# data[].attributes.body
1. safe
2. 50%
3. 2,6 billion
4. 30%

Exercise 2
1.surface water
2.untreated water
3.treated water
4.piped supply

# data[].attributes.body
1.
2. 50%
3. 2.6 billion
4. 30%

# data[].attributes.body
1. safe
2. over 50
3. 2.6 billion
4. 30%

ex2
1.surface water
2.untreated water
3.treated water
4.piped supply

ex3
1. wheel
2. loop of rope
3. PVC pipe
4. suction

# data[].attributes.body
1. safe
2. 50%
3. 2,6 billion
4. 30%

1. surface water
2. untreated water
3. treated water
4. piped supply

# data[].attributes.body
1 safe
2 over 50%
3 2.6 bilion
4 30

1 treated water
2 surface water
3 treated water
4 pipesuplly

1 wheel
2 loop of rope
3 PVC pipe
4 suction

# data[].attributes.body
1.
2. 50%
3. 2.6 billion
4. 30%
ex. 2
1. treated water
2. surface ______
3. treated _______
4. piped supply
ex 3
1. wheel
2.
3. PVC pipe
4. suction

# data[].attributes.body
safe,50%,2.6,30/untreated water, surface water, treated water, piped supply/bicycle wheel, a loop of rope, PVC pipe, suction

# data[].attributes.body
1.safe
2.50%
3.2.6 billion
4. around 30%
Ex 2:
1.surface water
2.untreated water
3.treated water
4.piped supply
Ex 3:
1.rope pump
2.washers
3.PVC pipe
4.suction

# data[].attributes.body
1. safe
2. 50%
3. 2.6 billion
4. 30%

1. surface water
2. untreated water
3. treated water
4. piped supply

1. wheel
2. loop of rope
3. pvc pipe
4. suction

# data[].attributes.body
1,Safe
2,over 50%
3,2.6 billion
4,30%

Exercise 2
Surface water
Untreated water
Treated water
Piped supply

Exercise 3
Wheel
Loop of rope
PVC pipe
Suction

# data[].attributes.body
1 drinking
2 50
3 2.6 billion
4 30%

Ex2
1 surface water
2 untreated water
3 treated water
4 piped supply

Ex3
1 wheel
2 loop of rope
3 PVC pipe
4 suction

# data[].attributes.body
1 safe
2 50
3 2,6 billion
4 30

1 surface water
2 untreated water
3treated water
4piped supply

1
2 loof of rope
3PVC pipe
4 suction

# data[].attributes.body
1. Safe
2. Over 50
3. 2.6 billion
4. 30%

1. Surface water
2. Untreated water
3 treated water
4 piped supply

1. Wheel

2. Loop of rope
3 PVC pipe
4 suction

# data[].attributes.body
1 Clean
2 More than 50%
3 2.6 billion hmmm
4 30%

ex2:
1 surface water
2 untreated water
3
4

# data[].attributes.body
1 safe
2 over 50
3 2,6 billion
4 30%

2.
1surface water
2 untreated water
3 treated water
4 piped supply

1wheel
2 pvc pipe
3loop of rope
4 suction

ex4
1information
2included
3is excluded
4contamination
5

# data[].attributes.body
1.safe
2.50%
3.2,6b
4.30

1. surface water
2. untreated water
3. treated water
4. piped supply

# data[].attributes.body
1. safe
2. 50%
3. 2.6 billion
4. 30%
ex2
1. surface water
2. untreated water
3. treated water
4. piped supply
ex3
1. wheel
2. PVC pipe
3. loop of rope
4. suction
ex4
1 information
2 included
3 is excluded
4 contamination
5 health
6 increase

# data[].attributes.body
1:safe
2: over 50
3:2.6 billion
4:30%
Ex2:
1: surface water
2:untreated water
3:treated water
4:piped water
Ex3:
1:wheel
2:loop of rope
3:PVC pipe
4:suction
Exam skil:
1:information
2:inclued
3:is exclued
4:contanmination
5:public health
6:increase

# data[].attributes.body
1. safe
2. over 50
3. 2.6 billion
4. 30%

1 surface water
2 untreated water
3 treated water
4 piped supply

# data[].attributes.body
1)safe
2) over over 50
3)2.6 billion
4)30%
EX2
1)surface water
2) untreated water
3) treated water
4)piped supply
EX3
1) wheel
2) loop of rope
3) PVC pipe
4) suction

EX4
1) information
2) included
3) is excluded
4)contaminant
5)
6)increase

# data[].attributes.body
1. safe
2. over 50
3. 2.6 billion
4. around 30%

1.surface water
2.untreated water
3.treated water
4. piped water

1.bicycle wheel
2. PVC pipe
3. loop of rope
4. suction

# data[].attributes.body
1. safe
2.50%
3.2.6 billion
4. 30%
ex2:
1.surface water
2, un treated water
3, treated water
4, piped water
ex3:
1.water pump
2, loop of rope
3, rope pump
4,suction

# data[].attributes.body
1. safe
2 50%
3.2.6
4.30%

ex2
1 surface water
2 untreated water
3 treated water
4 piped supply

# data[].attributes.body
1. safe
2. 50
3. 2.6 bil
4. 30

1. surface water
2. untreated wtaer
3. treated water
4. piped supply

1. cycle
2. pvc pipe
3. lôop of rope
4. suction

# data[].attributes.body
Ex 1
1 Drinkable
2 50
3 2.6 billion people
4 30%

Ex 2
1 surface water
2 untreated water
3 treated water
4 piped supply

Ex 3
1 bicycle wheel
2 PVC pipe
3 loop of rope
4 suction

Ex 4
1 information
2 included
3 is excluded
4 contamination
5 health
6 increase

# data[].attributes.body
1 Sources
2 over 50%
3 2,6 billion
4 30 %

1 surface water
1 treated water
3 treated water
4 piped supply

1 cycle part
2 pvc pipe
3 loop of rope
4 suction

# data[].attributes.body
Ex1
1. drinking
2. 50
3. 2.6 billion
4. 30%

Ex2
1. surface water
2. untreated water
3. treated water
4. piped supply

Ex3
1. wheel
2. loop of rope
3. PVC pipe
4. suction