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8161  Other / Beginners & Help / Re: [Guide] Factors to consider before joining paid signature campaigns. on: March 06, 2019, 01:04:41 PM
Relates to postcount, I remembered that I saw (maybe in Meta) months ago that forum staff states that there are two types of signature bounties:
(1) Pay per week.
(2) Pay per post.
For the second type, there are forum rules that managers of those bounties should restrict total amount of posts per week to be counted as eligible and can get paid by campaigns.
It is mainly to prevent spamming endemic from participants.

I tried to search where it mentioned, but still not found it for now.
Appreciate help from someone who can give me link.
Important point, maybe you can mention here to check the signature campaign rules if local boards are accepted.
8162  Alternate cryptocurrencies / Announcements (Altcoins) / Re: [ANN] Ethereum: Welcome to the Beginning on: March 06, 2019, 12:56:44 PM
That one does not relate to Ethereum.
Why did you spam that project here, fella?
The link likely leads to something vague. Huh
Does it a phishing site?
8163  Other / Meta / Re: How many banned users have you merited? on: March 06, 2019, 12:48:31 PM
Nice findings, LoyceV.
Around 11.3% of at-least-one-merit-earned users got banned actually not a high figure.
In total, 26864 users received at least 1 Merit until last Friday's merit data dump, and 3024 of those (11.26%) have been banned. It's probably a bit higher, my list of banned users is incomplete.
As I raised a hypothesis earlier, it might be better if you can scrap data and get several statistics:
(1) How many of them got their first merit before the demotion of Junior Members in September last year?
(2) How many of those re-promoted to Junior Members got banned after that?
(3) How long it take from the days they got their first merits and promoted again to the days their accounts got banned?
For the third question, it might be more specific if you analyse only demoted Junior members that got promoted again and banned later.
Of course, we need to look at data-evidence-based statistics.
For analysis, before digging deeply, I think you should take a quick analysis on their promoted days.
If most of newbies promoted in September last year, there is no reason to dig deeper.
I believe most of them promoted and got bans in September last year
Grin

Additionally, I still don't really get what you imply in those two figures.
You should make a note in the OP to state what they mean.
    1. 45 (43.26%)
8164  Other / Meta / Re: Merit & new rank requirements on: March 06, 2019, 09:37:38 AM
JeromeTash,
You can get it there.
https://bitcointalk.org/index.php?topic=2818350.msg48183121#msg48183121
coinlocket$ dropped the table, so it is lack of colums' headers.

I made a topic to trace the change of merit circulations over last 7 weeks after the Default Trust Change occured on 9th Jan. 2019.
https://bitcointalk.org/index.php?topic=5095156.msg50040066#msg50040066
After 7 weeks, both median and mean of intraday-merits between before and after period are almost the same (less than 4.2% differences)
8165  Other / Meta / Re: Merit & new rank requirements on: March 06, 2019, 08:50:09 AM
Agreed at this point.
I think it is just that everyone has got used to it now it has been in place so long.
I even did not know about the Activity requirements implementation. I simply thought it was here since the implementation of forum rank system.
Quote
The same thing happened when Activity was first introduced.
For changes,
I envisioned that some day, might be years from now, the forum will see new demotion waves.
Admin might give a long period of self-made users to promote, after that demotions will be made aim at high-rank users that won't earn any merit over years.
Quote
There were lots of threads and complaints about it until everyone forgot was it was like before the change.
8166  Other / Meta / Re: Merit & new rank requirements on: March 06, 2019, 08:38:53 AM
Sooner or later, they will come back, and dump their shitty complaints.
Maybe... when cryptocurrencies shoot high and the I-wanna-get-rich-fast people get back to the forums, many of them realised they are stuck in low level accounts and others just being new here, they might come back here to bash the system or beg for merits.
It might become a massive issues for those ones if new demotions aim at higher ranks implemented in the future by theymos.
It will be a very interesting, very hot topic if high-rank demotions occur.
Quote
Unfortunately, we're still getting spams and shitposts from multi-account holders who were given free merits to all their old accounts.
Absolutely helpful merit system to control and wipe out spambies.
Quote
But I imagine that the situation would be much worse if we didn't have the merit system at all.
8167  Other / Meta / Re: Stake your Bitcoin address here on: March 06, 2019, 08:34:16 AM
Staking as well. Please help me by verify this message.
Code:
-----BEGIN BITCOIN SIGNED MESSAGE-----
This is Hatuferu of bitcointalk and today is March 6, 2019

1M43N5b7d8AAznYgMuJU1wBwA6NzeMP5E6
-----BEGIN SIGNATURE-----
IIoUtTkVoH7Mw4aQtyuGzsxOn8SbPzJD++sSGPsJnegzVcKq/RJGWLLeFxhxyKHEu/ZLO6UgC5r+NR08EOAxsDg=
-----END BITCOIN SIGNED MESSAGE-----
I quoted, verified, and archived it for you to help you secure your account better.
8168  Other / Meta / Re: ⭐ Forum chronicle - UP Rank List - Congratulations! (BPIP Merit stat, Trust) ⭐ on: March 06, 2019, 07:39:48 AM
Congratulations Heisenberg_Hunter, promoted to a Senior Member!

RankUser nameBPIP profileBPIP Merit RECEIVEDBPIP Merit SENDTrustStatusPersonal comment about yourself
Heisenberg_HunterHeisenberg_HunterHeisenberg_HunterHeisenberg_Hunter0: -0 / +0activeInformation expected


8169  Other / Meta / Re: Merit & new rank requirements on: March 06, 2019, 07:32:59 AM
As promised, I keep updating the very inactive topic in Meta.
Once upon a time, it was the hottest place in Meta, so we should keep it updated.
Sometime later, it will return to be the hottest one again, I believe.
Grin

Please get them there if you are interested:
Abstract of the latest week update
Intra-week update
Intra-day update
8170  Other / Meta / Re: Time Series Analysis on Distributed Merits in the forum (daily, weekly, monthly) on: March 06, 2019, 07:16:36 AM
ABSTRACT


Intra-day merits:
Notes:
- The part of the asbstract describes figures of intraday merits over the period from 19/2/2018 to 25/02/2019 (truncated dataset);
- Days from 24/1/2018 to 25/2/2018 truncated due to highly potential outliers; and days after 25/02/2019 truncated as well due to incomplete week (the nineth week of 2019, 2019w9);
- Statistics presented in the post are for truncated dataset.

(1) Potential outliers are days that have intraday total merits beyond 147 or 1139;
(2) Median of intraday merits over the period is 618.5 ~ 619;
(3) 50% of observed days have their intra-day merits range from 519 to 767 (the interquartile range);
(4) Friday [in GTM time] is the day over weeks has lowest intraday merits in terms of both median and mean, at 554, and 6164, respectively.
(5) Monday [in GMT time] is the day over weeks has highest intraday merits in terms of both median and mean, at 666, and 745, respectively.
(6) There are 22 potential outliers in total, and there is only one potential outlier day happened in early weeks of 2019, on 09 Jan. 2019, at 1161.
(7) Minimum and maximum of intraday merits (full dataset) are 312 and 13018, on 11/2/2019 and 24/1/2018 respectively.


Intra-week merits:
Notes:
The part of the abstract use full dataset, only dropped last two days due to incomple week (2019w9).

(1)   The median of intra-week merits is 4474;
(2)   50% of observed weeks (57 weeeks in total), have total merits in the range from 3818 to 5487 (the interquaritle range of intra-week merits);
(3)   Minimum and maximum of intraweek merits are 3065 and 30949, in 2018w35, and 2018w4, respectively;
(4)   Six potential outliers [beyond 1315 or 7991], all of them occurred in the year 2018.
8171  Other / Meta / Re: Time Series Analysis on Distributed Merits in the forum (daily, weekly, monthly) on: March 06, 2019, 07:12:05 AM
Update on intra-week merits (from 24/1/2018 to 25/2/2019)

Converted dataset:
Code:
. list merit week

     +-----------------+
     | merit      week |
     |-----------------|
  1. | 30949    2018w4 |
  2. | 19958    2018w5 |
  3. | 13304    2018w6 |
  4. | 11722    2018w7 |
  5. |  8758    2018w8 |
     |-----------------|
  6. |  8806    2018w9 |
  7. |  7253   2018w10 |
  8. |  7309   2018w11 |
  9. |  6941   2018w12 |
 10. |  6707   2018w13 |
     |-----------------|
 11. |  6415   2018w14 |
 12. |  5487   2018w15 |
 13. |  4631   2018w16 |
 14. |  4585   2018w17 |
 15. |  4953   2018w18 |
     |-----------------|
 16. |  4753   2018w19 |
 17. |  4346   2018w20 |
 18. |  3854   2018w21 |
 19. |  4183   2018w22 |
 20. |  4527   2018w23 |
     |-----------------|
 21. |  3818   2018w24 |
 22. |  4921   2018w25 |
 23. |  4457   2018w26 |
 24. |  4253   2018w27 |
 25. |  4239   2018w28 |
     |-----------------|
 26. |  4159   2018w29 |
 27. |  3652   2018w30 |
 28. |  3798   2018w31 |
 29. |  3994   2018w32 |
 30. |  3618   2018w33 |
     |-----------------|
 31. |  3789   2018w34 |
 32. |  3065   2018w35 |
 33. |  3574   2018w36 |
 34. |  5630   2018w37 |
 35. |  7825   2018w38 |
     |-----------------|
 36. |  4388   2018w39 |
 37. |  4271   2018w40 |
 38. |  3800   2018w41 |
 39. |  4821   2018w42 |
 40. |  3945   2018w43 |
     |-----------------|
 41. |  3339   2018w44 |
 42. |  4513   2018w45 |
 43. |  3722   2018w46 |
 44. |  4558   2018w47 |
 45. |  3750   2018w48 |
     |-----------------|
 46. |  3560   2018w49 |
 47. |  3782   2018w50 |
 48. |  3753   2018w51 |
 49. |  3278   2018w52 |
 50. |  4793    2019w1 |
     |-----------------|
 51. |  6624    2019w2 |
 52. |  5306    2019w3 |
 53. |  4659    2019w4 |
 54. |  4474    2019w5 |
 55. |  4318    2019w6 |
     |-----------------|
 56. |  4207    2019w7 |
 57. |  4507    2019w8 |
     +-----------------+

Time series plot

Basic statistics:
- 50% of observed weeks have total intra-week merits above 4474, whilst the rest 50% of them have total intra-week merits below 4474. 4474 is the median.
- 50% of observed weeks have total intra-week merits fluctuated in the range from 3818 to 5487 (the interquartile range, from p25 to p75, in raw statistics below).
- Min - max: 3065 - 30949.

Code:
. tabstat merit, s(n mean sd p50 p25 p75 min max)

    variable |         N      mean        sd       p50       p25       p75       min       max
-------------+--------------------------------------------------------------------------------
       merit |        57   5764.93  4384.694      4474      3818      5487      3065     30949
----------------------------------------------------------------------------------------------
Potential outliers:
Code:
. di 5487-3818
1669

. di 1669*1.5
2503.5

. di 5487+2503.5
7990.5

. di 3818-2503.5
1314.5
It means that potential outliers are weeks that have intra-week merits beyond 1314.5 or 7990.5
How many weeks are potential outliers?
Code:
. count if (merit >= 7990.5 | merit < 1314.5) & merit != .
  6
6 weeks are outliers, in total.
List of those six weeks:
Code:
. list merit week if merit >=7990.5 | merit <=1314.5

     +----------------+
     | merit     week |
     |----------------|
  1. | 30949   2018w4 |
  2. | 19958   2018w5 |
  3. | 13304   2018w6 |
  4. | 11722   2018w7 |
  5. |  8758   2018w8 |
     |----------------|
  6. |  8806   2018w9 |
     +----------------+
All of them occured in the year 2018.  Grin
8172  Other / Meta / Re: Time Series Analysis on Distributed Merits in the forum (daily, weekly, monthly) on: March 06, 2019, 07:05:08 AM
List of the top 50-highest day in terms of intra-day merits:
Code:
. list merit id date dofw day month2 year week month

     +-------------------------------------------------------------------------------+
     | merit    id        date        dofw   day   month2   year      week     month |
     |-------------------------------------------------------------------------------|
  1. | 13018     1   24jan2018   Wednesday    24        1   2018    2018w4    2018m1 |
  2. |  6761     2   25jan2018    Thursday    25        1   2018    2018w4    2018m1 |
  3. |  4493     3   26jan2018      Friday    26        1   2018    2018w4    2018m1 |
  4. |  4192     7   30jan2018     Tuesday    30        1   2018    2018w5    2018m1 |
  5. |  3799     6   29jan2018      Monday    29        1   2018    2018w5    2018m1 |
     |-------------------------------------------------------------------------------|
  6. |  3489     4   27jan2018    Saturday    27        1   2018    2018w4    2018m1 |
  7. |  3188     5   28jan2018      Sunday    28        1   2018    2018w4    2018m1 |
  8. |  2820     8   31jan2018   Wednesday    31        1   2018    2018w5    2018m1 |
  9. |  2568    10   02feb2018      Friday     2        2   2018    2018w5    2018m2 |
 10. |  2545     9   01feb2018    Thursday     1        2   2018    2018w5    2018m2 |
     |-------------------------------------------------------------------------------|
 11. |  2513    22   14feb2018   Wednesday    14        2   2018    2018w7    2018m2 |
 12. |  2463   236   16sep2018      Sunday    16        9   2018   2018w37    2018m9 |
 13. |  2308    14   06feb2018     Tuesday     6        2   2018    2018w6    2018m2 |
 14. |  2167    12   04feb2018      Sunday     4        2   2018    2018w5    2018m2 |
 15. |  2141    15   07feb2018   Wednesday     7        2   2018    2018w6    2018m2 |
     |-------------------------------------------------------------------------------|
 16. |  2141    16   08feb2018    Thursday     8        2   2018    2018w6    2018m2 |
 17. |  2077    13   05feb2018      Monday     5        2   2018    2018w6    2018m2 |
 18. |  1991    23   15feb2018    Thursday    15        2   2018    2018w7    2018m2 |
 19. |  1867    11   03feb2018    Saturday     3        2   2018    2018w5    2018m2 |
 20. |  1862   237   17sep2018      Monday    17        9   2018   2018w38    2018m9 |
     |-------------------------------------------------------------------------------|
 21. |  1747    18   10feb2018    Saturday    10        2   2018    2018w6    2018m2 |
 22. |  1696    38   02mar2018      Friday     2        3   2018    2018w9    2018m3 |
 23. |  1608    25   17feb2018    Saturday    17        2   2018    2018w7    2018m2 |
 24. |  1579    21   13feb2018     Tuesday    13        2   2018    2018w7    2018m2 |
 25. |  1448    17   09feb2018      Friday     9        2   2018    2018w6    2018m2 |
     |-------------------------------------------------------------------------------|
 26. |  1442    19   11feb2018      Sunday    11        2   2018    2018w6    2018m2 |
 27. |  1411    24   16feb2018      Friday    16        2   2018    2018w7    2018m2 |
 28. |  1409    32   24feb2018    Saturday    24        2   2018    2018w8    2018m2 |
 29. |  1403    27   19feb2018      Monday    19        2   2018    2018w8    2018m2 |
 30. |  1382    34   26feb2018      Monday    26        2   2018    2018w9    2018m2 |
     |-------------------------------------------------------------------------------|
 31. |  1354    48   12mar2018      Monday    12        3   2018   2018w11    2018m3 |
 32. |  1333    37   01mar2018    Thursday     1        3   2018    2018w9    2018m3 |
 33. |  1331    20   12feb2018      Monday    12        2   2018    2018w7    2018m2 |
 34. |  1326    35   27feb2018     Tuesday    27        2   2018    2018w9    2018m2 |
 35. |  1322    56   20mar2018     Tuesday    20        3   2018   2018w12    2018m3 |
     |-------------------------------------------------------------------------------|
 36. |  1294   238   18sep2018     Tuesday    18        9   2018   2018w38    2018m9 |
 37. |  1289    26   18feb2018      Sunday    18        2   2018    2018w7    2018m2 |
 38. |  1279    30   22feb2018    Thursday    22        2   2018    2018w8    2018m2 |
 39. |  1268   239   19sep2018   Wednesday    19        9   2018   2018w38    2018m9 |
 40. |  1266    29   21feb2018   Wednesday    21        2   2018    2018w8    2018m2 |
     |-------------------------------------------------------------------------------|
 41. |  1245    41   05mar2018      Monday     5        3   2018   2018w10    2018m3 |
 42. |  1233    68   01apr2018      Sunday     1        4   2018   2018w13    2018m4 |
 43. |  1227    57   21mar2018   Wednesday    21        3   2018   2018w12    2018m3 |
 44. |  1186    33   25feb2018      Sunday    25        2   2018    2018w8    2018m2 |
 45. |  1169    28   20feb2018     Tuesday    20        2   2018    2018w8    2018m2 |
     |-------------------------------------------------------------------------------|
 46. |  1161   351   09jan2019   Wednesday     9        1   2019    2019w2    2019m1 |
 47. |  1159    50   14mar2018   Wednesday    14        3   2018   2018w11    2018m3 |
 48. |  1146    69   02apr2018      Monday     2        4   2018   2018w14    2018m4 |
 49. |  1138   153   25jun2018      Monday    25        6   2018   2018w26    2018m6 |
 50. |  1130    51   15mar2018    Thursday    15        3   2018   2018w11    2018m3 |
     |-------------------------------------------------------------------------------|

List of the top 50-lowest days in terms of intra-day merits:
Code:
. list merit id date dofw day month2 year week month

     +-------------------------------------------------------------------------------+
     | merit    id        date        dofw   day   month2   year      week     month |
     |-------------------------------------------------------------------------------|
  1. |   312   335   24dec2018      Monday    24       12   2018   2018w52   2018m12 |
  2. |   316   333   22dec2018    Saturday    22       12   2018   2018w51   2018m12 |
  3. |   325   340   29dec2018    Saturday    29       12   2018   2018w52   2018m12 |
  4. |   347   338   27dec2018    Thursday    27       12   2018   2018w52   2018m12 |
  5. |   347   298   17nov2018    Saturday    17       11   2018   2018w46   2018m11 |
     |-------------------------------------------------------------------------------|
  6. |   348   304   23nov2018      Friday    23       11   2018   2018w47   2018m11 |
  7. |   370   122   25may2018      Friday    25        5   2018   2018w21    2018m5 |
  8. |   376   191   02aug2018    Thursday     2        8   2018   2018w31    2018m8 |
  9. |   376   342   31dec2018      Monday    31       12   2018   2018w52   2018m12 |
 10. |   377   326   15dec2018    Saturday    15       12   2018   2018w50   2018m12 |
     |-------------------------------------------------------------------------------|
 11. |   379   220   31aug2018      Friday    31        8   2018   2018w35    2018m8 |
 12. |   383   217   28aug2018     Tuesday    28        8   2018   2018w35    2018m8 |
 13. |   385   214   25aug2018    Saturday    25        8   2018   2018w34    2018m8 |
 14. |   386   339   28dec2018      Friday    28       12   2018   2018w52   2018m12 |
 15. |   389   341   30dec2018      Sunday    30       12   2018   2018w52   2018m12 |
     |-------------------------------------------------------------------------------|
 16. |   394   345   03jan2019    Thursday     3        1   2019    2019w1    2019m1 |
 17. |   395   228   08sep2018    Saturday     8        9   2018   2018w36    2018m9 |
 18. |   397   320   09dec2018      Sunday     9       12   2018   2018w49   2018m12 |
 19. |   399   262   12oct2018      Friday    12       10   2018   2018w41   2018m10 |
 20. |   402   329   18dec2018     Tuesday    18       12   2018   2018w51   2018m12 |
     |-------------------------------------------------------------------------------|
 21. |   405   287   06nov2018     Tuesday     6       11   2018   2018w45   2018m11 |
 22. |   412   222   02sep2018      Sunday     2        9   2018   2018w35    2018m9 |
 23. |   415   278   28oct2018      Sunday    28       10   2018   2018w43   2018m10 |
 24. |   415   109   12may2018    Saturday    12        5   2018   2018w19    2018m5 |
 25. |   418   186   28jul2018    Saturday    28        7   2018   2018w30    2018m7 |
     |-------------------------------------------------------------------------------|
 26. |   420   187   29jul2018      Sunday    29        7   2018   2018w30    2018m7 |
 27. |   421   192   03aug2018      Friday     3        8   2018   2018w31    2018m8 |
 28. |   422   140   12jun2018     Tuesday    12        6   2018   2018w24    2018m6 |
 29. |   424   276   26oct2018      Friday    26       10   2018   2018w43   2018m10 |
 30. |   424   313   02dec2018      Sunday     2       12   2018   2018w48   2018m12 |
     |-------------------------------------------------------------------------------|
 31. |   426   277   27oct2018    Saturday    27       10   2018   2018w43   2018m10 |
 32. |   430   264   14oct2018      Sunday    14       10   2018   2018w41   2018m10 |
 33. |   430   284   03nov2018    Saturday     3       11   2018   2018w44   2018m11 |
 34. |   432   208   19aug2018      Sunday    19        8   2018   2018w33    2018m8 |
 35. |   432   221   01sep2018    Saturday     1        9   2018   2018w35    2018m9 |
     |-------------------------------------------------------------------------------|
 36. |   433   282   01nov2018    Thursday     1       11   2018   2018w44   2018m11 |
 37. |   435   190   01aug2018   Wednesday     1        8   2018   2018w31    2018m8 |
 38. |   435   154   26jun2018     Tuesday    26        6   2018   2018w26    2018m6 |
 39. |   444   182   24jul2018     Tuesday    24        7   2018   2018w30    2018m7 |
 40. |   445   143   15jun2018      Friday    15        6   2018   2018w24    2018m6 |
     |-------------------------------------------------------------------------------|
 41. |   450   373   31jan2019    Thursday    31        1   2019    2019w5    2019m1 |
 42. |   451   206   17aug2018      Friday    17        8   2018   2018w33    2018m8 |
 43. |   454   283   02nov2018      Friday     2       11   2018   2018w44   2018m11 |
 44. |   455   229   09sep2018      Sunday     9        9   2018   2018w36    2018m9 |
 45. |   455   167   09jul2018      Monday     9        7   2018   2018w28    2018m7 |
     |-------------------------------------------------------------------------------|
 46. |   457   216   27aug2018      Monday    27        8   2018   2018w35    2018m8 |
 47. |   458   324   13dec2018    Thursday    13       12   2018   2018w50   2018m12 |
 48. |   458   227   07sep2018      Friday     7        9   2018   2018w36    2018m9 |
 49. |   460   263   13oct2018    Saturday    13       10   2018   2018w41   2018m10 |
 50. |   461   130   02jun2018    Saturday     2        6   2018   2018w22    2018m6 |
     |-------------------------------------------------------------------------------|

During the period from 24/1/2018 to 25/2/2019, the minimum and maximum of intra-day merits are 312 and 13018 , on 24/12/2018 and 24/1/2018, respectively.
8173  Other / Meta / Re: Time Series Analysis on Distributed Merits in the forum (daily, weekly, monthly) on: March 06, 2019, 06:53:55 AM
Medians and means of intra-day merits over days of weeks.

- In median, the highest days are Monday, Wednesday, and Thursday at 666, 654, and 636, respectively; whislt the lowest days are Friday, Sunday, and Saturday at 554, 607, and 614, respectively.
- In means, the highest days are Monday, Wednesday, and both Sunday, Tuesday at 745, 714, and 694, respectively; whilst the lowest days are Friday, Saturday, and Thursday at 614, 627, and 667, respectively.
- In both medians and means, Monday is the highest day, whilst the lowest day is Friday.

Calendar day is in GMT time.
To take away all doubt: the first Merit was this one:
Code:
1516831941	1	2818066.msg28853325	35	877396
Use EpochConverter to convert 1516831941 (Unix Time) to GMT: Wednesday 24 January 2018 22:12:21.

Basic statistics:
Code:
. tabstat merit, s(n mean sd p50 p25 p75 min max) format(%9.1f) by(dofw)

Summary for variables: merit
     by categories of: dofw

     dofw |         N      mean        sd       p50       p25       p75       min       max
----------+--------------------------------------------------------------------------------
   Sunday |      53.0     693.7     327.2     607.0     486.0     796.0     389.0    2463.0
   Monday |      54.0     744.1     295.2     666.0     562.0     822.0     312.0    1862.0
  Tuesday |      53.0     694.0     226.3     626.0     580.0     767.0     383.0    1326.0
Wednesday |      53.0     714.0     217.5     654.0     559.0     759.0     435.0    1268.0
 Thursday |      53.0     667.0     220.9     636.0     509.0     764.0     347.0    1333.0
   Friday |      53.0     613.7     225.8     554.0     479.0     682.0     348.0    1696.0
 Saturday |      53.0     626.8     216.5     614.0     463.0     688.0     316.0    1409.0
----------+--------------------------------------------------------------------------------
    Total |     372.0     679.2     252.4     618.5     518.5     766.5     312.0    2463.0
-------------------------------------------------------------------------------------------

Box plots
Outliers displayed as red circles.

Outliers non-displayed.
8174  Other / Meta / Re: DefaultTrust changes on: March 06, 2019, 06:35:50 AM
Update for 7 weeks after the implementation of Default Trust Change:
If nothing new happen next days/ weeks, the delayed effects of Default Trust Change on merit circulations tailed off over the last 7 weeks.
If nothing strange occurs, I will stop doing analysis in the topic when the ten weeks later passed (3 more weeks).

Colors:
- Red: Decrease
- Green: Increase.

Two week later:
Median: + 37.1
Mean: + 24.2

Three weeks later:
Median: + 15.9
Mean: + 15.5

Four weeks later:
Median: + 15.6
Mean: + 11.1

Five weeks later:
Median: + 6.2
Mean: + 6.4

Six weeks later:
Median: + 4.2
Mean: + 3.5

Seven weeks later:
Median: + 4.2
Mean: + 2.7

More details such as methods of the calculation, can be found there, Tracking the difference of merit circulations with Default Trust Changes
8175  Other / Meta / Re: Tracking the difference of merit circulations with Default Trust Changes on: March 06, 2019, 06:35:25 AM
7 weeks later update:
Median: + 4.2 %
Mean: + 2.7 %



ABSTRACT

(1) Both median and mean of six-week-later period are higher then the before period, with cut-off day is 09/01/2019, at 4.2% and 2.7%, respectively.
(2) 50 percent of days in the seven weeks later period have intraday merits in the range from 595 to 736 (the interquartile range), whilst the figures of the before period are 511 to 767.
(3) The median of seven-week-later period is almost the same as the figure of the six-week-later period, at 643 and 642.5, respectively.





Box plots:
Outliers displayed with red circles

Outliers, non-displayed

Basic statistics:
Code:
. tabstat before090119 wkslater_2 wkslater_3 wkslater_4 wkslater_5 wkslater_6 wkslater_7, s(n mean sd p50 p25 p75 min max) format(%9.1f) c(s)

    variable |         N      mean        sd       p50       p25       p75       min       max
-------------+--------------------------------------------------------------------------------
before090119 |     324.0     677.0     263.0     616.5     510.5     766.5     312.0    2463.0
  wkslater_2 |      14.0     840.4     191.4     845.5     658.0     987.0     611.0    1161.0
  wkslater_3 |      21.0     781.9     179.5     715.0     643.0     880.0     587.0    1161.0
  wkslater_4 |      28.0     752.0     183.4     713.0     613.5     879.0     450.0    1161.0
  wkslater_5 |      35.0     719.5     176.9     655.0     595.0     813.0     450.0    1161.0
  wkslater_6 |      42.0     701.0     167.6     642.5     595.0     776.0     450.0    1161.0
  wkslater_7 |      49.0     694.9     163.0     643.0     595.0     736.0     450.0    1161.0
----------------------------------------------------------------------------------------------


Percent changes:
Code:
. * For Means
. di (695-677)*100/677
2.6587888

. * For Medians
. di (643-617)*100/617
4.2139384

8176  Other / Meta / Re: It is extremely hard to gain merits on: March 05, 2019, 04:30:19 PM
sMerits are abundantly everywhere.
Someone hold them without any specific purposes.
Someone hold them with good purposes, but they have not found merit deserved threads or posts to give their smerits.

In short, I believe that sMerits are not too scarce as most of us imagined, they are abundantly, and need deserved threads or posts to be sent to them.
In other words, sMerit is not scarce, whilst the good, merit derserved threads/ posts are really scarce.
As for my case, I earned more than 130 merits since December last year, and only fall behind a little bit to the minimum required merits to promote to Senior Member.
I will try and believe that I can get promoted till the end of March.
8177  Other / Meta / Re: Time Series Analysis on Distributed Merits in the forum (daily, weekly, monthly) on: March 05, 2019, 04:00:43 PM
Update on intra-day merit
(from 24/1/2018 to 27/2/2019)


Time series plots:
Full dataset

Truncated dataset:



Basic statistics:
Full dataset
Code:
. tabstat merit, s(n mean sd p50 p25 p75 min max)

    variable |         N      mean        sd       p50       p25       p75       min       max
-------------+--------------------------------------------------------------------------------
       merit |       400   824.725  852.1836       636     525.5     810.5       312     13018
----------------------------------------------------------------------------------------------
First two days dropped, and last two days dropped (due to incomplete week, 2019w9):
Code:
. tabstat merit, s(n mean sd p50 p25 p75 min max) format(%9.1f)

    variable |         N      mean        sd       p50       p25       p75       min       max
-------------+--------------------------------------------------------------------------------
       merit |     396.0     779.9     515.5     634.0     524.0     807.5     312.0    4493.0
----------------------------------------------------------------------------------------------

Potential outliers:
Code:
. list id merit date if (merit >= 1232.75 | merit <= 98.75) & merit != .

     +-------------------------+
     |  id   merit        date |
     |-------------------------|
  1. |   3    4493   26jan2018 |
  2. |   4    3489   27jan2018 |
  3. |   5    3188   28jan2018 |
  4. |   6    3799   29jan2018 |
  5. |   7    4192   30jan2018 |
     |-------------------------|
  6. |   8    2820   31jan2018 |
  7. |   9    2545   01feb2018 |
  8. |  10    2568   02feb2018 |
  9. |  11    1867   03feb2018 |
 10. |  12    2167   04feb2018 |
     |-------------------------|
 11. |  13    2077   05feb2018 |
 12. |  14    2308   06feb2018 |
 13. |  15    2141   07feb2018 |
 14. |  16    2141   08feb2018 |
 15. |  17    1448   09feb2018 |
     |-------------------------|
 16. |  18    1747   10feb2018 |
 17. |  19    1442   11feb2018 |
 18. |  20    1331   12feb2018 |
 19. |  21    1579   13feb2018 |
 20. |  22    2513   14feb2018 |
     |-------------------------|
 21. |  23    1991   15feb2018 |
 22. |  24    1411   16feb2018 |
 23. |  25    1608   17feb2018 |
 24. |  26    1289   18feb2018 |
 25. |  27    1403   19feb2018 |
     |-------------------------|
 27. |  29    1266   21feb2018 |
 28. |  30    1279   22feb2018 |
 30. |  32    1409   24feb2018 |
 32. |  34    1382   26feb2018 |
 33. |  35    1326   27feb2018 |
     |-------------------------|
 35. |  37    1333   01mar2018 |
 36. |  38    1696   02mar2018 |
 39. |  41    1245   05mar2018 |
 46. |  48    1354   12mar2018 |
 54. |  56    1322   20mar2018 |
     |-------------------------|
 66. |  68    1233   01apr2018 |
234. | 236    2463   16sep2018 |
235. | 237    1862   17sep2018 |
236. | 238    1294   18sep2018 |
237. | 239    1268   19sep2018 |
     +-------------------------+
How many outliers identified?
Code:
. count if (merit >= 1232.75 | merit <= 98.75) & merit != .
  40
40 days in total are extremely potential outliers.

List of 40 potential outliers, none of them occured in 2019.
Code:
. list id merit date if (merit >= 1232.75 | merit <= 98.75) & merit != .

     +-------------------------+
     |  id   merit        date |
     |-------------------------|
  1. |   3    4493   26jan2018 |
  2. |   4    3489   27jan2018 |
  3. |   5    3188   28jan2018 |
  4. |   6    3799   29jan2018 |
  5. |   7    4192   30jan2018 |
     |-------------------------|
  6. |   8    2820   31jan2018 |
  7. |   9    2545   01feb2018 |
  8. |  10    2568   02feb2018 |
  9. |  11    1867   03feb2018 |
 10. |  12    2167   04feb2018 |
     |-------------------------|
 11. |  13    2077   05feb2018 |
 12. |  14    2308   06feb2018 |
 13. |  15    2141   07feb2018 |
 14. |  16    2141   08feb2018 |
 15. |  17    1448   09feb2018 |
     |-------------------------|
 16. |  18    1747   10feb2018 |
 17. |  19    1442   11feb2018 |
 18. |  20    1331   12feb2018 |
 19. |  21    1579   13feb2018 |
 20. |  22    2513   14feb2018 |
     |-------------------------|
 21. |  23    1991   15feb2018 |
 22. |  24    1411   16feb2018 |
 23. |  25    1608   17feb2018 |
 24. |  26    1289   18feb2018 |
 25. |  27    1403   19feb2018 |
     |-------------------------|
 27. |  29    1266   21feb2018 |
 28. |  30    1279   22feb2018 |
 30. |  32    1409   24feb2018 |
 32. |  34    1382   26feb2018 |
 33. |  35    1326   27feb2018 |
     |-------------------------|
 35. |  37    1333   01mar2018 |
 36. |  38    1696   02mar2018 |
 39. |  41    1245   05mar2018 |
 46. |  48    1354   12mar2018 |
 54. |  56    1322   20mar2018 |
     |-------------------------|
 66. |  68    1233   01apr2018 |
234. | 236    2463   16sep2018 |
235. | 237    1862   17sep2018 |
236. | 238    1294   18sep2018 |
237. | 239    1268   19sep2018 |
     +-------------------------+

Truncated dataset
Code:
. tabstat merit, s(n mean sd p50 p25 p75 min max) format(%9.1f)

    variable |         N      mean        sd       p50       p25       p75       min       max
-------------+--------------------------------------------------------------------------------
       merit |     372.0     679.2     252.4     618.5     518.5     766.5     312.0    2463.0
----------------------------------------------------------------------------------------------

Potential outliers:
Code:

How many potential outliers identified in truncated dataset?
Code:
. count if (merit >= 1138.5 | merit <= 146.5) & merit != .
  22
List of those 22 days
Code:
. list id merit date if (merit >= 1138.5 | merit <= 146.5) & merit != .

     +-------------------------+
     |  id   merit        date |
     |-------------------------|
  1. |  27    1403   19feb2018 |
  2. |  28    1169   20feb2018 |
  3. |  29    1266   21feb2018 |
  4. |  30    1279   22feb2018 |
  6. |  32    1409   24feb2018 |
     |-------------------------|
  7. |  33    1186   25feb2018 |
  8. |  34    1382   26feb2018 |
  9. |  35    1326   27feb2018 |
 11. |  37    1333   01mar2018 |
 12. |  38    1696   02mar2018 |
     |-------------------------|
 15. |  41    1245   05mar2018 |
 22. |  48    1354   12mar2018 |
 24. |  50    1159   14mar2018 |
 30. |  56    1322   20mar2018 |
 31. |  57    1227   21mar2018 |
     |-------------------------|
 42. |  68    1233   01apr2018 |
 43. |  69    1146   02apr2018 |
210. | 236    2463   16sep2018 |
211. | 237    1862   17sep2018 |
212. | 238    1294   18sep2018 |
     |-------------------------|
213. | 239    1268   19sep2018 |
325. | 351    1161   09jan2019 |
     +-------------------------+
Only one of them occured in 2019, on 09/1/2019.
8178  Other / Meta / Re: Time Series Analysis on Distributed Merits in the forum (daily, weekly, monthly) on: March 02, 2019, 04:45:51 PM
I thank you, LoyceV, for another data dump this week.

Update:
Converted intra-day merits in 2019
Code:
. list id merit date day month2 year week month dofw if year == 2019

     +-----------------------------------------------------------------------------+
     |  id   merit        date   day   month2   year     week    month        dofw |
     |-----------------------------------------------------------------------------|
343. | 343     603   01jan2019     1        1   2019   2019w1   2019m1     Tuesday |
344. | 344     526   02jan2019     2        1   2019   2019w1   2019m1   Wednesday |
345. | 345     394   03jan2019     3        1   2019   2019w1   2019m1    Thursday |
346. | 346    1082   04jan2019     4        1   2019   2019w1   2019m1      Friday |
347. | 347     835   05jan2019     5        1   2019   2019w1   2019m1    Saturday |
     |-----------------------------------------------------------------------------|
348. | 348     783   06jan2019     6        1   2019   2019w1   2019m1      Sunday |
349. | 349     570   07jan2019     7        1   2019   2019w1   2019m1      Monday |
350. | 350     782   08jan2019     8        1   2019   2019w2   2019m1     Tuesday |
351. | 351    1161   09jan2019     9        1   2019   2019w2   2019m1   Wednesday |
352. | 352     987   10jan2019    10        1   2019   2019w2   2019m1    Thursday |
     |-----------------------------------------------------------------------------|
353. | 353     878   11jan2019    11        1   2019   2019w2   2019m1      Friday |
354. | 354     711   12jan2019    12        1   2019   2019w2   2019m1    Saturday |
355. | 355     978   13jan2019    13        1   2019   2019w2   2019m1      Sunday |
356. | 356    1127   14jan2019    14        1   2019   2019w2   2019m1      Monday |
357. | 357     813   15jan2019    15        1   2019   2019w3   2019m1     Tuesday |
     |-----------------------------------------------------------------------------|
358. | 358     880   16jan2019    16        1   2019   2019w3   2019m1   Wednesday |
359. | 359    1018   17jan2019    17        1   2019   2019w3   2019m1    Thursday |
360. | 360     611   18jan2019    18        1   2019   2019w3   2019m1      Friday |
361. | 361     643   19jan2019    19        1   2019   2019w3   2019m1    Saturday |
362. | 362     658   20jan2019    20        1   2019   2019w3   2019m1      Sunday |
     |-----------------------------------------------------------------------------|
363. | 363     683   21jan2019    21        1   2019   2019w3   2019m1      Monday |
364. | 364     618   22jan2019    22        1   2019   2019w4   2019m1     Tuesday |
365. | 365     735   23jan2019    23        1   2019   2019w4   2019m1   Wednesday |
366. | 366     715   24jan2019    24        1   2019   2019w4   2019m1    Thursday |
367. | 367     615   25jan2019    25        1   2019   2019w4   2019m1      Friday |
     |-----------------------------------------------------------------------------|
368. | 368     587   26jan2019    26        1   2019   2019w4   2019m1    Saturday |
369. | 369     655   27jan2019    27        1   2019   2019w4   2019m1      Sunday |
370. | 370     734   28jan2019    28        1   2019   2019w4   2019m1      Monday |
371. | 371     612   29jan2019    29        1   2019   2019w5   2019m1     Tuesday |
372. | 372     510   30jan2019    30        1   2019   2019w5   2019m1   Wednesday |
     |-----------------------------------------------------------------------------|
373. | 373     450   31jan2019    31        1   2019   2019w5   2019m1    Thursday |
374. | 374     595   01feb2019     1        2   2019   2019w5   2019m2      Friday |
375. | 375     940   02feb2019     2        2   2019   2019w5   2019m2    Saturday |
376. | 376     571   03feb2019     3        2   2019   2019w5   2019m2      Sunday |
377. | 377     796   04feb2019     4        2   2019   2019w5   2019m2      Monday |
     |-----------------------------------------------------------------------------|
378. | 378     776   05feb2019     5        2   2019   2019w6   2019m2     Tuesday |
379. | 379     559   06feb2019     6        2   2019   2019w6   2019m2   Wednesday |
380. | 380     548   07feb2019     7        2   2019   2019w6   2019m2    Thursday |
381. | 381     611   08feb2019     8        2   2019   2019w6   2019m2      Friday |
382. | 382     623   09feb2019     9        2   2019   2019w6   2019m2    Saturday |
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383. | 383     559   10feb2019    10        2   2019   2019w6   2019m2      Sunday |
384. | 384     642   11feb2019    11        2   2019   2019w6   2019m2      Monday |
385. | 385     585   12feb2019    12        2   2019   2019w7   2019m2     Tuesday |
386. | 386     671   13feb2019    13        2   2019   2019w7   2019m2   Wednesday |
387. | 387     649   14feb2019    14        2   2019   2019w7   2019m2    Thursday |
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388. | 388     607   15feb2019    15        2   2019   2019w7   2019m2      Friday |
389. | 389     523   16feb2019    16        2   2019   2019w7   2019m2    Saturday |
390. | 390     607   17feb2019    17        2   2019   2019w7   2019m2      Sunday |
391. | 391     565   18feb2019    18        2   2019   2019w7   2019m2      Monday |
392. | 392     637   19feb2019    19        2   2019   2019w8   2019m2     Tuesday |
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393. | 393     696   20feb2019    20        2   2019   2019w8   2019m2   Wednesday |
394. | 394     504   21feb2019    21        2   2019   2019w8   2019m2    Thursday |
395. | 395     509   22feb2019    22        2   2019   2019w8   2019m2      Friday |
396. | 396     657   23feb2019    23        2   2019   2019w8   2019m2    Saturday |
397. | 397     608   24feb2019    24        2   2019   2019w8   2019m2      Sunday |
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398. | 398     896   25feb2019    25        2   2019   2019w8   2019m2      Monday |
399. | 399     736   26feb2019    26        2   2019   2019w9   2019m2     Tuesday |
400. | 400     553   27feb2019    27        2   2019   2019w9   2019m2   Wednesday |
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For days in 2018, please get them there
8179  Other / Meta / Re: [CLUBS] Top Merited-Users Classified into 4 Clubs on: March 02, 2019, 04:40:15 PM
I would add one more sub-club namely "kissed by Lauda"
LOL, you should create your new own club, not here.
Such kind of sub-club as kissed-by-Lauda club will get support from CH, but I don't support it here.
It is very distracting from the main purposes of the topic, that is giving list of the top earned-merits profiles and their merited threads.
Those cases might be inspirational stories for forum users.
8180  Other / Meta / Re: [TOP-200] Members who support newbies - Thanks! on: March 02, 2019, 04:37:09 PM
even when  looking at the post history as its usually so short.
There are two possible hypotheses:
(1) They are farm accounts. Got promoted from minor merit abusements to move upwards to Junior Member rank.
Then, later they got banned due to plagiarism.
(2) They are real accounts (not farm ones): But, they simply tried making pseudo- / fake- quality threads to earn at least one merit.
Then, later they got banned due to plagiarism.

I don't see reason to sell Junior Member accounts. The most probable scenario is bans due to plagiarism.
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