Notes RM Chapter 11

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Chapter 11

Sampling

The nature of sampling:

- Population:Its the whole from which the researcher is going to drive a part known as asample.

- Population Element: a unit in the population- Population Frame: List of the whole (all population elements), official type of

document.

- Sample: a unit of the element- Subject: a unit of the sample

Example:

- Research Topic: postgraduate students studyingMBA in greater Cairo- Population: any institution or university giving MBA degree, the whole.- Population Element: Eslsca, unit of the whole- Sample: Class in Eslsca, unit of the element- Subject: students in the class, unit of the sample- Population Frame: List of all institutions all universities granting MBA.

In probability sampling:

- Researcher should provide a complete list of the population elements in the populationframe.

- If researcher is ready with population frame, then he can work probability sampling;since everybody is involved, this means that everybody has got an equal chance of being

chosen.


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Appropriate sample size:

- In quantitative: a minimum number of a good representative, samples is required,number is calculated through an equation proportional of the total size of population.

A representative sample: a sample that represents and keeps the characteristics of the

population (gender and age diversity).

- In qualitative: sample saturation is the goal, researcher doesnt have a minimum or amaximum number.

Steps:

1- Target population: Who is the appropriate person who is eligible to fill thequestionnaire? Is it women only or men only or middle managers.


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2- Parameters of interest: Research hypothesis tell exactly the parameters of interest andwhat to ask the target population.

3- Sampling frame: its a list of the members included in a sample.4- Sampling method5- Sample Size:

In quantitative: a number is calculated through an equation proportional of the total

size of population.

In qualitative: sample saturation is the goal, researcher doesnt have a minimum or a

maximum number.

Restricted probability sampling Unrestricted random sampling- Researcher has some restrictions to

put into considerations.

- Researcher giving questionnaire towhoever without any restriction,

irrespective of age or gender, and ask

him to fill the questionnaire.


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Probability Nonprobability

- Unrestricted - Simple random sampling - Convenience sampling:whoever is available & willing

to participate will be part of

the sample.

- A case of sampling that youcant get hold of the total

population.

- RestrictedCertain

considerationsto meet

- Complex random1-Systematic: researcher knows

population elements and startpicking samples according to

specific order, i.e 1,3,5,7.

2-Cluster: is the most highlydefined sample.

3-Stratified: is dividing sampleinto no. of strata.

4-Double: It is surveying thesame person twice.

- Purposive sampling: there arecertain standards that make the

sample eligible to answer thequestions.

- Three types of purposivesampling:

1-Judgment: looking forsomeone specifically.

2-Quota: maintain certainsample size to be sure that

sample is representative.

3-Snowball: ask participant torecommend another one.

- - Every and each one has equalopportunity of being chosen.

- We use it when we knowexactly the population.

- It generates more reliablefindings.

- Generalizable.

- When researcher dont knowwho the population is.

- Its about validity & notgeneralizability.


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Systematic: researcher knows every element in the population elements and start picking

samples according to specific order, i.e 1,3,5,7.


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Stratified sampling in research= market segment in marketing

It is dividing sample into number of strata, each strata has got certain characteristics. i.e: class is

the strata, stratum will be:

- Stratum 1: top performers- Stratum 2: poor performers.

People within the same stratum are having homogeneity

From one stratum to another, there is a case of heterogeneity.


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Cluster sampling:

- It is the complete opposite of stratified sampling.- It is the most highly defined sample ever.- Sample is divided to clusters: cluster 1 & cluster 2

People within cluster 1 are heterogenous. From cluster 1 to cluster 2, there is homogeneity.


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Very Important slide.


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Double Sampling:

1. It is surveying the same person twice.i.e: a researcher has done a survey about student satisfaction, 20 students participated,however, 5 of them gave deep answers to the questions, the researcher resurvey them

and that would be double sampling

2. A sample of the sample, same scope but different questions


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Area sampling = geographic sampling

Mobinil, Vodafone and Etisalat are helping with area sampling.

Area sampling is used extensively in marketing research.


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Notes RM Chapter 11