (0.0233, 0.0722)

T-Test of difference = 0 (vs not =): T-Value = 4.04 P-Value = 0.001 DF = 23

 

 

Boxplot of 0, 862

 

 

Two-Sample T-Test and CI: 0, 755

 

Two-sample T for 0 vs 755

 

N Mean StDev SE Mean

0 20 1.5465 0.0500 0.011

755 21 1.50029 0.00901 0.0020

 

 

Difference = mu (0) - mu (755)

Estimate for difference: 0.0463

95% CI for difference: (0.0226, 0.0699)

T-Test of difference = 0 (vs not =): T-Value = 4.08 P-Value = 0.001 DF = 20

 

 

Boxplot of 0, 755

 

 

Two-Sample T-Test and CI: 0, 1293

 

Two-sample T for 0 vs 1293

 

N Mean StDev SE Mean

0 20 1.5465 0.0500 0.011

1293 22 1.4120 0.0366 0.0078

 

 

Difference = mu (0) - mu (1293)

Estimate for difference: 0.1346

95% CI for difference: (0.1069, 0.1623)

T-Test of difference = 0 (vs not =): T-Value = 9.88 P-Value = 0.000 DF = 34

 

Two-Sample T-Test and CI: 0, 1294

 

Two-sample T for 0 vs 1294

 

N Mean StDev SE Mean

0 20 1.5465 0.0500 0.011

1294 22 1.4133 0.0341 0.0073

 

 

Difference = mu (0) - mu (1294)

Estimate for difference: 0.1333

95% CI for difference: (0.1062, 0.1604)

T-Test of difference = 0 (vs not =): T-Value = 10.00 P-Value = 0.000 DF = 33

 

Two-sample T for 0 vs 1724

 

N Mean StDev SE Mean

0 20 1.5465 0.0500 0.011

1724 22 1.4030 0.0213 0.0045

 

 

Difference = mu (0) - mu (1724)

Estimate for difference: 0.1435

95% CI for difference: (0.1187, 0.1683)

T-Test of difference = 0 (vs not =): T-Value = 11.90 P-Value = 0.000 DF = 25

 

Two-sample T for 0 vs 2155

 

N Mean StDev SE Mean

0 20 1.5465 0.0500 0.011

2155 22 1.4012 0.0222 0.0047

 

 

Difference = mu (0) - mu (2155)

Estimate for difference: 0.1453

95% CI for difference: (0.1203, 0.1703)

T-Test of difference = 0 (vs not =): T-Value = 11.97 P-Value = 0.000 DF = 25

 

Two-sample T for 862 vs 755

 

N Mean StDev SE Mean

862 20 1.4988 0.0170 0.0038

755 21 1.50029 0.00901 0.0020

 

 

Difference = mu (862) - mu (755)

Estimate for difference: -0.00149

95% CI for difference: (-0.01027, 0.00730)

T-Test of difference = 0 (vs not =): T-Value = -0.35 P-Value = 0.732 DF = 28

 

Two-sample T for 862 vs 1293

 

N Mean StDev SE Mean

862 20 1.4988 0.0170 0.0038

1293 22 1.4120 0.0366 0.0078

 

 

Difference = mu (862) - mu (1293)

Estimate for difference: 0.08685

95% CI for difference: (0.06912, 0.10457)

T-Test of difference = 0 (vs not =): T-Value = 10.01 P-Value = 0.000 DF = 30

 

Two-sample T for 862 vs 1724

 

N Mean StDev SE Mean

862 20 1.4988 0.0170 0.0038

1724 22 1.4030 0.0213 0.0045

 

 

Difference = mu (862) - mu (1724)

Estimate for difference: 0.09575

95% CI for difference: (0.08378, 0.10773)

T-Test of difference = 0 (vs not =): T-Value = 16.17 P-Value = 0.000 DF = 39

 

Two-sample T for 862 vs 2155

 

N Mean StDev SE Mean

862 20 1.4988 0.0170 0.0038

2155 22 1.4012 0.0222 0.0047

 

 

Difference = mu (862) - mu (2155)

Estimate for difference: 0.09757

95% CI for difference: (0.08527, 0.10988)

T-Test of difference = 0 (vs not =): T-Value = 16.05 P-Value = 0.000 DF = 38

 

Two-sample T for 862 vs 3017

 

N Mean StDev SE Mean

862 20 1.4988 0.0170 0.0038

3017 22 1.3983 0.0139 0.0030

 

 

Difference = mu (862) - mu (3017)

Estimate for difference: 0.10048

95% CI for difference: (0.09070, 0.11027)

T-Test of difference = 0 (vs not =): T-Value = 20.82 P-Value = 0.000 DF = 36

 

 

Two-sample T for 1293 vs 3017

 

N Mean StDev SE Mean

1293 22 1.4120 0.0366 0.0078

3017 22 1.3983 0.0139 0.0030

 

 

Difference = mu (1293) - mu (3017)

Estimate for difference: 0.01364

95% CI for difference: (-0.00350, 0.03078)

T-Test of difference = 0 (vs not =): T-Value = 1.64 P-Value = 0.114 DF = 26

 

Two-sample T for 1724 vs 3017

 

N Mean StDev SE Mean

1724 22 1.4030 0.0213 0.0045

3017 22 1.3983 0.0139 0.0030

 

 

Difference = mu (1724) - mu (3017)

Estimate for difference: 0.00473

95% CI for difference: (-0.00625, 0.01571)

T-Test of difference = 0 (vs not =): T-Value = 0.87 P-Value = 0.388 DF = 36

 

Two-sample T for 2155 vs 3017

 

N Mean StDev SE Mean

2155 22 1.4012 0.0222 0.0047

3017 22 1.3983 0.0139 0.0030

 

 

Difference = mu (2155) - mu (3017)

Estimate for difference: 0.00291

95% CI for difference: (-0.00843, 0.01425)

T-Test of difference = 0 (vs not =): T-Value = 0.52 P-Value = 0.606 DF = 35

 

Two-sample T for 2155 vs 3448

 

N Mean StDev SE Mean

2155 22 1.4012 0.0222 0.0047

3448 23 1.3080 0.0270 0.0056

 

 

Difference = mu (2155) - mu (3448)

Estimate for difference: 0.09327

95% CI for difference: (0.07843, 0.10811)

T-Test of difference = 0 (vs not =): T-Value = 12.68 P-Value = 0.000 DF = 42

I am sure this is a lot of important information but sadly it looks like an alien life form wrote it out to me. That or maybe Einstein, lol. I wish mathematical analytics was my strong point.

I am sure this is a lot of important information but sadly it looks like an alien life form wrote it out to me. That or maybe Einstein, lol. I wish mathematical analytics was my strong point.

P-values are one way to compare two sets of data for differences. You want to use different types of statistical tests depending on the nature of the data and the variable being compared. p-values indicate the likelihood that the results or outcome you are observing are due to random chance, with lower p-values being less likely the observed results are due to random chance. A p-value near zero means it’s highly unlikely the result is due to random chance.

In this case, dipstik tested several sets of Abilities per minute just spamming a basic attack, at different alacrity ratings. The goal being to prove whether or not GCD rounding to tenths or hundredths of a second was occurring. Based on dipstik’s results, the differences between the test runs of basic attack spamming at different alacrity ratings is only significant when the tested alacrity ratings are on different sides of an AR breakpoint. In other words the results pretty much confirm that the GCD is still rounded to tenths of a second.

EDIT: this is proven by the low-breakpoints dipstik chose. An Alacrity Rating of 755, under the new formulae, translates into an Alacrity Percentage of 4.67%. An Alacrity Rating of 862 translates into an Alacrity Percentage of 5.27%. These percentages, if the GCD was rounding to hundredths of a second, would mean a GCD of 1.44 and 1.43 seconds respectively. Dipstik's results show no statistically significant difference between APM at either of those Alacrity Rating levels. Its also followed up in the high breakpoints dipstik chose. The comparisons between an Alacrity Rating of 1293, 1724, and 3017, all between the 1.4 and 1.3s GCD, show no statistically significant difference.

P-values are one way to compare two sets of data for differences. You want to use different types of statistical tests depending on the nature of the data and the variable being compared. p-values indicate the likelihood that the results or outcome you are observing are due to random chance, with lower p-values being less likely the observed results are due to random chance. A p-value near zero means it’s highly unlikely the result is due to random chance.

In this case, dipstik tested several sets of Abilities per minute just spamming a basic attack, at different alacrity ratings. The goal being to prove whether or not GCD rounding to tenths or hundredths of a second was occurring. Based on dipstik’s results, the differences between the test runs of basic attack spamming at different alacrity ratings is only significant when the tested alacrity ratings are on different sides of an AR breakpoint. In other words the results pretty much confirm that the GCD is still rounded to tenths of a second.

 

EDIT: this is proven by the low-breakpoints dipstik chose. An Alacrity Rating of 755, under the new formulae, translates into an Alacrity Percentage of 4.67%. An Alacrity Rating of 862 translates into an Alacrity Percentage of 5.27%. These percentages, if the GCD was rounding to hundredths of a second, would mean a GCD of 1.44 and 1.43 seconds respectively. Dipstik's results show no statistically significant difference between APM at either of those Alacrity Rating levels. Its also followed up in the high breakpoints dipstik chose. The comparisons between an Alacrity Rating of 1293, 1724, and 3017, all between the 1.4 and 1.3s GCD, show no statistically significant difference.

good show ol chap

to add: the summary table png is a table of the 95% confidence intervals of difference between means between the row and column headers. for example, for row (left side) 0 column (top) 755 we have an interval of 0.0226 to 0.0699. That means there is a 95% chance the the difference between the gcd times if you have 0 alacrity and 755 alacrity will be between 0.0226 and 0.0699 seconds. For row 1294 and column 3017 we have an interval from -0.006 and 0.016 seconds. This means that there is a 95% chance that the difference is less than 0.02 seconds (essentially zero).

good show ol chap

 

to add: the summary table png is a table of the 95% confidence intervals of difference between means between the row and column headers. for example, for row (left side) 0 column (top) 755 we have an interval of 0.0226 to 0.0699. That means there is a 95% chance the the difference between the gcd times if you have 0 alacrity and 755 alacrity will be between 0.0226 and 0.0699 seconds. For row 1294 and column 3017 we have an interval from -0.006 and 0.016 seconds. This means that there is a 95% chance that the difference is less than 0.02 seconds (essentially zero).

If I understand correctly between what you and Phal have said, 1.3 lvls will make little to no difference anymore and we will be making 1.5 to 1.4 builds if alacrity is rounding down?

There are pretty powerful set bonuses in the game now tied to certain longish cooldown abilities like entrench and mental alacrity which you do not want to delay or elongate the cd on those - you want those to be as short as possible actually without making your crit chance plumet bellow like 35-38%. just a 5 sec difference on such a cooldown makes a huge difference in dps. Check the set boni damage boosts based on your class if your wearing such a set, because most of your dps increase comes in that window when something like entrench or alacrity etc is active. I believe many of the classes not just those two have such a set now. Activating such a cd (so the ability refreshed faster) while under something like an alacrity proc relic in scaled down content will be a petty standard trick I think.

On pure burst no dot damage specs yeah the baseline 1.4gcd / 7.5% alac is fine, rest crit usually. On dot classes I hate going under 10% alac because dots start to "tick" slower and I do think there is at that point a noticeable dps decrease. Maybe in Pvp where you prioritize bigger hits over sustain you can drop it... but there again some neat cooldowns on longer (1 min+) cd abilities will be noticeably slower at 7.5% alac vs 10%.

If I understand correctly between what you and Phal have said, 1.3 lvls will make little to no difference anymore and we will be making 1.5 to 1.4 builds if alacrity is rounding down?

No. The breakpoints still exist, if you have enough alacrity rating you could run with a 1.3s GCD. It will be significantly different APM than at 1.4s GCD, i.e. it works just fine. The results were only to prove or disprove if GCD was being rounded to tenths or hundredths of a second. It’s rounding just like LIVE, up to tenths of a second.

No. The breakpoints still exist, if you have enough alacrity rating you could run with a 1.3s GCD. It will be significantly different APM than at 1.4s GCD, i.e. it works just fine. The results were only to prove or disprove if GCD was being rounded to tenths or hundredths of a second. It’s rounding just like LIVE, up to tenths of a second.

Ok, cool. Just checking.

P-values are one way to compare two sets of data for differences. You want to use different types of statistical tests depending on the nature of the data and the variable being compared. p-values indicate the likelihood that the results or outcome you are observing are due to random chance, with lower p-values being less likely the observed results are due to random chance. A p-value near zero means it’s highly unlikely the result is due to random chance.

In this case, dipstik tested several sets of Abilities per minute just spamming a basic attack, at different alacrity ratings. The goal being to prove whether or not GCD rounding to tenths or hundredths of a second was occurring. Based on dipstik’s results, the differences between the test runs of basic attack spamming at different alacrity ratings is only significant when the tested alacrity ratings are on different sides of an AR breakpoint. In other words the results pretty much confirm that the GCD is still rounded to tenths of a second.

 

EDIT: this is proven by the low-breakpoints dipstik chose. An Alacrity Rating of 755, under the new formulae, translates into an Alacrity Percentage of 4.67%. An Alacrity Rating of 862 translates into an Alacrity Percentage of 5.27%. These percentages, if the GCD was rounding to hundredths of a second, would mean a GCD of 1.44 and 1.43 seconds respectively. Dipstik's results show no statistically significant difference between APM at either of those Alacrity Rating levels. Its also followed up in the high breakpoints dipstik chose. The comparisons between an Alacrity Rating of 1293, 1724, and 3017, all between the 1.4 and 1.3s GCD, show no statistically significant difference.

Very nice translation, I appreciate your work here lol.