Education Quality Improvement Programme Impact Evaluation Midline Survey 2016
Tanzania, 2016
Get MicrodataCreated on
Jun 26, 2017
Last modified
Sep 07, 2022
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- Data files
- ml_v2_1_school
- ml_v2_1_teacher
- ml_v2_1_lesson
- ml_v2_2_pupil
s04 q12: Specified local or foreign language teacher uses when teaching (t_ml_teachlangspec)
Data file: ml_v2_1_teacher
Overview
Valid:
0
Invalid:
2903
Type:
Discrete
Decimal:
0
Start:
1411
End:
1414
Width:
4
Range:
-9 - 1003
Format:
Numeric
Questions and instructions
Categories
| Value | Category |
|---|---|
| -9 | Missing |
| -8 | Missing due to a mistake in CAPI enabling rule that was later fixed |
| -7 | Missing due to late addition of question |
| -6 | No record kept/Record not available/Attendance not taken |
| -5 | Not available |
| -4 | No response |
| -3 | Not applicable |
| -2 | Don't know |
| -1 | Refused |
| 1 | Alagwa |
| 2 | Akiek |
| 3 | Arusha |
| 4 | Assa |
| 5 | Barabaig |
| 6 | Bembe |
| 7 | Bena |
| 8 | Bende |
| 9 | Bondei |
| 10 | Bungu |
| 11 | Burunge |
| 12 | Chagga |
| 13 | Datoga |
| 14 | Dhaiso |
| 15 | Digo |
| 16 | Doe |
| 17 | Fipa |
| 18 | Gogo |
| 19 | Gorowa |
| 20 | Gweno |
| 21 | Ha |
| 22 | Hadzabe |
| 23 | Hangaza |
| 24 | Haya |
| 25 | Hehe |
| 26 | Ikizu |
| 27 | Ikoma |
| 28 | Iraqw |
| 29 | Isanzu |
| 30 | Jiji |
| 31 | Jita |
| 32 | Kabwa |
| 33 | Kaguru |
| 34 | Kahe |
| 35 | Kami |
| 36 | Kara (Regi) |
| 37 | Kerewe |
| 38 | Kimbu |
| 39 | Kinga |
| 40 | Kisankasa |
| 41 | Kisi |
| 42 | Konongo |
| 43 | Kuria |
| 44 | Kutu |
| 45 | Kw'adza |
| 46 | Kwavi |
| 47 | Kwaya |
| 48 | Kwere |
| 49 | Kwifa |
| 50 | Lambya |
| 51 | Luguru |
| 52 | Luo |
| 53 | Maasai |
| 54 | Machinga |
| 55 | Magoma |
| 56 | Makonde |
| 57 | Makua |
| 58 | Makwe |
| 59 | Malila |
| 60 | Mambwe |
| 61 | Manda |
| 62 | Matengo |
| 63 | Matumbi |
| 64 | Mawiha |
| 65 | Mbugwe |
| 66 | Mbunga |
| 67 | Mosiro |
| 68 | Mpoto |
| 69 | Mwanga |
| 70 | Mwera |
| 71 | Ndali |
| 72 | Ndamba |
| 73 | Ndendeule |
| 74 | Ndengereko |
| 75 | Ndonde |
| 76 | Ngasa |
| 77 | Ngindo |
| 78 | Ngoni |
| 79 | Ngulu |
| 80 | Ngurimi |
| 81 | Ngwele |
| 82 | Nilamba |
| 83 | Nindi |
| 84 | Nyakyusa |
| 85 | Nyambo |
| 86 | Nyamwanga |
| 87 | Nyamwezi |
| 88 | Nyanyembe |
| 89 | Nyaturu |
| 90 | Nyiha |
| 91 | Nyiramba |
| 92 | Pangwa |
| 93 | Pare |
| 94 | Pimbwe |
| 95 | Pogolo |
| 96 | Rangi |
| 97 | Rufiji |
| 98 | Rungi |
| 99 | Rungu |
| 100 | Rungwa |
| 101 | Rwa |
| 102 | Safwa |
| 103 | Sagara |
| 104 | Sandawe |
| 105 | Sangu |
| 106 | Segeju |
| 107 | Shambaa |
| 108 | Shubi |
| 109 | Sizaki |
| 110 | Subi |
| 111 | Sukuma |
| 112 | Sumbwa |
| 114 | Temi |
| 115 | Tongwe |
| 116 | Tumbuka |
| 117 | Vidunda |
| 118 | Vinza |
| 119 | Wanda |
| 120 | Wanji |
| 121 | Ware |
| 122 | Yao |
| 123 | Zanaki |
| 124 | Zaramo |
| 125 | Zigua |
| 126 | Zinza |
| 127 | Zyoba |
| 996 | Other (specify) |
| 1001 | English |
| 1002 | Hindi |
| 1003 | Portugese |
| Sysmiss |
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.