High Frequency Survey: Wave 4 and Crisis Recovery Survey 2017
South Sudan, 2017
Get Microdata
Reference ID
WBG_SSD_2017_HFS-W4-CRS_v01_M
Producer(s)
South Sudan National Bureau of Statistics
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Metadata
Created on
Sep 22, 2021
Last modified
Sep 22, 2021
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- Data files
- assets
- food
- hhm
- hhm_analysis
- hhm_separated
- livestock
- mi-extract
- nonfood
- hhq_analysis
B.19 Which tribe does %hhh_name% belong to? (hhh_tribe)
Data file: hhm_analysis
Overview
Valid:
3180
Invalid:
54364
Minimum:
1
Maximum:
1000
Type:
Discrete
Decimal:
0
Start:
126
End:
130
Width:
5
Range:
-99 - 1000
Format:
Numeric
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| -99 | Refuse to answer | 0 |
0%
|
| -98 | Don't know | 0 |
0%
|
| 1 | Acholi | 21 |
0.7%
|
| 2 | Aja | 0 |
0%
|
| 3 | Anuak, Anyuak | 1 |
0%
|
| 4 | Atuot | 0 |
0%
|
| 5 | Atwot, Atuot | 0 |
0%
|
| 6 | Avukaya | 8 |
0.3%
|
| 7 | Azande, Zande | 167 |
5.3%
|
| 8 | Bai | 20 |
0.6%
|
| 9 | Baka | 12 |
0.4%
|
| 10 | Balanda Bor | 62 |
1.9%
|
| 11 | Balanda Viri | 190 |
6%
|
| 12 | Bari | 9 |
0.3%
|
| 13 | Binga | 5 |
0.2%
|
| 14 | Bongo | 27 |
0.8%
|
| 15 | Boya | 1 |
0%
|
| 16 | Burun | 0 |
0%
|
| 17 | Bviri | 0 |
0%
|
| 18 | Didinga | 4 |
0.1%
|
| 19 | Dinka, Jieeng, Muonyjang | 328 |
10.3%
|
| 20 | Dongotono, Dongotona | 9 |
0.3%
|
| 21 | Donyiro | 0 |
0%
|
| 22 | Dukpu | 14 |
0.4%
|
| 23 | Feroghe | 13 |
0.4%
|
| 24 | Fertit | 8 |
0.3%
|
| 25 | Gollo | 40 |
1.3%
|
| 26 | Ifoto | 2 |
0.1%
|
| 27 | Imatong | 1 |
0%
|
| 28 | Indri | 6 |
0.2%
|
| 29 | Jiye | 0 |
0%
|
| 30 | Jur Beli, Jurbiel, Bel | 8 |
0.3%
|
| 31 | Jur Manager | 2 |
0.1%
|
| 32 | Jur Modo | 3 |
0.1%
|
| 33 | Jurchol, Jo-Luo, Jur Chol | 36 |
1.1%
|
| 34 | Kachipo, Kichepo | 0 |
0%
|
| 35 | Kakowa | 6 |
0.2%
|
| 36 | Kakwa | 25 |
0.8%
|
| 37 | Kaliko | 2 |
0.1%
|
| 38 | Kara | 3 |
0.1%
|
| 39 | Ketebo | 1 |
0%
|
| 40 | Kresh | 61 |
1.9%
|
| 41 | Kuku | 5 |
0.2%
|
| 42 | Lango | 5 |
0.2%
|
| 43 | Larim | 0 |
0%
|
| 44 | Laro | 0 |
0%
|
| 45 | Logir | 0 |
0%
|
| 46 | Logo | 0 |
0%
|
| 47 | Lokoja | 0 |
0%
|
| 48 | Lokoya | 10 |
0.3%
|
| 49 | Lopid | 1 |
0%
|
| 50 | Lopit | 5 |
0.2%
|
| 51 | Lotuko, Lotuka | 42 |
1.3%
|
| 52 | Lugbwara | 0 |
0%
|
| 53 | Lulubo | 2 |
0.1%
|
| 54 | Luo | 12 |
0.4%
|
| 55 | Maban | 1 |
0%
|
| 56 | Madi | 16 |
0.5%
|
| 57 | Makaraka | 1 |
0%
|
| 58 | Mangaya | 5 |
0.2%
|
| 59 | Mangayat | 0 |
0%
|
| 60 | Moro Nuba | 3 |
0.1%
|
| 62 | Moru, Moro | 22 |
0.7%
|
| 63 | Mundari | 25 |
0.8%
|
| 65 | Mundu | 4 |
0.1%
|
| 66 | Murle | 1 |
0%
|
| 67 | Narim, Longarim | 0 |
0%
|
| 68 | Ndogo | 38 |
1.2%
|
| 69 | Ngulgule | 1 |
0%
|
| 70 | Nuer, Naath | 1736 |
54.6%
|
| 71 | Nyamusa | 2 |
0.1%
|
| 72 | Nyangatom | 0 |
0%
|
| 73 | Nyangwara | 1 |
0%
|
| 74 | Nyepu | 0 |
0%
|
| 75 | Olubo | 0 |
0%
|
| 76 | Pari, Paeri | 7 |
0.2%
|
| 78 | Pojulu | 11 |
0.3%
|
| 79 | Rek | 0 |
0%
|
| 80 | Sebei | 0 |
0%
|
| 81 | Sere | 1 |
0%
|
| 82 | Shatt | 7 |
0.2%
|
| 83 | Shilluk, Chollo, Collo | 21 |
0.7%
|
| 84 | Shita | 0 |
0%
|
| 85 | Shwai | 0 |
0%
|
| 86 | Tacho | 0 |
0%
|
| 87 | Tenet | 0 |
0%
|
| 88 | Thuri | 1 |
0%
|
| 89 | Tid, Teuth | 0 |
0%
|
| 90 | Toposa | 21 |
0.7%
|
| 91 | Uduk | 0 |
0%
|
| 92 | Vidiri | 1 |
0%
|
| 93 | Welega, Wallega | 0 |
0%
|
| 94 | Woro | 1 |
0%
|
| 95 | Yulu | 14 |
0.4%
|
| 96 | Arabic | 7 |
0.2%
|
| 97 | Falata | 12 |
0.4%
|
| 98 | Nuba | 3 |
0.1%
|
| 1000 | Other (please specify) | 40 |
1.3%
|
| 10001 | .Z | 13249 | |
| Sysmiss | 41115 |
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.