GEOGRAPHY FORM 5-SAMPLING IN FIELD RESEARCH

GEOGRAPHY FORM 5-SAMPLING IN FIELD RESEARCH

UNAWEZA JIPATIA NOTES ZETU KWA KUCHANGIA KIASI KIDOGO KABISA:PIGA SIMU:0787237719

SAMPLING IN FIELD RESEARCH

Meaning of different terms used in sampling in field research

Sample

This is a part of population, it is a set of selected elements from a population for study. It must be selected elements from a population for study. It must be selected according to principles of sampling and this will make it move representative of total population

Sampling

Is the process of selecting small number of people or objects or units(sample) to represent the entire population, Example to checking the soil type it may be taken small amount of soil the amount taken is said to be sample

 Population or universe

Is the group of individuals ,items, objects from which samples taken for a particular study

It is the targeted group

Element

These include individual persons, objects or units about which information is collected

Sample size

This refers to the total number of item or individual to be selected from the population to constitute a sample. The larger the sample size the lower the likely error in generalization to the population. Also the larger the sample size the more the money and time needed to carry our the researcher

Sampling design

Refers to the part of the research plan that indicates how cases are to be selected for observation

 

Sampling frame

This is a complete or reliable list of all elements in a population from which a sample will be selected or drawn. It is a complete list of every unit in the universe or population

 

Variable

This is a logical grouping of the attributes like sex or gender composed of two attributes ie males and female

Variable are divided into two groups 

1.  independent
2. dependent variable

Parameter

This is a summary description of given variables in a population

Characteristics of a good sample

1.       1.It must cover wide geographical area

2.       It must have enough number of representatives so as to show clearly what is in population

3         It must have a wide range of types of elements to reduce biases

4         It must be selected by the researcher him/her self as he/she know the kind of respondent she/she need and methods he/she will use to obtain it

 

Importance of sampling in field research

i.   Sample can save time since can produce result from within short and relative time

ii. it is cheap in terms of cost I serve budget constrains

iii. sampling provide a greatest scope in terms of variable that may be studied

iv. sampling is scientifically and statistically justifiable

v. sampling is an alternative way when population under study contain large number of items’ and occupy a vast geographical area

 

 TYPES OF SAMPLING

There are two types of sampling;

1. Probability sampling
2. Non- probability sampling

PROBABILITY SAMPLING

• It is a random selection is a sample
• This is a sampling method where selection at sample is done randomly by chance .Here each individual in a population has an equal chance of being included in the sample

Types of probability sampling

1. Sample random sampling
2. Systematic random sampling
3. Stratified sampling
4. Mulit stage sampling
5. Cluster  sampling

 

a. Sample random sampling

This gives every possible combination element in a population equal chance of being included in the sample.

It is chance sampling technique where each of every items or individual in the population has an equal opportunity in the inclusion the sample

Method of simple random sampling

I.   By lottery method

II.  The table of random number

III.  Computer method : it is similar to table random number but under this number are picked by computer

 

b. Systematic sampling

Is the type of probability sampling by selecting of individual or items on a given regular interval. It is very applicable when population sample is large and the target population is evenly distributed

 For example
formula of  sampling interval  K = N/n

N- Total number of population

n- sample size
K- sampling Interval

to obtain the sample using systematic sampling

Question.
If the total population is 1000 individual, and the number of  people who must be in the sample are 100, what will be sampling interval

 

Steps

I.  Calculate sampling interval or fraction

K=Fraction(K)  or sampling interval
N = 1000
n = 100

II.  Picking the starting point by any method of simple random sampling

III.  Picking systematically with the specific interval (k) by adding (k) to the pick number until the required single is achieve

c. Stratified sampling

It is a type of probability sampling involving a selection of study sample by dividing the targeted population into the homogeneous sub group(strata) and then simple random sampling in each sub group

E.g suppose the target population consist of 700 male sub population and 300 female sub population

Create male and female sub sample provided that 100 total population sample is required

Step

i).  Calculate the total number of the population

 

ii). Finding the sampling ratio

Given by

ratio

iii). Calculate sub sample of male and female by taking sampling ratio multiple by sample population of each

male = 1/10  x   700 = 70 male

Female = 1/10 x 300 = 30 female

 

Ø  Example 2 ,3000 students, 100staff, 50 non teaching staff,

Using stratified  sampling technique prepare  sample for a particular studying of 10%

Steps
Calculate sub samples

i.  student 10/100 x 3000=300

–          teachers 10/100 x 100=10

Non teacher 10/100 X 50=5

–     Therefore  300 +  10 + 5 = 315

ii. the sample of the particular study is 315

advantages stratified

• It is more representative than simple random sampling of the same size drawn from the same population
• Conclusion from stratified sample are more general sable than simple random.

 

Disadvantage

• The technique is complex because it need researcher to analyze the population carefully to discover its true composition
• Chance that researcher get wrong stratum,subgroup are great

d. Cluster/area /spatial sampling

Is the type of at probability sampling used when target population is displaced over a wide geographical area. Under this the total area at study is divided.

The total area into a number at smaller non-overlapping areas, generally called geographical clusters Then a number of smaller areas are randomly elected

All units in these small areas are included in the sample

 

e. Multi stage sampling

This is further development of the idea cluster sampling .This technique is meant for big inquiries extending to  a considerably large geographical area like an entire country

Under this, the first stage may be to select large primary sample unit such as state, then region then district,then town and finally certain families within towns

i.e the second sample is selected or drawn from the first sample, the third sample from the second sample etc

example: population of 2500 people is spread over Temeke district.A sample of 600 household need to be selected from this population for study

-Researcher will list down all divisions in Temeke district. Let us say there 10 dimension so in this stage he may take five division( of them)

–  List down all the wards in those five division let us say there are six (6) wards in each division i.e 6 x5 = 30 wards. in the second stage, sample wards = 10 wards

-List down villages or streets in these 10 wards and the are 10 street or village in each ward. Thus 10 x10 =100 villages in the third stage the villages = 25 sample village

–  List down house holds of each village and let us say there 100 house hold house holds

In the fourth stage sample the household = 500 households

Thus our sample is 500 household

NON-PROBABILITY SAMPLING

Is the type at sampling which does not give each items or element in target population equal chance to be included in sampling
Types of non-probability sampling

a.       Accidental/chunk/convenience sampling

b.      Snow-ball sampling

c.       Purposive/judgmental

d.      Quota sampling

 

I.  Accidental sampling

Under this method, the researcher  Collect data from responds for a given research study he/she meets accidentally during the period research

 

II.  Snow ball sampling

The researcher starts his/her research with small number of respondents who are available and ask them t o call for other who will fit in the study

 

III.  Purpose/judgment sampling

Is the type of Non- probability sampling where researcher purposeful chooses responder whose in his/her own opinion thought are to be relevant of the study

IV. Quota sampling

In stratified sampling the cost of taking random samples from individual strata is often expensive that interviewer are simply given quota to be filled from different strata, the actual selection of items for sample being left to the interviewers judgment

The size of the quota for each stratum is generally, proportionate to the size that stratum in the population

( If that stratum is ¼ of the total population then the researcher take a ¼ of individual in that particular stratum

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