Enabling poor rural people
to overcome poverty



The sampling frame is the tool used to include a representative selection of communities (clusters) from within the project area.

Step 1: Population data

The sampling frame is constructed with population data from the project area. All communities are listed in alphabetical order, and population figures are added.

Example: Population data

Region Subregion Village
Population
Cumulative Population
Cluster
DINGUIRAYE

BANORA    
 

1

Banora

590

   
 

2

Boubéré

1638

   
 

3

Boukaria

481

   
 

4

Diarendji

1195

   
 

5

Kolla

894

   
 

6

Loppé Sountoun

1131

   
 

7

Matagania

2499

   
 

8

M'Bonet

1094

   
 

9

Nafadji

1526

   
 

10

N'Baloufara

460

   
 

11

Sénéma Tombo

456

   

DIALAKORO  
 

12

Dar es Salam

950

   
 

13

Dialakoro

3900

   
 

14

Fello Lamou

888

   
 

15

Mossoko

1077

   
 

16

Watagala

1194

   

DIATIFERE     
 

17

Dabatou

1082

   
 

18

Diatiféré

2283

   
 

19

Fadougou

855

   
 

20

Faméré

1016

   
 

21

Fandanda

1180

   
 

22

Mamoudouya

1993

   
 

23

Nanako

1367

   
 

24

Soubékindi

1016

   
 

25

Sourou

1320

   
 

26

Syllaya

849

   
 

27

Wonson

1549

   

DINGUIRAYE  
 

28

Balagnoumaya

1403

   
 

29

Dinguiraye Ville

9016

   
 

30

Héleyabhé

1612

   
 

31

Kambam Halledé

674

   
 

32

Kambam Sabhé

613

   
 

33

Kebali

1917

   
 

34

Kouby Leyséré

491

   
 

35

Koumbia Ley Fello

1281

   
 

36

Lankon

690

   
 

37

Paridji

796

   
 

38

Parawol Diagul

1029

   
 

39

Sébékoro

1677

   
 

40

Tinkisso

776

   

GAGNAKALY  
 

41

Bagui

1117

   
 

42

Béléya

571

   
 

43

Doussoura

545

   
 

44

Gagnakaly

1156

   
 

45

Hérako

637

   
 

46

Kalenko Missira

815

   
 

47

Kella

861

   
 

48

Missa Djalonké

577

   
 

49

Nouhouya

444

   

KALINKO   
 

50

Babila

1509

   
 

51

Bokoty

1095

   
 

52

Diabérémini

2313

   
 

53

Diankourou

1180

   
 

54

Djissouma

1223

   
 

55

Farabato

481

   
 

56

Fodécariah

647

   
 

57

Fognokonko

689

   
 

58

Kalinko

1236

   
 

59

Kansatoh

2492

   
 

60

Lenny Tyewi

401

     
 

61

Louffamissidé

584

   
 

62

Missira

766

   
 

63

Niogo

1036

   
 

64

Santafara

683

   
 

65

Walandama

438

   
 

66

Yalaguéré

908

   

LANSANAYA  
 

67

Dayégbhé

1073

   
 

68

Hansanguéré

671

   
 

69

Lansanaya

824

   
 

70

Santiguia

1201

   
 

71

Tambanoro

890

   
 

72

Wouyagbhé

1018

   

SELOUMA   
 

73

Bosséré

1372

   
 

74

Fadia

627

   
 

75

Kobala

1503

   
 

76

Sélouma

2470

   
 

77

Walawala

2220

   
   

TOTAL

94731

   
 

Step 2: Cumulative Population

The population data are then cumulated. As demonstrated below, the population of Banora (590), plus Boubere (1638) is equal to a cumulative population of 2228. When the population of Boukaria (481) is added, the cumulative becomes 2709. This process is continued until the list is complete. In many project areas, the list of villages will be considerably longer than it is in the case used here.

Example: Cumulative population

 Region  

Sub-region

Village

Population

Cumulative Population

Cluster

 DINGUIRAYE  

       
 

BANORA

       
 

1

Banora

590

590

 
 

2

Boubéré

1638

2228

 
 

3

Boukaria

481

2709

 
 

4

Diarendji

1195

3904

 
 

5

Kolla

894

4798

 
 

6

Loppé Sountoun

1131

5929

 
 

7

Matagania

2499

8428

 
 

8

M'Bonet

1094

9522

 
 

9

Nafadji

1526

11048

 
 

10

N'Baloufara

460

11508

 
 

11

Sénéma Tombo

456

11964

 
 

DIALAKORO

   
 

12

Dar es Salam

950

12914

 
 

13

Dialakoro

3900

16814

 
 

14

Fello Lamou

888

17702

 
 

15

Mossoko

1077

18779

 
 

16

Watagala

1194

19973

 
 

DIATIFERE

     
 

17

Dabatou

1082

21055

 
 

18

Diatiféré

2283

23338

  
 

19

Fadougou

855

24193

   
 

20

Faméré

1016

25209

   
 

21

Fandanda

1180

26389

   
 

22

Mamoudouya

1993

28382

  
 

23

Nanako

1367

29749

   
 

24

Soubékindi

1016

30765

   
 

25

Sourou

1320

32085

   
 

26

Syllaya

849

32934

   
 

27

Wonson

1549

34483

   
 

DINGUIRAYE

   
 

28

Balagnoumaya

1403

35886

   
 

29

Dinguiraye Ville

9016

44902

   
 

30

Héleyabhé

1612

46514

   
 

31

Kambam Halledé

674

47188

   
 

32

Kambam Sabhé

613

47801

   
 

33

Kebali

1917

49718

   
 

34

Kouby Leyséré

491

50209

   
 

35

Koumbia Ley Fello

1281

51490

   
 

36

Lankon

690

52180

  
 

37

Paridji

796

52976

   
 

38

Parawol Diagul

1029

54005

   
 

39

Sébékoro

1677

55682

   
 

40

Tinkisso

776

56458

  
 

GAGNAKALY

   
 

41

Bagui

1117

57575

   
 

42

Béléya

571

58146

   
 

43

Doussoura

545

58691

   
 

44

Gagnakaly

1156

59847

   
 

45

Hérako

637

60484

  
 

46

Kalenko Missira

815

61299

   
 

47

Kella

861

62160

   
 

48

Missa Djalonké

577

62737

   
 

49

Nouhouya

444

63181

  
 

KALINKO

     
 

50

Babila

1509

64690

   
 

51

Bokoty

1095

65785

   
 

52

Diabérémini

2313

68098

   
 

53

Diankourou

1180

69278

   
 

54

Djissouma

1223

70501

   
 

55

Farabato

481

70982

   
 

56

Fodécariah

647

71629

  
 

57

Fognokonko

689

72318

 
 

58

Kalinko

1236

73554

   
 

59

Kansatoh

2492

76046

    
 

60

Lenny Tyewi

401

76447

   
 

61

Louffamissidé

584

77031

   
 

62

Missira

766

77797

  
 

63

Niogo

1036

78833

   
 

64

Santafara

683

79516

   
 

65

Walandama

438

79954

   
 

66

Yalaguéré

908

80862

 
 

LANSANAYA

   
 

67

Dayégbhé

1073

81935

   
 

68

Hansanguéré

671

82606

   
 

69

Lansanaya

824

83430

   
 

70

Santiguia

1201

84631

    
 

71

Tambanoro

890

85521

   
 

72

Wouyagbhé

1018

86539

   
 

SELOUMA

     
 

73

Bosséré

1372

87911

   
 

74

Fadia

627

88538

  
 

75

Kobala

1503

90041

   
 

76

Sélouma

2470

92511

   
 

77

Walawala

2220

94731

   
   

TOTAL

94731

     

The sampling frame is basically completed at this point. Now it will be used to assign the distribution of clusters (villages).

Step 3: Clusters

To assign the clusters, it is first necessary to determine a sampling interval and to select a random number.

3.1 Sampling interval

The sampling interval (SI) will be used to systematically assign clusters from the sampling frame. The SI is equal to the total population of the project area (94731), divided by the number of clusters (30). (See the example from the project area.)

Example

SI = Total Population SI = 94731 SI = 3158
No. Clusters
30
 

3.2 Random number

The random number is used to determine the starting point for the first cluster. It should have a value in the range between zero and the SI, which is 0 –3158 in the example.

The random number can be generated by an appropriate computer programme (such as EPI Info), drawn from a random number table, or simply taken from a currency note. As the last method is often the simplest in the field, more detail is given below.

Example

Find a banknote and look at the serial number (SO 19801300). Taking the first four numbers, 1-9-8-0, generates a random number that fits in the required range of 0 – 3158.

3.3 Initial cluster

The first cluster corresponds to the village that has a cumulative population equal to or greater than the random number (1980), which is Boubere in the hypothetical project area. The second cluster corresponds to the village that has a cumulative population equal to or greater than the random number plus the sampling interval (1980+3158=5138), which is Loppe Sountoun village.

Example

Cluster # 1 corresponds to cumulative population of 1980 (Boubere)
Cluster # 2 =1980+3158=5138 (Loppe Sountoun)
Cluster # 3 = 5138+3158=8296 (Matagania)
Cluster # 4 = 8296+3158=11454 (Nibalfoura)
Cluster # 5 = 11454+3158=14612 (Dialakoro)
Cluster # 6 = 14612+3158=1770 (Mossoko). and so on

Example: Clusters

Region

Sub-region

Village

Population

Cumulative Population

Cluster

DINGUIRAYE

       
 

BANORA

       
 

1

Banora

590

590

 
 

2

Boubéré

1638

2228

1

 

3

Boukaria

481

2709

 
 

4

Diarendji

1195

3904

 
 

5

Kolla

894

4798

 
 

6

Loppé Sountoun

1131

5929

2

 

7

Matagania

2499

8428

3

 

8

M'Bonet

1094

9522

 
 

9

Nafadji

1526

11048

 
 

10

N'Baloufara

460

11508

4

 

11

Sénéma Tombo

456

11964

 
 

DIALAKORO

     
 

12

Dar es Salam

950

12914

 
 

13

Dialakoro

3900

16814

5

 

14

Fello Lamou

888

17702

 
 

15

Mossoko

1077

18779

6

 

16

Watagala

1194

19973

 
 

DIATIFERE

       
 

17

Dabatou

1082

21055

7

 

18

Diatiféré

2283

23338

 
 

19

Fadougou

855

24193

8

 

20

Faméré

1016

25209

 
 

21

Fandanda

1180

26389

 
 

22

Mamoudouya

1993

28382

9

 

23

Nanako

1367

29749

 
 

24

Soubékindi

1016

30765

10

 

25

Sourou

1320

32085

 
 

26

Syllaya

849

32934

 
 

27

Wonson

1549

34483

11

 

DINGUIRAYE

     
 

28

Balagnoumaya

1403

35886

 
 

29

Dinguiraye Ville

9016

44902

12, 13, 14

 

30

Héleyabhé

1612

46514

15

 

31

Kambam Halledé

674

47188

 
 

32

Kambam Sabhé

613

47801

 
 

33

Kebali

1917

49718

16

 

34

Kouby Leyséré

491

50209

 
 

35

Koumbia Ley Fello

1281

51490

 
 

36

Lankon

690

52180

 
 

37

Paridji

796

52976

17

 

38

Parawol Diagul

1029

54005

 
 

39

Sébékoro

1677

55682

18

 

40

Tinkisso

776

56458

 
 

GAGNAKALY

     
 

41

Bagui

1117

57575

 
 

42

Béléya

571

58146

 
 

43

Doussoura

545

58691

 
 

44

Gagnakaly

1156

59847

19

 

45

Hérako

637

60484

 
 

46

Kalenko Missira

815

61299

 
 

47

Kella

861

62160

20

 

48

Missa Djalonké

577

62737

 
 

49

Nouhouya

444

63181

 
 

KALINKO

       
 

50

Babila

1509

64690

 
 

51

Bokoty

1095

65785

21

 

52

Diabérémini

2313

68098

 
 

53

Diankourou

1180

69278

22

 

54

Djissouma

1223

70501

 
 

55

Farabato

481

70982

 
 

56

Fodécariah

647

71629

23

 

57

Fognokonko

689

72318

 
 

58

Kalinko

1236

73554

 
 

59

Kansatoh

2492

76046

24

 

60

Lenny Tyewi

401

76447

 
 

61

Louffamissidé

584

77031

 
 

62

Missira

766

77797

25

 

63

Niogo

1036

78833

 
 

64

Santafara

683

79516

 
 

65

Walandama

438

79954

 
 

66

Yalaguéré

908

80862

 
 

LANSANAYA

     
 

67

Dayégbhé

1073

81935

26

 

68

Hansanguéré

671

82606

 
 

69

Lansanaya

824

83430

 
 

70

Santiguia

1201

84631

27

 

71

Tambanoro

890

85521

 
 

72

Wouyagbhé

1018

86539

 
 

SELOUMA

       
 

73

Bosséré

1372

87911

28

 

74

Fadia

627

88538

 
 

75

Kobala

1503

90041

 
 

76

Sélouma

2470

92511

29

 

77

Walawala

2220

94731

30

   

TOTAL

94731

   

The methodology for selecting households within the clusters is explained in Unit II, Training handbook: Collecting anthropometric measures of children.