National Panel Survey 2014-2015, Wave 4
Tanzania, 2014 - 2015
Get Microdata
Reference ID
TZA_2014_NPS-R4_v03_M
Producer(s)
National Bureau of Statistics
Created on
Oct 10, 2017
Last modified
Oct 10, 2017
Page views
41714
Downloads
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- Data files
- ag_filters
- ag_network
- ag_sec_01
- ag_sec_2a
- ag_sec_2b
- ag_sec_3a
- ag_sec_3b
- ag_sec_4a
- ag_sec_4b
- ag_sec_5a
- ag_sec_5b
- ag_sec_6a
- ag_sec_6b
- ag_sec_7a
- ag_sec_7b
- ag_sec_10
- ag_sec_11
- ag_sec_12a
- ag_sec_12b
- ag_sec_a
- hh_filters
- hh_sec_a
- hh_sec_b
- hh_sec_c
- hh_sec_d
- hh_sec_e
- hh_sec_f
- hh_sec_g
- hh_sec_h
- hh_sec_i
- hh_sec_j1
- hh_sec_j3
- hh_sec_j4
- hh_sec_k
- hh_sec_l
- hh_sec_m
- hh_sec_n
- hh_sec_o1
- hh_sec_o2
- hh_sec_p
- hh_sec_q1
- hh_sec_q2
- hh_sec_r
- hh_sec_s
- hh_sec_u2
- hh_sec_v
- lf_filters
- lf_network
- lf_sec_01
- lf_sec_02
- lf_sec_03
- lf_sec_04
- lf_sec_05
- lf_sec_06
- lf_sec_07
- lf_sec_08
- lf_sec_09
- lf_sec_11a
- lf_sec_11b
- lf_sec_12
- lf_sec_13a
- lf_sec_13b
- lf_sec_a
- npsy4.child.anthro
- npsy4.ea.offset
- LF_SEC_10
- com_sec_a1a2
- com_sec_cb
- com_sec_cc
- com_sec_cd
- com_sec_ce
- com_sec_cf
- com_sec_cf_id
- com_sec_cg
- consumptionNPS4
PLEASE LIST ALL PLOTS CULTIVATED DURING THE LAST 12 MONTHS. (ag6a_01)
Data file: ag_sec_6a
Overview
Valid:
3302
Invalid:
0
Type:
Discrete
Start:
17
End:
30
Width:
14
Range:
-
Format:
character
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| APPLE | 3 |
0.1%
|
|
| BUTUNDA | 1 |
0%
|
|
| ELIMU | 1 |
0%
|
|
| EMBE | 733 |
22.2%
|
|
| EMBE NG'ONGO | 4 |
0.1%
|
|
| FENESI | 63 |
1.9%
|
|
| FURSADI | 1 |
0%
|
|
| FURU | 1 |
0%
|
|
| HAKUNA | 1 |
0%
|
|
| KOMAMANGA | 10 |
0.3%
|
|
| LIMAO | 16 |
0.5%
|
|
| LIMAU | 9 |
0.3%
|
|
| MACHUNGWA | 227 |
6.9%
|
|
| MADALANZI | 1 |
0%
|
|
| MAFYOKS | 18 |
0.5%
|
|
| MAFYURISI | 1 |
0%
|
|
| MAGOGWE | 2 |
0.1%
|
|
| MALIMAO | 5 |
0.2%
|
|
| MALIMAU | 1 |
0%
|
|
| MAPESHENI | 40 |
1.2%
|
|
| MAPINIGES | 1 |
0%
|
|
| MASHELISHELI | 2 |
0.1%
|
|
| MASTAFELI | 9 |
0.3%
|
|
| MATHOMAS | 1 |
0%
|
|
| MATOFAA | 1 |
0%
|
|
| MATOMASI | 3 |
0.1%
|
|
| MATOPETOPE | 2 |
0.1%
|
|
| MATUNDA DAMU | 20 |
0.6%
|
|
| MATUNDA MUNGU | 1 |
0%
|
|
| MATUNDA NYANYA | 1 |
0%
|
|
| MATUNDADAMU | 1 |
0%
|
|
| MAZAMBARAU | 1 |
0%
|
|
| MBILIMBI | 3 |
0.1%
|
|
| MBIRIMBI | 1 |
0%
|
|
| MBUYU | 1 |
0%
|
|
| MCHENZA | 61 |
1.8%
|
|
| MDIMU | 6 |
0.2%
|
|
| MFULUSAJI | 1 |
0%
|
|
| MIDIM | 1 |
0%
|
|
| MIDIMU | 2 |
0.1%
|
|
| MIEMBE | 2 |
0.1%
|
|
| MIEMBENI | 1 |
0%
|
|
| MIGOMBA | 703 |
21.3%
|
|
| MIKARANGA | 1 |
0%
|
|
| MILIMAO | 16 |
0.5%
|
|
| MILIMAU | 15 |
0.5%
|
|
| MIPAPAI | 2 |
0.1%
|
|
| MIPERA | 1 |
0%
|
|
| MIPINIGESI | 1 |
0%
|
|
| MISHELISHELI | 1 |
0%
|
|
| MISHOKISHOKI | 1 |
0%
|
|
| MISITAFELI | 1 |
0%
|
|
| MISTAFELI | 7 |
0.2%
|
|
| MITI YA MBAO | 1 |
0%
|
|
| MITOPETOPE | 3 |
0.1%
|
|
| MKOMAMANGA | 2 |
0.1%
|
|
| MKWAJU | 1 |
0%
|
|
| MLIMAO | 27 |
0.8%
|
|
| MLIMAO (LIMAO) | 2 |
0.1%
|
|
| MLIMAU | 38 |
1.2%
|
|
| MNDIMU | 5 |
0.2%
|
|
| MSAMBIA | 6 |
0.2%
|
|
| MSTAFELI | 12 |
0.4%
|
|
| MTOMASI | 1 |
0%
|
|
| MTONGA | 1 |
0%
|
|
| MTOPETOPE | 2 |
0.1%
|
|
| MTORONGONI | 1 |
0%
|
|
| MZAMBARAO | 2 |
0.1%
|
|
| MZAMBARAU | 6 |
0.2%
|
|
| NANASI | 78 |
2.4%
|
|
| NAZI | 2 |
0.1%
|
|
| NDIMU | 5 |
0.2%
|
|
| NDIZI | 197 |
6%
|
|
| NYAMBWITA | 2 |
0.1%
|
|
| PALALI | 1 |
0%
|
|
| PAPAI | 326 |
9.9%
|
|
| PARACHICHI | 309 |
9.4%
|
|
| PEACHES | 1 |
0%
|
|
| PEASI | 11 |
0.3%
|
|
| PERA | 153 |
4.6%
|
|
| PICHES | 18 |
0.5%
|
|
| PICHEZI | 1 |
0%
|
|
| PINDICASE | 1 |
0%
|
|
| PINGAS | 1 |
0%
|
|
| PINGASES | 1 |
0%
|
|
| PINGESI | 1 |
0%
|
|
| PINIGES | 1 |
0%
|
|
| PINIGESI | 3 |
0.1%
|
|
| PITCHES | 2 |
0.1%
|
|
| SAMBIA | 2 |
0.1%
|
|
| SHARAZI | 1 |
0%
|
|
| SHOKISHOKI | 1 |
0%
|
|
| STAFELI | 15 |
0.5%
|
|
| SUNGWI | 1 |
0%
|
|
| TENDE | 2 |
0.1%
|
|
| TOPE TOPE | 2 |
0.1%
|
|
| TOPETOPE | 28 |
0.8%
|
|
| UKWAJU | 1 |
0%
|
|
| VANILA | 1 |
0%
|
|
| VINYAMBWITA | 1 |
0%
|
|
| ZABIBU | 2 |
0.1%
|
|
| ZAITUNI PORI | 1 |
0%
|
|
| ZAMBARAO | 1 |
0%
|
|
| ZAMBARAU | 10 |
0.3%
|
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.