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PROBABILITY SAMPLING (RANDOM)

Simple Random sampling

Systematic sampling

Stratified sampling

Cluster sampling

ProbabilitySampling

A method of sampling that uses of randomselection so that each member of the

population, or of sub-groups, has an equal

probability of being chosen.

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Definetarget

population

Identifysampling

frame

Determinesample

size

Determinemethod ofsampling

Selectsample

Steps in probability sampling

Step 1 Step 2 Step 3 Step 4 Step 5

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1.Simple Random Sampling (SRS)In a SRS, subjects are selected from the population in

which every member of the population has equal chanceof being chosen (e.g., drawing names out of a hat, use atable of random number). Applicable when population issmall, homogeneous & readily available.

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Systematic Sampling is a sampling method in which

every nth elementis selected from a list of all elements

in the survey population, beginning with a randomly

selected element.

E.g, from among 50 students, we need to select 5 to be

our sample (10%), we would randomly select a number

from 1 to 10, then select every 10thstudent for our

sample.

2. SystematicSampling

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A population is divided into homogenous, mutually

exclusive starta or subgroups (age, gender, location,level of education), and a sample is randomly selected

from each stratum.

3. Stratified (Random) Sampling

Proportionate stratified

sampling

based on the

percentage of subjectsin the population that is

present in each stratum.

Disproportionate stratified

sampling

the researcher selects the

same number of subjectsto be in each stratum of

the sample.

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Section 4

Section 5

Section 3

Section 2Section 1

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is the selectionof two or more levelsof clusters.

E.g., school districts, schools within districts,

classroom within school, students within

classroom. We could begin by sampling 40 of

150 school districts, then 6 classrooms in each

of the 40 districts, and then 10 students in

each classroom.

Multi-stage cluster Sampling

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STRENGTHS AND WEAKNESSES OF SAMPLING METHOD

Sampling

methods

Advantages Disadvantages

Simple

Random

Sampling

Easy to understand

Little knowledge of

population needed.

Free of subject

classsification error

Easy to analyze and

interpret results.

Require numbering

each element in a

non-electronic list of

members of the

population.

Larger sampling

error than in

stratified sampling

for same sample size.

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Sampling Advantages Disadvantages

Systematic(Random)

Sampling

Easier to draw.Easy to

understand

Free of subject

classsification error.Easy to analyze

and interpret

results.

Subjects dont

need to be

numbered.

Largersampling error

than in stratified

sampling for

same samplesize.

Periodicty in

list of population

elements.

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Sampling

Techniques

Advantages Disadvantages

Stratified

(Random)

Sampling

Allow easy subgroup

comparisons.

More representativethan Simple random or

systematic.

Fewer subjects

needed if strata arerelated to the

dependent variable.

Requires

subgroup

identification ofeach population

element.

Costly and

difficult toprepare lists of

population

elements in each

subgroup

Advantages & Disadvantages

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