You can now book 550,000+ hotels in 210 countries using DASH. Travel to 82,000+ destinations worldwide on Travala.com the next-gen online travel agency  Great, tungfa. Over recent months, DASH has expanded to so many nations, especially in Latin America and Africa continents.
I have a big question for myself, that is 'When the expansion will show its impacts on DASH acceptance, level of usage, and price'. |
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Personally, I do not see reasons why the 2.500.000 user is a good reason to feel happy about the current situation of the forum.
Furthermore, amongst 2.500.000 forum users, so many cases been permanent banned or nuked.
Congrats[fairly/ unfairly] like this don't help the forum in general, because the sort of compliment might play as one of main motivational forces for spammers/ bot-creating tools/ etc. to make more massively automatic account creation.
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Congratulations for being able to post images. Thanks a lot! yes, now I can post images!  As I told you, there are two options for you. It is clearly that you choose the first option, buying a Paid Copper Membership. 1) Buying a Copper Membership, which is not too expensive. As a developer of Bitcoin Stash project, I strongly suggest you to spend a little BTC to buy a Copper membership. Here is link for your interest: Paid memberships. Nearly 0.0021 BTC! |
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I have still waited for the update statistics from LoyceV.
I guess that LoyceV will help with new dataset tomorrow. This week has witness a bit delayed update from LoyceV.
Anyway, it does not matter with me. I will wait patiently.
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Some days ago, I read a topic created by someone [who I have not remembered his / her account name] on those indicators with updated statistics till recent months of 2018.
I have intention to make a fully time series graph.
Therefore, someone read and remember where the topic is, please give me link.
Thank you for your help, all you guys.
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You don't need a project for smerit, just a good/helpful post.
Nothing really difficult.
Ah, saying like this, what I meant is mainly because the author of the question is bstash. He/ she is a developer of Bitcoin Stash project. Therefore, building up a good Bitcoin Stash project is one of good ways for him/ her to earn merits. This is why I recommended him / her with two approaches. |
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You can make it. So I still need 1 merit to become a Jr. member!  There are two ways: 1) Buying a Copper Membership, which is not too expensive. As a developer of Bitcoin Stash project, I strongly suggest you to spend a little BTC to buy a Copper membership. Here is link for your interest: Paid memberships. Nearly 0.0021 BTC! 2) Building up a good project, then supporters/ investors of Bitcoin Stash will give you their sMerits later. This way, will take a lot of time, and mainly depend upon the quality of your project. |
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More pointless data that no one cares about. Just another piece of shit fishing for merit by making some graphs.
Hey dude, At first, you should look at your post history, before trolling me like this. It is too ridiculous when a guy with so many one-lined threads criticized me on how to make constructive threads/ topics.
At least, it give me a hint on potential things that can happened. Your are right, because I can not go to any causal inference with such limited data with only three variables (all of them are independent variables), without appropriate independent variables. I'll praised you that you gave an effort on creating a data analysis via time series but I don't it is the right way to use it. Time series is usually being use in the prices of assets to determine their movements through time. If you want to determine if their is some kind of seasonability when it comes to new members registering in the forum you should have put BTC's prices as an additional data to determine if there is some kind of connection why there are peaks in registration every two years. Simply putting two data internal to the forum won't give you as much of a reason why those peaks are happening.
It's just a assumption without real data, but you are probably right. The important thing is the level of increasing new posts, new users, new topics recent months when Bitcoin dropped. From the past ( as shown in the chart), three indicators tend to tell with Bitcoin drops.  New users & new threads will definitely be increasing due to the recent price fall. This is unfortunately the perfect time for trolls/fudsters & genuine assholes to infect the entire forum with their absolute disease.
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Your ideas look good, but it should be adjusted a little bit. need first 1 merit from others for Newbie to be Jr., wear the signature and post the image.
need first 1 merit from others for Member to wear the signature.
need first 2 merit from others for FM, Sr. to wear the signature.
need first 3 merit from others for Hero, Legend to wear the signature.
Something like this one, increasing merits required for each rank, higher than required merits at the beginning of merit system. It means users have to earn at least 1, 2 or 3 merits by themselves from their constructive threads or from merit selling ( ) in order to maintain their ranks. If they are unable to do this, they will be automatically demoted, like Junior Members in September this year.
If the suggestion will be really implemented, we will definitely witness a massive wave of demotion from higher ranked users, from Full Members to Ledgendary. We might see a shocking events in the forum, one of the biggest shocks since the start of bitcointalk forum, including the implementation of merit system, and this one (if occur). |
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Update on monthly merit analysis: Notes:- The January is incomplete month (only from 24th Jan. to then end of Jan.) - The December has been dropped due to incomplete month.
Abstract- The first three months of 2018, January, February, and March are the highest month in terms of total montly merits. The fact is not strange, obviously. - Interestingly, there is a spike in September, when a demoted wave of Junior Members occured, which in turn resulted in massive merit abusements. - Median is 19597, and the interquartile range is from 18047 to 32084.
1) Time series plot2) Basic statisticsMean +/- standard deviation: 24944 +/- 10505 Median (Interquartile range): 19597 (18047 - 32084) Min - Max: 16317 - 46630 . list month merit
+-----------------+
| month merit |
|-----------------|
1. | 2018m1 41760 |
2. | 2018m2 46630 |
3. | 2018m3 32084 |
4. | 2018m4 23173 |
5. | 2018m5 19597 |
|-----------------|
6. | 2018m6 18752 |
7. | 2018m7 18047 |
8. | 2018m8 16317 |
9. | 2018m9 22261 |
10. | 2018m10 18395 |
|-----------------|
11. | 2018m11 17370 |
+-----------------+
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Updates for today. You all can enjoy my newest analysis.  Thanks LoyceV for updates last two weeks. I am busy recent days, so I did not update my topic last week. I will do it hours later today.
Abstract (for truncated dataset) 50% of observed days (since 19/02/2018 to 02/12/2018) have its total daily merits below 626 (the median) or higher than 626. Importantly, 50% of observed days have their total daily merits in the range from 521 to 774, which is the interquartile range that ranges from the 25th quartile (Q1) to the 75th quartile (Q3). The minimum and maximum daily merits during the period are 347 and 2463, respectively. Potential outliers are days that have total merits above 1154 or below 142.About medians of merits over days of week, Monday is the highest with 674 merits distributed on Mondays in medians, and Friday is the lowest with the median of Friday merits is 542. There are nearly 24% difference between the medians of Friday and Monday.And, Friday is the only day of week which has median lower than 600.
Updates:1) Daily merits1.1. Full dataset (from 24/1/2018 to 2/12/2018) I dropped days after 2/12/2018 because those days belong to the 2018w49, which has not completed with LoyceV data source). Now, lets' take a look at its basic statistics: During the whole period since the beginning day of merit system, the daily merits has its median is 643, which means that 50% of those observed days have their daily merits above 643, and 50% of them have their daily merits above 643. - The interquartile range (from 25th to 75th quartile): is 530 - 858. It means that 50% of those observed days have daily merits in the range from 530 to 858. In addition, 25% of those days have daily merits below 530 (below the 25h quartile), while 25% of them have daily merits above 858 (above the 75th quartile). - The mean +/- standard deviation: is 880 +/- 952. I don't want to use those statistics due to dramatical biases from outliers. Extremely potential outliers are days have their total daily merits above 1350 or below 38. Detailed calculations presented below: - Below: Q1 -1.5*IQR = 530-(1.5*328) = 38; - or Above: Q3 + 1.5*IQR = 858+(1.5*328) = 1350. - IQR = Q3 - Q1 = 858 - 530 = 328 From now on, I only presented analytical results for truncated dataset. What is truncated dataset? It is the dataset, after truncating / dropping all days before 19/02/2018, which are extremely outliers. . list id date week month merit if merit > 1350 & merit != .
+--------------------------------------------+
| id date week month merit |
|--------------------------------------------|
1. | 1 24jan2018 2018w4 2018m1 13018 |
2. | 2 25jan2018 2018w4 2018m1 6761 |
3. | 3 26jan2018 2018w4 2018m1 4493 |
4. | 4 27jan2018 2018w4 2018m1 3489 |
5. | 5 28jan2018 2018w4 2018m1 3188 |
|--------------------------------------------|
6. | 6 29jan2018 2018w5 2018m1 3799 |
7. | 7 30jan2018 2018w5 2018m1 4192 |
8. | 8 31jan2018 2018w5 2018m1 2820 |
9. | 9 01feb2018 2018w5 2018m2 2545 |
10. | 10 02feb2018 2018w5 2018m2 2568 |
|--------------------------------------------|
11. | 11 03feb2018 2018w5 2018m2 1867 |
12. | 12 04feb2018 2018w5 2018m2 2167 |
13. | 13 05feb2018 2018w6 2018m2 2077 |
14. | 14 06feb2018 2018w6 2018m2 2308 |
15. | 15 07feb2018 2018w6 2018m2 2141 |
|--------------------------------------------|
16. | 16 08feb2018 2018w6 2018m2 2141 |
17. | 17 09feb2018 2018w6 2018m2 1448 |
18. | 18 10feb2018 2018w6 2018m2 1747 |
19. | 19 11feb2018 2018w6 2018m2 1442 |
21. | 21 13feb2018 2018w7 2018m2 1579 |
|--------------------------------------------|
22. | 22 14feb2018 2018w7 2018m2 2513 |
23. | 23 15feb2018 2018w7 2018m2 1991 |
24. | 24 16feb2018 2018w7 2018m2 1411 |
25. | 25 17feb2018 2018w7 2018m2 1608 |
27. | 27 19feb2018 2018w8 2018m2 1403 |
|--------------------------------------------|
32. | 32 24feb2018 2018w8 2018m2 1409 |
34. | 34 26feb2018 2018w9 2018m2 1382 |
38. | 38 02mar2018 2018w9 2018m3 1696 |
48. | 48 12mar2018 2018w11 2018m3 1354 |
236. | 236 16sep2018 2018w37 2018m9 2463 |
|--------------------------------------------|
237. | 237 17sep2018 2018w38 2018m9 1862 |
+--------------------------------------------+
As you can easily see that there are some days listed as extremely outliers after 19th Feb. 2018, but I left them in the dataset, not truncated them, in order to have full weeks in truncated dataset. - Median: 626 - Interquartile range: 521 - 774 - Mean +/- standard deviation: 695 +/- 268 - Extremely potential outliers: above 1154 or below 142. With IQR = 774 - 521 = 253 Q1 - 1.5*IQR = 521 - 1.5*253 = 141.5 ~ 142 Q3 + 1.5*IQR = 774 + 1.5*253 = 1153.5 ~ 1154. Box plotsa) Box plot of daily merits since 19th February 2018 to 2nd December 2018.Merit after presents statistics of the whole period from 19/2/2018 to 2/12/2018. w26 presents statistics of the period that started on 19/2/2018 to the end of the week26 (on 01/7/2018) b) Box plot of daily merit (full dataset). This one is only for reference.
Merits over days of weekRaw statisticsSummary for variables: merit
by categories of: dofw
dofw | N mean sd p50 p25 p75 min max
----------+--------------------------------------------------------------------------------
Sunday | 41.0 715.7 360.5 603.0 476.0 829.0 412.0 2463.0
Monday | 41.0 771.3 314.1 674.0 562.0 884.0 455.0 1862.0
Tuesday | 41.0 715.0 246.1 632.0 580.0 767.0 383.0 1326.0
Wednesday | 41.0 723.5 227.1 652.0 562.0 761.0 435.0 1268.0
Thursday | 41.0 687.0 220.7 644.0 528.0 774.0 376.0 1333.0
Friday | 41.0 611.7 238.0 542.0 463.0 698.0 348.0 1696.0
Saturday | 41.0 639.5 223.3 614.0 463.0 688.0 347.0 1409.0
----------+--------------------------------------------------------------------------------
Total | 287.0 694.8 268.1 626.0 521.0 774.0 347.0 2463.0
-------------------------------------------------------------------------------------------
What we got here? The days of week that have lowest and highest means of totally merits are Friday and Wednesday, at 612 and 724 merits distributed, respectively. It means there are (724 - 612) = 212 merit difference or the Wednesday have nearly 18% total merits higher than the Friday. Personally, it is a dramatical difference. . di (724-612)*100/612
18.300654
Now, how about median difference? The days of week that have lowest and highest medians of totally merits are Friday and Monday, at 542 and 674, respectively. It means that there are (674-542) = 132 merit points diference between the Friday and Monday. In other words, there are nearly 24% difference between the medians of Friday and Monday.. di (674-542)*100/542
24.354244
a) Outliers displayed. b) Outliers non-displayed. Statistics of full dataset (just for reference) Summary for variables: merit
by categories of: dofw
dofw | N mean sd p50 p25 p75 min max
----------+--------------------------------------------------------------------------------
Sunday | 45.0 831.8 557.3 619.0 486.0 880.0 412.0 3188.0
Monday | 44.0 882.5 582.4 681.0 575.5 945.0 455.0 3799.0
Tuesday | 44.0 849.9 628.7 638.5 580.0 890.5 383.0 4192.0
Wednesday | 45.0 1114.5 1882.6 681.0 569.0 963.0 435.0 13018.0
Thursday | 45.0 924.5 995.1 673.0 530.0 846.0 376.0 6761.0
Friday | 45.0 777.7 695.0 554.0 475.0 774.0 348.0 4493.0
Saturday | 45.0 776.2 542.4 627.0 506.0 778.0 347.0 3489.0
----------+--------------------------------------------------------------------------------
Total | 313.0 879.7 951.8 643.0 530.0 858.0 347.0 13018.0
-------------------------------------------------------------------------------------------
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Update on weekly merit analysis.1) Full weekly converted dataset. list
+-----------------+
| week merit |
|-----------------|
1. | 2018w4 30949 |
2. | 2018w5 19958 |
3. | 2018w6 13304 |
4. | 2018w7 11722 |
5. | 2018w8 8758 |
|-----------------|
6. | 2018w9 8806 |
7. | 2018w10 7253 |
8. | 2018w11 7309 |
9. | 2018w12 6941 |
10. | 2018w13 6707 |
|-----------------|
11. | 2018w14 6415 |
12. | 2018w15 5487 |
13. | 2018w16 4631 |
14. | 2018w17 4585 |
15. | 2018w18 4953 |
|-----------------|
16. | 2018w19 4753 |
17. | 2018w20 4346 |
18. | 2018w21 3854 |
19. | 2018w22 4183 |
20. | 2018w23 4527 |
|-----------------|
21. | 2018w24 3818 |
22. | 2018w25 4921 |
23. | 2018w26 4457 |
24. | 2018w27 4253 |
25. | 2018w28 4239 |
|-----------------|
26. | 2018w29 4159 |
27. | 2018w30 3652 |
28. | 2018w31 3798 |
29. | 2018w32 3994 |
30. | 2018w33 3618 |
|-----------------|
31. | 2018w34 3789 |
32. | 2018w35 3065 |
33. | 2018w36 3574 |
34. | 2018w37 5630 |
35. | 2018w38 7825 |
|-----------------|
36. | 2018w39 4388 |
37. | 2018w40 4271 |
38. | 2018w41 3800 |
39. | 2018w42 4821 |
40. | 2018w43 3945 |
|-----------------|
41. | 2018w44 3339 |
42. | 2018w45 4513 |
43. | 2018w46 3722 |
44. | 2018w47 4558 |
45. | 2018w48 3750 |
+-----------------+
2) Time series plot
3) Basic statistics (for truncated dataset) The median of weekly merits is 4388. It means that 50% of observed weeks have their merits above 4388, and 50% of them have their merits below 4388. The interquartile range, from 3818 to 4953, discloses that 50% of observed their merits above 3818 and below 4953. It also means that 25% of weeks have their merits below 3818 and 25% of weeks have their merits above 4953. The minimum and maximum of observed weeks (since 19/02/2018 to 02/12/2018) are 3065 and 8806, respectively.
3) Box plotFull dataset Only weeks of truncated dataset. Potential outliers:Q1 = 3818 Q3 = 4953 ----> IQR = Q3 - Q1 = 4953 - 3818 = 1135 ----> 1.5*IQR = 1135*1.5 = 1702.5 Potential outliers are weeks that have total merits above 6655.5 (~6656) or below 2115 (~2116). Detail calculations presented below * Q1 - 1.5*IQR
. di 3818-1702.5
2115.5
* Q3 + 1.5*IQR
. di 4953+1702.5
6655.5
There are seven weeks are potential outliers: . list week merit if merit > 6656 | merit < 2116, abb(30)
+-----------------+
| week merit |
|-----------------|
1. | 2018w8 8758 |
2. | 2018w9 8806 |
3. | 2018w10 7253 |
4. | 2018w11 7309 |
5. | 2018w12 6941 |
|-----------------|
6. | 2018w13 6707 |
31. | 2018w38 7825 |
+-----------------+
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Full converted daily dataset (used for analysis in the above thread). . list id merit day month2 year date dofw week month
+-------------------------------------------------------------------------------+
| id merit day month2 year date dofw week month |
|-------------------------------------------------------------------------------|
1. | 1 13018 24 1 2018 24jan2018 Wednesday 2018w4 2018m1 |
2. | 2 6761 25 1 2018 25jan2018 Thursday 2018w4 2018m1 |
3. | 3 4493 26 1 2018 26jan2018 Friday 2018w4 2018m1 |
4. | 4 3489 27 1 2018 27jan2018 Saturday 2018w4 2018m1 |
5. | 5 3188 28 1 2018 28jan2018 Sunday 2018w4 2018m1 |
|-------------------------------------------------------------------------------|
6. | 6 3799 29 1 2018 29jan2018 Monday 2018w5 2018m1 |
7. | 7 4192 30 1 2018 30jan2018 Tuesday 2018w5 2018m1 |
8. | 8 2820 31 1 2018 31jan2018 Wednesday 2018w5 2018m1 |
9. | 9 2545 1 2 2018 01feb2018 Thursday 2018w5 2018m2 |
10. | 10 2568 2 2 2018 02feb2018 Friday 2018w5 2018m2 |
|-------------------------------------------------------------------------------|
11. | 11 1867 3 2 2018 03feb2018 Saturday 2018w5 2018m2 |
12. | 12 2167 4 2 2018 04feb2018 Sunday 2018w5 2018m2 |
13. | 13 2077 5 2 2018 05feb2018 Monday 2018w6 2018m2 |
14. | 14 2308 6 2 2018 06feb2018 Tuesday 2018w6 2018m2 |
15. | 15 2141 7 2 2018 07feb2018 Wednesday 2018w6 2018m2 |
|-------------------------------------------------------------------------------|
16. | 16 2141 8 2 2018 08feb2018 Thursday 2018w6 2018m2 |
17. | 17 1448 9 2 2018 09feb2018 Friday 2018w6 2018m2 |
18. | 18 1747 10 2 2018 10feb2018 Saturday 2018w6 2018m2 |
19. | 19 1442 11 2 2018 11feb2018 Sunday 2018w6 2018m2 |
20. | 20 1331 12 2 2018 12feb2018 Monday 2018w7 2018m2 |
|-------------------------------------------------------------------------------|
21. | 21 1579 13 2 2018 13feb2018 Tuesday 2018w7 2018m2 |
22. | 22 2513 14 2 2018 14feb2018 Wednesday 2018w7 2018m2 |
23. | 23 1991 15 2 2018 15feb2018 Thursday 2018w7 2018m2 |
24. | 24 1411 16 2 2018 16feb2018 Friday 2018w7 2018m2 |
25. | 25 1608 17 2 2018 17feb2018 Saturday 2018w7 2018m2 |
|-------------------------------------------------------------------------------|
26. | 26 1289 18 2 2018 18feb2018 Sunday 2018w7 2018m2 |
27. | 27 1403 19 2 2018 19feb2018 Monday 2018w8 2018m2 |
28. | 28 1169 20 2 2018 20feb2018 Tuesday 2018w8 2018m2 |
29. | 29 1266 21 2 2018 21feb2018 Wednesday 2018w8 2018m2 |
30. | 30 1279 22 2 2018 22feb2018 Thursday 2018w8 2018m2 |
|-------------------------------------------------------------------------------|
31. | 31 1046 23 2 2018 23feb2018 Friday 2018w8 2018m2 |
32. | 32 1409 24 2 2018 24feb2018 Saturday 2018w8 2018m2 |
33. | 33 1186 25 2 2018 25feb2018 Sunday 2018w8 2018m2 |
34. | 34 1382 26 2 2018 26feb2018 Monday 2018w9 2018m2 |
35. | 35 1326 27 2 2018 27feb2018 Tuesday 2018w9 2018m2 |
|-------------------------------------------------------------------------------|
36. | 36 991 28 2 2018 28feb2018 Wednesday 2018w9 2018m2 |
37. | 37 1333 1 3 2018 01mar2018 Thursday 2018w9 2018m3 |
38. | 38 1696 2 3 2018 02mar2018 Friday 2018w9 2018m3 |
39. | 39 1089 3 3 2018 03mar2018 Saturday 2018w9 2018m3 |
40. | 40 989 4 3 2018 04mar2018 Sunday 2018w9 2018m3 |
|-------------------------------------------------------------------------------|
41. | 41 1245 5 3 2018 05mar2018 Monday 2018w10 2018m3 |
42. | 42 1074 6 3 2018 06mar2018 Tuesday 2018w10 2018m3 |
43. | 43 1109 7 3 2018 07mar2018 Wednesday 2018w10 2018m3 |
44. | 44 922 8 3 2018 08mar2018 Thursday 2018w10 2018m3 |
45. | 45 789 9 3 2018 09mar2018 Friday 2018w10 2018m3 |
|-------------------------------------------------------------------------------|
46. | 46 1023 10 3 2018 10mar2018 Saturday 2018w10 2018m3 |
47. | 47 1091 11 3 2018 11mar2018 Sunday 2018w10 2018m3 |
48. | 48 1354 12 3 2018 12mar2018 Monday 2018w11 2018m3 |
49. | 49 994 13 3 2018 13mar2018 Tuesday 2018w11 2018m3 |
50. | 50 1159 14 3 2018 14mar2018 Wednesday 2018w11 2018m3 |
|-------------------------------------------------------------------------------|
51. | 51 1130 15 3 2018 15mar2018 Thursday 2018w11 2018m3 |
52. | 52 840 16 3 2018 16mar2018 Friday 2018w11 2018m3 |
53. | 53 797 17 3 2018 17mar2018 Saturday 2018w11 2018m3 |
54. | 54 1035 18 3 2018 18mar2018 Sunday 2018w11 2018m3 |
55. | 55 992 19 3 2018 19mar2018 Monday 2018w12 2018m3 |
|-------------------------------------------------------------------------------|
56. | 56 1322 20 3 2018 20mar2018 Tuesday 2018w12 2018m3 |
57. | 57 1227 21 3 2018 21mar2018 Wednesday 2018w12 2018m3 |
58. | 58 764 22 3 2018 22mar2018 Thursday 2018w12 2018m3 |
59. | 59 733 23 3 2018 23mar2018 Friday 2018w12 2018m3 |
60. | 60 1045 24 3 2018 24mar2018 Saturday 2018w12 2018m3 |
|-------------------------------------------------------------------------------|
61. | 61 858 25 3 2018 25mar2018 Sunday 2018w12 2018m3 |
62. | 62 808 26 3 2018 26mar2018 Monday 2018w13 2018m3 |
63. | 63 879 27 3 2018 27mar2018 Tuesday 2018w13 2018m3 |
64. | 64 848 28 3 2018 28mar2018 Wednesday 2018w13 2018m3 |
65. | 65 1043 29 3 2018 29mar2018 Thursday 2018w13 2018m3 |
|-------------------------------------------------------------------------------|
66. | 66 928 30 3 2018 30mar2018 Friday 2018w13 2018m3 |
67. | 67 968 31 3 2018 31mar2018 Saturday 2018w13 2018m3 |
68. | 68 1233 1 4 2018 01apr2018 Sunday 2018w13 2018m4 |
69. | 69 1146 2 4 2018 02apr2018 Monday 2018w14 2018m4 |
70. | 70 1080 3 4 2018 03apr2018 Tuesday 2018w14 2018m4 |
|-------------------------------------------------------------------------------|
71. | 71 1061 4 4 2018 04apr2018 Wednesday 2018w14 2018m4 |
72. | 72 838 5 4 2018 05apr2018 Thursday 2018w14 2018m4 |
73. | 73 620 6 4 2018 06apr2018 Friday 2018w14 2018m4 |
74. | 74 614 7 4 2018 07apr2018 Saturday 2018w14 2018m4 |
75. | 75 1056 8 4 2018 08apr2018 Sunday 2018w14 2018m4 |
|-------------------------------------------------------------------------------|
76. | 76 884 9 4 2018 09apr2018 Monday 2018w15 2018m4 |
77. | 77 768 10 4 2018 10apr2018 Tuesday 2018w15 2018m4 |
78. | 78 963 11 4 2018 11apr2018 Wednesday 2018w15 2018m4 |
79. | 79 917 12 4 2018 12apr2018 Thursday 2018w15 2018m4 |
80. | 80 682 13 4 2018 13apr2018 Friday 2018w15 2018m4 |
|-------------------------------------------------------------------------------|
81. | 81 681 14 4 2018 14apr2018 Saturday 2018w15 2018m4 |
82. | 82 592 15 4 2018 15apr2018 Sunday 2018w15 2018m4 |
83. | 83 609 16 4 2018 16apr2018 Monday 2018w16 2018m4 |
84. | 84 628 17 4 2018 17apr2018 Tuesday 2018w16 2018m4 |
85. | 85 681 18 4 2018 18apr2018 Wednesday 2018w16 2018m4 |
|-------------------------------------------------------------------------------|
86. | 86 848 19 4 2018 19apr2018 Thursday 2018w16 2018m4 |
87. | 87 463 20 4 2018 20apr2018 Friday 2018w16 2018m4 |
88. | 88 522 21 4 2018 21apr2018 Saturday 2018w16 2018m4 |
89. | 89 880 22 4 2018 22apr2018 Sunday 2018w16 2018m4 |
90. | 90 709 23 4 2018 23apr2018 Monday 2018w17 2018m4 |
|-------------------------------------------------------------------------------|
91. | 91 626 24 4 2018 24apr2018 Tuesday 2018w17 2018m4 |
92. | 92 687 25 4 2018 25apr2018 Wednesday 2018w17 2018m4 |
93. | 93 675 26 4 2018 26apr2018 Thursday 2018w17 2018m4 |
94. | 94 583 27 4 2018 27apr2018 Friday 2018w17 2018m4 |
95. | 95 623 28 4 2018 28apr2018 Saturday 2018w17 2018m4 |
|-------------------------------------------------------------------------------|
96. | 96 682 29 4 2018 29apr2018 Sunday 2018w17 2018m4 |
97. | 97 822 30 4 2018 30apr2018 Monday 2018w18 2018m4 |
98. | 98 741 1 5 2018 01may2018 Tuesday 2018w18 2018m5 |
99. | 99 759 2 5 2018 02may2018 Wednesday 2018w18 2018m5 |
100. | 100 747 3 5 2018 03may2018 Thursday 2018w18 2018m5 |
|-------------------------------------------------------------------------------|
101. | 101 597 4 5 2018 04may2018 Friday 2018w18 2018m5 |
102. | 102 688 5 5 2018 05may2018 Saturday 2018w18 2018m5 |
103. | 103 599 6 5 2018 06may2018 Sunday 2018w18 2018m5 |
104. | 104 898 7 5 2018 07may2018 Monday 2018w19 2018m5 |
105. | 105 618 8 5 2018 08may2018 Tuesday 2018w19 2018m5 |
|-------------------------------------------------------------------------------|
106. | 106 761 9 5 2018 09may2018 Wednesday 2018w19 2018m5 |
107. | 107 475 10 5 2018 10may2018 Thursday 2018w19 2018m5 |
108. | 108 867 11 5 2018 11may2018 Friday 2018w19 2018m5 |
109. | 109 415 12 5 2018 12may2018 Saturday 2018w19 2018m5 |
110. | 110 719 13 5 2018 13may2018 Sunday 2018w19 2018m5 |
|-------------------------------------------------------------------------------|
111. | 111 674 14 5 2018 14may2018 Monday 2018w20 2018m5 |
112. | 112 700 15 5 2018 15may2018 Tuesday 2018w20 2018m5 |
113. | 113 652 16 5 2018 16may2018 Wednesday 2018w20 2018m5 |
114. | 114 574 17 5 2018 17may2018 Thursday 2018w20 2018m5 |
115. | 115 542 18 5 2018 18may2018 Friday 2018w20 2018m5 |
|-------------------------------------------------------------------------------|
116. | 116 587 19 5 2018 19may2018 Saturday 2018w20 2018m5 |
117. | 117 617 20 5 2018 20may2018 Sunday 2018w20 2018m5 |
118. | 118 626 21 5 2018 21may2018 Monday 2018w21 2018m5 |
119. | 119 639 22 5 2018 22may2018 Tuesday 2018w21 2018m5 |
120. | 120 531 23 5 2018 23may2018 Wednesday 2018w21 2018m5 |
|-------------------------------------------------------------------------------|
121. | 121 554 24 5 2018 24may2018 Thursday 2018w21 2018m5 |
122. | 122 370 25 5 2018 25may2018 Friday 2018w21 2018m5 |
123. | 123 575 26 5 2018 26may2018 Saturday 2018w21 2018m5 |
124. | 124 559 27 5 2018 27may2018 Sunday 2018w21 2018m5 |
125. | 125 589 28 5 2018 28may2018 Monday 2018w22 2018m5 |
|-------------------------------------------------------------------------------|
126. | 126 638 29 5 2018 29may2018 Tuesday 2018w22 2018m5 |
127. | 127 599 30 5 2018 30may2018 Wednesday 2018w22 2018m5 |
128. | 128 687 31 5 2018 31may2018 Thursday 2018w22 2018m5 |
129. | 129 698 1 6 2018 01jun2018 Friday 2018w22 2018m6 |
130. | 130 461 2 6 2018 02jun2018 Saturday 2018w22 2018m6 |
|-------------------------------------------------------------------------------|
131. | 131 511 3 6 2018 03jun2018 Sunday 2018w22 2018m6 |
132. | 132 773 4 6 2018 04jun2018 Monday 2018w23 2018m6 |
133. | 133 731 5 6 2018 05jun2018 Tuesday 2018w23 2018m6 |
134. | 134 504 6 6 2018 06jun2018 Wednesday 2018w23 2018m6 |
135. | 135 506 7 6 2018 07jun2018 Thursday 2018w23 2018m6 |
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136. | 136 766 8 6 2018 08jun2018 Friday 2018w23 2018m6 |
137. | 137 672 9 6 2018 09jun2018 Saturday 2018w23 2018m6 |
138. | 138 575 10 6 2018 10jun2018 Sunday 2018w23 2018m6 |
139. | 139 519 11 6 2018 11jun2018 Monday 2018w24 2018m6 |
140. | 140 422 12 6 2018 12jun2018 Tuesday 2018w24 2018m6 |
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141. | 141 786 13 6 2018 13jun2018 Wednesday 2018w24 2018m6 |
142. | 142 528 14 6 2018 14jun2018 Thursday 2018w24 2018m6 |
143. | 143 445 15 6 2018 15jun2018 Friday 2018w24 2018m6 |
144. | 144 654 16 6 2018 16jun2018 Saturday 2018w24 2018m6 |
145. | 145 464 17 6 2018 17jun2018 Sunday 2018w24 2018m6 |
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146. | 146 601 18 6 2018 18jun2018 Monday 2018w25 2018m6 |
147. | 147 662 19 6 2018 19jun2018 Tuesday 2018w25 2018m6 |
148. | 148 707 20 6 2018 20jun2018 Wednesday 2018w25 2018m6 |
149. | 149 705 21 6 2018 21jun2018 Thursday 2018w25 2018m6 |
150. | 150 774 22 6 2018 22jun2018 Friday 2018w25 2018m6 |
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151. | 151 643 23 6 2018 23jun2018 Saturday 2018w25 2018m6 |
152. | 152 829 24 6 2018 24jun2018 Sunday 2018w25 2018m6 |
153. | 153 1138 25 6 2018 25jun2018 Monday 2018w26 2018m6 |
154. | 154 435 26 6 2018 26jun2018 Tuesday 2018w26 2018m6 |
155. | 155 516 27 6 2018 27jun2018 Wednesday 2018w26 2018m6 |
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156. | 156 470 28 6 2018 28jun2018 Thursday 2018w26 2018m6 |
157. | 157 479 29 6 2018 29jun2018 Friday 2018w26 2018m6 |
158. | 158 778 30 6 2018 30jun2018 Saturday 2018w26 2018m6 |
159. | 159 641 1 7 2018 01jul2018 Sunday 2018w26 2018m7 |
160. | 160 711 2 7 2018 02jul2018 Monday 2018w27 2018m7 |
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161. | 161 902 3 7 2018 03jul2018 Tuesday 2018w27 2018m7 |
162. | 162 557 4 7 2018 04jul2018 Wednesday 2018w27 2018m7 |
163. | 163 577 5 7 2018 05jul2018 Thursday 2018w27 2018m7 |
164. | 164 475 6 7 2018 06jul2018 Friday 2018w27 2018m7 |
165. | 165 506 7 7 2018 07jul2018 Saturday 2018w27 2018m7 |
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166. | 166 525 8 7 2018 08jul2018 Sunday 2018w27 2018m7 |
167. | 167 455 9 7 2018 09jul2018 Monday 2018w28 2018m7 |
168. | 168 620 10 7 2018 10jul2018 Tuesday 2018w28 2018m7 |
169. | 169 555 11 7 2018 11jul2018 Wednesday 2018w28 2018m7 |
170. | 170 644 12 7 2018 12jul2018 Thursday 2018w28 2018m7 |
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171. | 171 542 13 7 2018 13jul2018 Friday 2018w28 2018m7 |
172. | 172 627 14 7 2018 14jul2018 Saturday 2018w28 2018m7 |
173. | 173 796 15 7 2018 15jul2018 Sunday 2018w28 2018m7 |
174. | 174 636 16 7 2018 16jul2018 Monday 2018w29 2018m7 |
175. | 175 641 17 7 2018 17jul2018 Tuesday 2018w29 2018m7 |
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176. | 176 608 18 7 2018 18jul2018 Wednesday 2018w29 2018m7 |
177. | 177 554 19 7 2018 19jul2018 Thursday 2018w29 2018m7 |
178. | 178 606 20 7 2018 20jul2018 Friday 2018w29 2018m7 |
179. | 179 567 21 7 2018 21jul2018 Saturday 2018w29 2018m7 |
180. | 180 547 22 7 2018 22jul2018 Sunday 2018w29 2018m7 |
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181. | 181 684 23 7 2018 23jul2018 Monday 2018w30 2018m7 |
182. | 182 444 24 7 2018 24jul2018 Tuesday 2018w30 2018m7 |
183. | 183 492 25 7 2018 25jul2018 Wednesday 2018w30 2018m7 |
184. | 184 673 26 7 2018 26jul2018 Thursday 2018w30 2018m7 |
185. | 185 521 27 7 2018 27jul2018 Friday 2018w30 2018m7 |
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186. | 186 418 28 7 2018 28jul2018 Saturday 2018w30 2018m7 |
187. | 187 420 29 7 2018 29jul2018 Sunday 2018w30 2018m7 |
188. | 188 471 30 7 2018 30jul2018 Monday 2018w31 2018m7 |
189. | 189 632 31 7 2018 31jul2018 Tuesday 2018w31 2018m7 |
190. | 190 435 1 8 2018 01aug2018 Wednesday 2018w31 2018m8 |
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191. | 191 376 2 8 2018 02aug2018 Thursday 2018w31 2018m8 |
192. | 192 421 3 8 2018 03aug2018 Friday 2018w31 2018m8 |
193. | 193 695 4 8 2018 04aug2018 Saturday 2018w31 2018m8 |
194. | 194 768 5 8 2018 05aug2018 Sunday 2018w31 2018m8 |
195. | 195 595 6 8 2018 06aug2018 Monday 2018w32 2018m8 |
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196. | 196 610 7 8 2018 07aug2018 Tuesday 2018w32 2018m8 |
197. | 197 647 8 8 2018 08aug2018 Wednesday 2018w32 2018m8 |
198. | 198 471 9 8 2018 09aug2018 Thursday 2018w32 2018m8 |
199. | 199 567 10 8 2018 10aug2018 Friday 2018w32 2018m8 |
200. | 200 517 11 8 2018 11aug2018 Saturday 2018w32 2018m8 |
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201. | 201 587 12 8 2018 12aug2018 Sunday 2018w32 2018m8 |
202. | 202 513 13 8 2018 13aug2018 Monday 2018w33 2018m8 |
203. | 203 565 14 8 2018 14aug2018 Tuesday 2018w33 2018m8 |
204. | 204 626 15 8 2018 15aug2018 Wednesday 2018w33 2018m8 |
205. | 205 470 16 8 2018 16aug2018 Thursday 2018w33 2018m8 |
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206. | 206 451 17 8 2018 17aug2018 Friday 2018w33 2018m8 |
207. | 207 561 18 8 2018 18aug2018 Saturday 2018w33 2018m8 |
208. | 208 432 19 8 2018 19aug2018 Sunday 2018w33 2018m8 |
209. | 209 658 20 8 2018 20aug2018 Monday 2018w34 2018m8 |
210. | 210 600 21 8 2018 21aug2018 Tuesday 2018w34 2018m8 |
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211. | 211 612 22 8 2018 22aug2018 Wednesday 2018w34 2018m8 |
212. | 212 530 23 8 2018 23aug2018 Thursday 2018w34 2018m8 |
213. | 213 528 24 8 2018 24aug2018 Friday 2018w34 2018m8 |
214. | 214 385 25 8 2018 25aug2018 Saturday 2018w34 2018m8 |
215. | 215 476 26 8 2018 26aug2018 Sunday 2018w34 2018m8 |
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216. | 216 457 27 8 2018 27aug2018 Monday 2018w35 2018m8 |
217. | 217 383 28 8 2018 28aug2018 Tuesday 2018w35 2018m8 |
218. | 218 488 29 8 2018 29aug2018 Wednesday 2018w35 2018m8 |
219. | 219 514 30 8 2018 30aug2018 Thursday 2018w35 2018m8 |
220. | 220 379 31 8 2018 31aug2018 Friday 2018w35 2018m8 |
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221. | 221 432 1 9 2018 01sep2018 Saturday 2018w35 2018m9 |
222. | 222 412 2 9 2018 02sep2018 Sunday 2018w35 2018m9 |
223. | 223 536 3 9 2018 03sep2018 Monday 2018w36 2018m9 |
224. | 224 567 4 9 2018 04sep2018 Tuesday 2018w36 2018m9 |
225. | 225 654 5 9 2018 05sep2018 Wednesday 2018w36 2018m9 |
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226. | 226 509 6 9 2018 06sep2018 Thursday 2018w36 2018m9 |
227. | 227 458 7 9 2018 07sep2018 Friday 2018w36 2018m9 |
228. | 228 395 8 9 2018 08sep2018 Saturday 2018w36 2018m9 |
229. | 229 455 9 9 2018 09sep2018 Sunday 2018w36 2018m9 |
230. | 230 472 10 9 2018 10sep2018 Monday 2018w37 2018m9 |
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231. | 231 580 11 9 2018 11sep2018 Tuesday 2018w37 2018m9 |
232. | 232 595 12 9 2018 12sep2018 Wednesday 2018w37 2018m9 |
233. | 233 540 13 9 2018 13sep2018 Thursday 2018w37 2018m9 |
234. | 234 517 14 9 2018 14sep2018 Friday 2018w37 2018m9 |
235. | 235 463 15 9 2018 15sep2018 Saturday 2018w37 2018m9 |
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236. | 236 2463 16 9 2018 16sep2018 Sunday 2018w37 2018m9 |
237. | 237 1862 17 9 2018 17sep2018 Monday 2018w38 2018m9 |
238. | 238 1294 18 9 2018 18sep2018 Tuesday 2018w38 2018m9 |
239. | 239 1268 19 9 2018 19sep2018 Wednesday 2018w38 2018m9 |
240. | 240 846 20 9 2018 20sep2018 Thursday 2018w38 2018m9 |
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241. | 241 807 21 9 2018 21sep2018 Friday 2018w38 2018m9 |
242. | 242 944 22 9 2018 22sep2018 Saturday 2018w38 2018m9 |
243. | 243 804 23 9 2018 23sep2018 Sunday 2018w38 2018m9 |
244. | 244 749 24 9 2018 24sep2018 Monday 2018w39 2018m9 |
245. | 245 596 25 9 2018 25sep2018 Tuesday 2018w39 2018m9 |
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246. | 246 562 26 9 2018 26sep2018 Wednesday 2018w39 2018m9 |
247. | 247 675 27 9 2018 27sep2018 Thursday 2018w39 2018m9 |
248. | 248 518 28 9 2018 28sep2018 Friday 2018w39 2018m9 |
249. | 249 669 29 9 2018 29sep2018 Saturday 2018w39 2018m9 |
250. | 250 619 30 9 2018 30sep2018 Sunday 2018w39 2018m9 |
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251. | 251 509 1 10 2018 01oct2018 Monday 2018w40 2018m10 |
252. | 252 760 2 10 2018 02oct2018 Tuesday 2018w40 2018m10 |
253. | 253 705 3 10 2018 03oct2018 Wednesday 2018w40 2018m10 |
254. | 254 521 4 10 2018 04oct2018 Thursday 2018w40 2018m10 |
255. | 255 513 5 10 2018 05oct2018 Friday 2018w40 2018m10 |
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256. | 256 660 6 10 2018 06oct2018 Saturday 2018w40 2018m10 |
257. | 257 603 7 10 2018 07oct2018 Sunday 2018w40 2018m10 |
258. | 258 678 8 10 2018 08oct2018 Monday 2018w41 2018m10 |
259. | 259 578 9 10 2018 09oct2018 Tuesday 2018w41 2018m10 |
260. | 260 639 10 10 2018 10oct2018 Wednesday 2018w41 2018m10 |
|-------------------------------------------------------------------------------|
261. | 261 616 11 10 2018 11oct2018 Thursday 2018w41 2018m10 |
262. | 262 399 12 10 2018 12oct2018 Friday 2018w41 2018m10 |
263. | 263 460 13 10 2018 13oct2018 Saturday 2018w41 2018m10 |
264. | 264 430 14 10 2018 14oct2018 Sunday 2018w41 2018m10 |
265. | 265 655 15 10 2018 15oct2018 Monday 2018w42 2018m10 |
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266. | 266 626 16 10 2018 16oct2018 Tuesday 2018w42 2018m10 |
267. | 267 732 17 10 2018 17oct2018 Wednesday 2018w42 2018m10 |
268. | 268 774 18 10 2018 18oct2018 Thursday 2018w42 2018m10 |
269. | 269 643 19 10 2018 19oct2018 Friday 2018w42 2018m10 |
270. | 270 538 20 10 2018 20oct2018 Saturday 2018w42 2018m10 |
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271. | 271 853 21 10 2018 21oct2018 Sunday 2018w42 2018m10 |
272. | 272 694 22 10 2018 22oct2018 Monday 2018w43 2018m10 |
273. | 273 674 23 10 2018 23oct2018 Tuesday 2018w43 2018m10 |
274. | 274 759 24 10 2018 24oct2018 Wednesday 2018w43 2018m10 |
275. | 275 553 25 10 2018 25oct2018 Thursday 2018w43 2018m10 |
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276. | 276 424 26 10 2018 26oct2018 Friday 2018w43 2018m10 |
277. | 277 426 27 10 2018 27oct2018 Saturday 2018w43 2018m10 |
278. | 278 415 28 10 2018 28oct2018 Sunday 2018w43 2018m10 |
279. | 279 534 29 10 2018 29oct2018 Monday 2018w44 2018m10 |
280. | 280 529 30 10 2018 30oct2018 Tuesday 2018w44 2018m10 |
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281. | 281 495 31 10 2018 31oct2018 Wednesday 2018w44 2018m10 |
282. | 282 433 1 11 2018 01nov2018 Thursday 2018w44 2018m11 |
283. | 283 454 2 11 2018 02nov2018 Friday 2018w44 2018m11 |
284. | 284 430 3 11 2018 03nov2018 Saturday 2018w44 2018m11 |
285. | 285 464 4 11 2018 04nov2018 Sunday 2018w44 2018m11 |
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286. | 286 562 5 11 2018 05nov2018 Monday 2018w45 2018m11 |
287. | 287 405 6 11 2018 06nov2018 Tuesday 2018w45 2018m11 |
288. | 288 691 7 11 2018 07nov2018 Wednesday 2018w45 2018m11 |
289. | 289 843 8 11 2018 08nov2018 Thursday 2018w45 2018m11 |
290. | 290 536 9 11 2018 09nov2018 Friday 2018w45 2018m11 |
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291. | 291 688 10 11 2018 10nov2018 Saturday 2018w45 2018m11 |
292. | 292 788 11 11 2018 11nov2018 Sunday 2018w45 2018m11 |
293. | 293 591 12 11 2018 12nov2018 Monday 2018w46 2018m11 |
294. | 294 580 13 11 2018 13nov2018 Tuesday 2018w46 2018m11 |
295. | 295 569 14 11 2018 14nov2018 Wednesday 2018w46 2018m11 |
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296. | 296 650 15 11 2018 15nov2018 Thursday 2018w46 2018m11 |
297. | 297 499 16 11 2018 16nov2018 Friday 2018w46 2018m11 |
298. | 298 347 17 11 2018 17nov2018 Saturday 2018w46 2018m11 |
299. | 299 486 18 11 2018 18nov2018 Sunday 2018w46 2018m11 |
300. | 300 898 19 11 2018 19nov2018 Monday 2018w47 2018m11 |
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301. | 301 767 20 11 2018 20nov2018 Tuesday 2018w47 2018m11 |
302. | 302 608 21 11 2018 21nov2018 Wednesday 2018w47 2018m11 |
303. | 303 759 22 11 2018 22nov2018 Thursday 2018w47 2018m11 |
304. | 304 348 23 11 2018 23nov2018 Friday 2018w47 2018m11 |
305. | 305 716 24 11 2018 24nov2018 Saturday 2018w47 2018m11 |
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306. | 306 462 25 11 2018 25nov2018 Sunday 2018w47 2018m11 |
307. | 307 531 26 11 2018 26nov2018 Monday 2018w48 2018m11 |
308. | 308 510 27 11 2018 27nov2018 Tuesday 2018w48 2018m11 |
309. | 309 558 28 11 2018 28nov2018 Wednesday 2018w48 2018m11 |
310. | 310 643 29 11 2018 29nov2018 Thursday 2018w48 2018m11 |
|-------------------------------------------------------------------------------|
311. | 311 554 30 11 2018 30nov2018 Friday 2018w48 2018m11 |
312. | 312 530 1 12 2018 01dec2018 Saturday 2018w48 2018m12 |
313. | 313 424 2 12 2018 02dec2018 Sunday 2018w48 2018m12 |
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Thanks LoyceV for updates last two weeks. I am busy recent days, so I did not update my topic last week. I will do it hours later today.
Abstract (for truncated dataset) 50% of observed days (since 19/02/2018 to 02/12/2018) have its total daily merits below 626 (the median) or higher than 626. Importantly, 50% of observed days have their total daily merits in the range from 521 to 774, which is the interquartile range that ranges from the 25th quartile (Q1) to the 75th quartile (Q3). The minimum and maximum daily merits during the period are 347 and 2463, respectively. Potential outliers are days that have total merits above 1154 or below 142.About medians of merits over days of week, Monday is the highest with 674 merits distributed on Mondays in medians, and Friday is the lowest with the median of Friday merits is 542. There are nearly 24% difference between the medians of Friday and Monday.And, Friday is the only day of week which has median lower than 600.
Updates:1) Daily merits1.1. Full dataset (from 24/1/2018 to 2/12/2018) I dropped days after 2/12/2018 because those days belong to the 2018w49, which has not completed with LoyceV data source). Now, lets' take a look at its basic statistics: During the whole period since the beginning day of merit system, the daily merits has its median is 643, which means that 50% of those observed days have their daily merits above 643, and 50% of them have their daily merits above 643. - The interquartile range (from 25th to 75th quartile): is 530 - 858. It means that 50% of those observed days have daily merits in the range from 530 to 858. In addition, 25% of those days have daily merits below 530 (below the 25h quartile), while 25% of them have daily merits above 858 (above the 75th quartile). - The mean +/- standard deviation: is 880 +/- 952. I don't want to use those statistics due to dramatical biases from outliers. Extremely potential outliers are days have their total daily merits above 1350 or below 38. Detailed calculations presented below: - Below: Q1 -1.5*IQR = 530-(1.5*328) = 38; - or Above: Q3 + 1.5*IQR = 858+(1.5*328) = 1350. - IQR = Q3 - Q1 = 858 - 530 = 328 From now on, I only presented analytical results for truncated dataset. What is truncated dataset? It is the dataset, after truncating / dropping all days before 19/02/2018, which are extremely outliers. . list id date week month merit if merit > 1350 & merit != .
+--------------------------------------------+
| id date week month merit |
|--------------------------------------------|
1. | 1 24jan2018 2018w4 2018m1 13018 |
2. | 2 25jan2018 2018w4 2018m1 6761 |
3. | 3 26jan2018 2018w4 2018m1 4493 |
4. | 4 27jan2018 2018w4 2018m1 3489 |
5. | 5 28jan2018 2018w4 2018m1 3188 |
|--------------------------------------------|
6. | 6 29jan2018 2018w5 2018m1 3799 |
7. | 7 30jan2018 2018w5 2018m1 4192 |
8. | 8 31jan2018 2018w5 2018m1 2820 |
9. | 9 01feb2018 2018w5 2018m2 2545 |
10. | 10 02feb2018 2018w5 2018m2 2568 |
|--------------------------------------------|
11. | 11 03feb2018 2018w5 2018m2 1867 |
12. | 12 04feb2018 2018w5 2018m2 2167 |
13. | 13 05feb2018 2018w6 2018m2 2077 |
14. | 14 06feb2018 2018w6 2018m2 2308 |
15. | 15 07feb2018 2018w6 2018m2 2141 |
|--------------------------------------------|
16. | 16 08feb2018 2018w6 2018m2 2141 |
17. | 17 09feb2018 2018w6 2018m2 1448 |
18. | 18 10feb2018 2018w6 2018m2 1747 |
19. | 19 11feb2018 2018w6 2018m2 1442 |
21. | 21 13feb2018 2018w7 2018m2 1579 |
|--------------------------------------------|
22. | 22 14feb2018 2018w7 2018m2 2513 |
23. | 23 15feb2018 2018w7 2018m2 1991 |
24. | 24 16feb2018 2018w7 2018m2 1411 |
25. | 25 17feb2018 2018w7 2018m2 1608 |
27. | 27 19feb2018 2018w8 2018m2 1403 |
|--------------------------------------------|
32. | 32 24feb2018 2018w8 2018m2 1409 |
34. | 34 26feb2018 2018w9 2018m2 1382 |
38. | 38 02mar2018 2018w9 2018m3 1696 |
48. | 48 12mar2018 2018w11 2018m3 1354 |
236. | 236 16sep2018 2018w37 2018m9 2463 |
|--------------------------------------------|
237. | 237 17sep2018 2018w38 2018m9 1862 |
+--------------------------------------------+
As you can easily see that there are some days listed as extremely outliers after 19th Feb. 2018, but I left them in the dataset, not truncated them, in order to have full weeks in truncated dataset. - Median: 626 - Interquartile range: 521 - 774 - Mean +/- standard deviation: 695 +/- 268 - Extremely potential outliers: above 1154 or below 142. With IQR = 774 - 521 = 253 Q1 - 1.5*IQR = 521 - 1.5*253 = 141.5 ~ 142 Q3 + 1.5*IQR = 774 + 1.5*253 = 1153.5 ~ 1154. Box plotsa) Box plot of daily merits since 19th February 2018 to 2nd December 2018.Merit after presents statistics of the whole period from 19/2/2018 to 2/12/2018. w26 presents statistics of the period that started on 19/2/2018 to the end of the week26 (on 01/7/2018) b) Box plot of daily merit (full dataset). This one is only for reference.
Merits over days of weekRaw statisticsSummary for variables: merit
by categories of: dofw
dofw | N mean sd p50 p25 p75 min max
----------+--------------------------------------------------------------------------------
Sunday | 41.0 715.7 360.5 603.0 476.0 829.0 412.0 2463.0
Monday | 41.0 771.3 314.1 674.0 562.0 884.0 455.0 1862.0
Tuesday | 41.0 715.0 246.1 632.0 580.0 767.0 383.0 1326.0
Wednesday | 41.0 723.5 227.1 652.0 562.0 761.0 435.0 1268.0
Thursday | 41.0 687.0 220.7 644.0 528.0 774.0 376.0 1333.0
Friday | 41.0 611.7 238.0 542.0 463.0 698.0 348.0 1696.0
Saturday | 41.0 639.5 223.3 614.0 463.0 688.0 347.0 1409.0
----------+--------------------------------------------------------------------------------
Total | 287.0 694.8 268.1 626.0 521.0 774.0 347.0 2463.0
-------------------------------------------------------------------------------------------
What we got here? The days of week that have lowest and highest means of totally merits are Friday and Wednesday, at 612 and 724 merits distributed, respectively. It means there are (724 - 612) = 212 merit difference or the Wednesday have nearly 18% total merits higher than the Friday. Personally, it is a dramatical difference. . di (724-612)*100/612
18.300654
Now, how about median difference? The days of week that have lowest and highest medians of totally merits are Friday and Monday, at 542 and 674, respectively. It means that there are (674-542) = 132 merit points diference between the Friday and Monday. In other words, there are nearly 24% difference between the medians of Friday and Monday.. di (674-542)*100/542
24.354244
a) Outliers displayed. b) Outliers non-displayed. Statistics of full dataset (just for reference) Summary for variables: merit
by categories of: dofw
dofw | N mean sd p50 p25 p75 min max
----------+--------------------------------------------------------------------------------
Sunday | 45.0 831.8 557.3 619.0 486.0 880.0 412.0 3188.0
Monday | 44.0 882.5 582.4 681.0 575.5 945.0 455.0 3799.0
Tuesday | 44.0 849.9 628.7 638.5 580.0 890.5 383.0 4192.0
Wednesday | 45.0 1114.5 1882.6 681.0 569.0 963.0 435.0 13018.0
Thursday | 45.0 924.5 995.1 673.0 530.0 846.0 376.0 6761.0
Friday | 45.0 777.7 695.0 554.0 475.0 774.0 348.0 4493.0
Saturday | 45.0 776.2 542.4 627.0 506.0 778.0 347.0 3489.0
----------+--------------------------------------------------------------------------------
Total | 313.0 879.7 951.8 643.0 530.0 858.0 347.0 13018.0
-------------------------------------------------------------------------------------------
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It does not make sense to send sMerits to banned accounts, especially permanent banned accounts. They don't need them, and probably don't deserve merits due to their serious violations on forum rules. or even banned status.
But, you maybe right at this point. All this does not in any way reduce the quality of a post or the impact and usefulness it has on others.
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You are right at this point. Users have their own rights and decisions to use their sMerits, holding them forever (till Theymos decide decaying un-used sMerits) or sending them to any one, any topic, any thread they agree with and think that those ones are merit-deserved.
And, @satoshi is one of the most prestigious guys in crypto world. He/she/they obviously deserve/s tons of merits. People paying respect to Satoshi is not wasting of merit.
It's only an assumption, which might happen or not. Personally, I think we should stick on current situation, rules, systems, etc. of the forum in our discussion. Keep in mind that theymos can generate infinite amount of smerit.
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< ... >
Hate to say this, but honestly I don't want to read threads with pyramid quotes, like yours. Pyramid quotes require huge space of each page, and make the whole page looks very uncomfortable. Next time, you should drop unnecessary texts, and only quote specific points at which you want to discuss. Additionally, it's too bad to see pyramid quotes in Meta board. |
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Welcome, vit05 answered it, but I want to give you more detailed steps. This one might helpful for your interests. Guideline on posting images, hyperlinks (by tbct_mt2)In a nutshell, in order to post videos inside your posts. There is only one way, by posting link to videsos inside image, like this: [img][url=video's hyperlink] attached image's link[/url][/img] Remember that you have to put outside the , not instead [url=http://][img][/img][/url] Additionally, you can adjust image size by using the option width=interest size, like this [img width=interest size]http://[/img] Or, centering images with the option in order to make a better appaerance of your posts. [center][img][/img][/center] Doing this, others have to click on attached images to visit videos' links and watch them.
Why? Simply leaving a short note below the image, then everyone will know it is link to video and they have to click on the range to watch it. Simply posting the link to the video might be better, so no one unknowingly clicks on the link.
You should also include additional descriptions as it's leading people away from the bitcointalk landing page.
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I made some initiatives recent weeks, so I hope that the OP author will take a look at it. Thanks in advance for your time to glance at them all. |
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