Time series plot
Dataset for median, interquartile range of intraday merits
Code:
+------------------------------------------+
| week median q1 q3 merit |
|------------------------------------------|
1. | 2018w26 733 609 991 4465 |
2. | 2018w27 715 598 979 4278 |
3. | 2018w28 707 592 963 4247 |
4. | 2018w29 693 589 922 4167 |
5. | 2018w30 684 577 902 3661 |
|------------------------------------------|
6. | 2018w31 682 575 891 3863 |
7. | 2018w32 675 567 880 4011 |
8. | 2018w33 667 559 867 3631 |
9. | 2018w34 652 555 848 3805 |
10. | 2018w35 642 537 844 3072 |
|------------------------------------------|
11. | 2018w36 639 528 838 3590 |
12. | 2018w37 634 528 829 5644 |
13. | 2018w38 641 530 846 7837 |
14. | 2018w39 640 531 839 4395 |
15. | 2018w40 639 528 829 4310 |
|------------------------------------------|
16. | 2018w41 637 528 808 3816 |
17. | 2018w42 639 530 807 4829 |
18. | 2018w43 639 528 801 3953 |
19. | 2018w44 628 521 796 3347 |
20. | 2018w45 630 522 789 4525 |
|------------------------------------------|
21. | 2018w46 628 523 788 3747 |
22. | 2018w47 628 522.5 783.5 4575 |
23. | 2018w48 627 522 778 3765 |
24. | 2018w49 623.5 520 775 3571 |
25. | 2018w50 622 520 774 3805 |
|------------------------------------------|
26. | 2018w51 621.5 517.5 770 3769 |
27. | 2018w52 617.5 514 764 3338 |
28. | 2019w1 617 514 769 4803 |
29. | 2019w2 621.5 515 775 6632 |
30. | 2019w3 623 517 777 5317 |
|------------------------------------------|
31. | 2019w4 623.5 518.5 775 4667 |
32. | 2019w5 622 518 775 4491 |
33. | 2019w6 622 520 775 4332 |
34. | 2019w7 621 522 771 4221 |
35. | 2019w8 621.5 521 770 4521 |
|------------------------------------------|
36. | 2019w9 622 520 769 4638 |
37. | 2019w10 624 522 766 4913 |
38. | 2019w11 624 522 762 4326 |
39. | 2019w12 626.5 523 761 4609 |
40. | 2019w13 628 525 766 6130 |
|------------------------------------------|
41. | 2019w14 627.5 529 761 4526 |
42. | 2019w15 629 530 762 5271 |
43. | 2019w16 632.5 530.5 764 4688 |
44. | 2019w17 629 530 762 4448 |
45. | 2019w18 629 531 762 4764 |
|------------------------------------------|
46. | 2019w19 636 532 762 5454 |
47. | 2019w20 638.5 532.5 767.5 5214 |
48. | 2019w21 639 533 766 4580 |
49. | 2019w22 639 535 761 4445 |
50. | 2019w23 639 535 761 4687 |
|------------------------------------------|
51. | 2019w24 640 536 764 5354 |
52. | 2019w25 640 537 762 4726 |
53. | 2019w26 640 535 762 4367 |
54. | 2019w27 640 535 761 4225 |
55. | 2019w28 639 532.5 761 4119 |
|------------------------------------------|
56. | 2019w29 639 532 761 4277 |
57. | 2019w30 636.5 533 760 4176 |
58. | 2019w31 629 532 760 3549 |
59. | 2019w32 628 530 757 3207 |
60. | 2019w33 628 530 755 4236 |
|------------------------------------------|
61. | 2019w34 627 529 752 3622 |
62. | 2019w35 627 528 750 3540 |
63. | 2019w36 625.5 526.5 742 3809 |
64. | 2019w37 625 525 742 4043 |
65. | 2019w38 624 528 738 4520 |
|------------------------------------------|
66. | 2019w39 624 528 737 4318 |
67. | 2019w40 624 525 737 4357 |
68. | 2019w41 624 525 737 4565 |
69. | 2019w42 626 528 742 5542 |
70. | 2019w43 627 529 742 4975 |
|------------------------------------------|
71. | 2019w44 627 530 740 4730 |
72. | 2019w45 627 530 742 4735 |
73. | 2019w46 628 531 751 14251 |
74. | 2019w47 629 532 759 17685 |
75. | 2019w48 631.5 532.5 760 5907 |
|------------------------------------------|
76. | 2019w49 629 534 760 4524 |
List of median, q1, q3 of intra-day merits over weeks, in descending orders of medians.
Code:
+------------------------------------------+
| week median q1 q3 merit |
|------------------------------------------|
1. | 2019w1 617 514 769 4803 |
2. | 2018w52 617.5 514 764 3338 |
3. | 2019w7 621 522 771 4221 |
4. | 2019w2 621.5 515 775 6632 |
5. | 2019w8 621.5 521 770 4521 |
|------------------------------------------|
6. | 2018w51 621.5 517.5 770 3769 |
7. | 2018w50 622 520 774 3805 |
8. | 2019w6 622 520 775 4332 |
9. | 2019w9 622 520 769 4638 |
10. | 2019w5 622 518 775 4491 |
|------------------------------------------|
11. | 2019w3 623 517 777 5317 |
12. | 2018w49 623.5 520 775 3571 |
13. | 2019w4 623.5 518.5 775 4667 |
14. | 2019w41 624 525 737 4565 |
15. | 2019w11 624 522 762 4326 |
|------------------------------------------|
16. | 2019w39 624 528 737 4318 |
17. | 2019w38 624 528 738 4520 |
18. | 2019w10 624 522 766 4913 |
19. | 2019w40 624 525 737 4357 |
20. | 2019w37 625 525 742 4043 |
|------------------------------------------|
21. | 2019w36 625.5 526.5 742 3809 |
22. | 2019w42 626 528 742 5542 |
23. | 2019w12 626.5 523 761 4609 |
24. | 2019w44 627 530 740 4730 |
25. | 2019w34 627 529 752 3622 |
|------------------------------------------|
26. | 2019w43 627 529 742 4975 |
27. | 2018w48 627 522 778 3765 |
28. | 2019w35 627 528 750 3540 |
29. | 2019w45 627 530 742 4735 |
30. | 2019w14 627.5 529 761 4526 |
|------------------------------------------|
31. | 2018w44 628 521 796 3347 |
32. | 2019w13 628 525 766 6130 |
33. | 2019w32 628 530 757 3207 |
34. | 2018w46 628 523 788 3747 |
35. | 2019w46 628 531 751 14251 |
|------------------------------------------|
36. | 2018w47 628 522.5 783.5 4575 |
37. | 2019w33 628 530 755 4236 |
38. | 2019w17 629 530 762 4448 |
39. | 2019w31 629 532 760 3549 |
40. | 2019w49 629 534 760 4524 |
|------------------------------------------|
41. | 2019w47 629 532 759 17685 |
42. | 2019w15 629 530 762 5271 |
43. | 2019w18 629 531 762 4764 |
44. | 2018w45 630 522 789 4525 |
45. | 2019w48 631.5 532.5 760 5907 |
|------------------------------------------|
46. | 2019w16 632.5 530.5 764 4688 |
47. | 2018w37 634 528 829 5644 |
48. | 2019w19 636 532 762 5454 |
49. | 2019w30 636.5 533 760 4176 |
50. | 2018w41 637 528 808 3816 |
|------------------------------------------|
51. | 2019w20 638.5 532.5 767.5 5214 |
52. | 2018w43 639 528 801 3953 |
53. | 2018w40 639 528 829 4310 |
54. | 2018w36 639 528 838 3590 |
55. | 2019w21 639 533 766 4580 |
|------------------------------------------|
56. | 2019w29 639 532 761 4277 |
57. | 2019w28 639 532.5 761 4119 |
58. | 2019w22 639 535 761 4445 |
59. | 2019w23 639 535 761 4687 |
60. | 2018w42 639 530 807 4829 |
|------------------------------------------|
61. | 2019w26 640 535 762 4367 |
62. | 2019w24 640 536 764 5354 |
63. | 2019w27 640 535 761 4225 |
64. | 2019w25 640 537 762 4726 |
65. | 2018w39 640 531 839 4395 |
|------------------------------------------|
66. | 2018w38 641 530 846 7837 |
67. | 2018w35 642 537 844 3072 |
68. | 2018w34 652 555 848 3805 |
69. | 2018w33 667 559 867 3631 |
70. | 2018w32 675 567 880 4011 |
|------------------------------------------|
71. | 2018w31 682 575 891 3863 |
72. | 2018w30 684 577 902 3661 |
73. | 2018w29 693 589 922 4167 |
74. | 2018w28 707 592 963 4247 |
75. | 2018w27 715 598 979 4278 |
|------------------------------------------|
76. | 2018w26 733 609 991 4465 |
Now, let's take a look at the variations of intra-day medians over weeks.
Method:
I took medians of intraday merits over weeks (since 2018w46, from id 293 - 299, here). The median of intraday merits at the end of 2018w46 will be calculated from intraday merits started from days with id #26 - # 299; days before id #26 truncated due to extremely outliers.
For later weeks, just moving forwards with each 7-day-time-frame to calculate next medians of intradays over weeks.
For later weeks, just moving forwards with each 7-day-time-frame to calculate next medians of intradays over weeks.
Results:
Since 2018w48 to 2019w49, the dataset has:
- 73 weeks in total.
- Median of median of intraday merits over weeks is 628.
- Interquartile range of median of median of intraday merits over weeks ranges from 624 to 639.
Code:
. tabstat median, s(n mean sd p50 p25 p75 min max) format(%9.1f)
variable | N mean sd p50 p25 p75 min max
-------------+--------------------------------------------------------------------------------
median | 73.0 633.5 14.8 628.0 624.0 639.0 617.0 693.0
----------------------------------------------------------------------------------------------
Data source:
- From LoyceV's weekly data dumps.
- From my converted datasets in the topic: Time Series Analysis on Distributed Merits in the forum (daily, weekly, monthly)
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