Migration Survey 2019
Senegal, 2019
Get MicrodataCreated on
Jan 16, 2021
Last modified
Jan 16, 2021
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- Data files
-
base
comunautaire_public.dta - Section0_public.dta
- Section1_public.dta
- Section2_public.dta
- Section3_menage_public.dta
- Section3_scolarité_public.dta
- Section4_public.dta
- Section5_menage_public.dta
- Section5_migrant_public.dta
- Section6_menage_public.dta
- Section6_migrant_public.dta
- Section7_public.dta
- Section8_public.dta
- Section9_migrant_potentiel_public.dta
- Section9_migrant_retour_public.dta
Le département du Sénégal où le membre du ménage est né (p01_13)
Data file: Section1_public.dta
Overview
Valid:
32407
Invalid:
1618
Minimum:
11
Maximum:
143
Mean:
59.3813990804456
Standard deviation:
42.0527143186273
Type:
Discrete
Decimal:
0
Start:
139
End:
141
Width:
3
Range:
11 - 143
Format:
Numeric
Questions and instructions
Literal question
Dans quel département du Sénégal est né (NOM)?
Categories
| Value | Category | Cases | |
|---|---|---|---|
| 11 | DAKAR | 6331 |
19.5%
|
| 12 | PIKINE | 1996 |
6.2%
|
| 13 | RUFISQUE | 664 |
2%
|
| 14 | GUEDIAWAYE | 634 |
2%
|
| 21 | BIGNONA | 514 |
1.6%
|
| 22 | OUSSOUYE | 55 |
0.2%
|
| 23 | ZIGUINCHOR | 595 |
1.8%
|
| 31 | BAMBEY | 410 |
1.3%
|
| 32 | DIOURBEL | 924 |
2.9%
|
| 33 | M’BACKE | 727 |
2.2%
|
| 41 | DAGANA | 361 |
1.1%
|
| 42 | PODOR | 1328 |
4.1%
|
| 43 | SAINT LOUIS | 507 |
1.6%
|
| 51 | BAKEL | 417 |
1.3%
|
| 52 | TAMBACOUNDA | 770 |
2.4%
|
| 53 | GOUDIRY | 280 |
0.9%
|
| 54 | KOUPENTOUM | 118 |
0.4%
|
| 61 | KAOLACK | 1130 |
3.5%
|
| 62 | NIORO | 247 |
0.8%
|
| 63 | GUINGUINEO | 25 |
0.1%
|
| 71 | M’BOUR | 467 |
1.4%
|
| 72 | THIES | 1615 |
5%
|
| 73 | TIVAOUANE | 716 |
2.2%
|
| 81 | KEBEMER | 225 |
0.7%
|
| 82 | LINGUERE | 232 |
0.7%
|
| 83 | LOUGA | 770 |
2.4%
|
| 91 | FATICK | 652 |
2%
|
| 92 | FOUNDIOUGNE | 293 |
0.9%
|
| 93 | GOSSAS | 60 |
0.2%
|
| 101 | KOLDA | 718 |
2.2%
|
| 102 | VELINGARA | 1007 |
3.1%
|
| 103 | MEDINA YORO FOULAH | 374 |
1.2%
|
| 111 | MATAM | 2543 |
7.8%
|
| 112 | KANEL | 2731 |
8.4%
|
| 113 | RANEROU | 49 |
0.2%
|
| 121 | KAFFRINE | 332 |
1%
|
| 122 | BIRKELANE | 35 |
0.1%
|
| 123 | KOUNGHEUL | 83 |
0.3%
|
| 124 | MALEM HODDAR | 21 |
0.1%
|
| 131 | KEDOUGOU | 292 |
0.9%
|
| 132 | SALEMATA | 60 |
0.2%
|
| 133 | SARAYA | 110 |
0.3%
|
| 141 | SEDHIOU | 353 |
1.1%
|
| 142 | BOUNKILING | 348 |
1.1%
|
| 143 | GOUDOMP | 288 |
0.9%
|
| Sysmiss | 1618 |
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.
Interviewer instructions
Questionnaire papier: Enregistrez le nom du département
Questionnaire CAPI enregistrer la liste de tous les pays
Questionnaire CAPI enregistrer la liste de tous les pays
Question post text
2 Hors du pays- 1.14