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RESEARCH

© Y o sa A . A lz u hd y U N Y

QUANTITATIVE

© Y o s a A . A lz u h d y – F B S -U N Y

RESEARCH

QUANTITATIVE

2a. WHO of

RESEARCH

Quantitative Research

© Yosa A. Alzuhdy, M.Hum.

yosa@uny.ac.id

English Language and

Literature Study Program

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Three questions to begin:

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WHO? Sampling

Often the groups sociologists want to study are so large or so dispersed that research on the whole group is impossible.

To construct a picture of the entire group, they take data from a subset of the.

 _A sample _{is any subset of a population.}  _A population _{is a relatively large}

collection of people, the universe of the

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Sampling

 _{Many situations where not possible to study}

the entire population

 _{A sample is a finite part of a population}

whose properties are studied to gain information about the whole.

 _{Subset of population can be used to make}

generalizations

 _{Must be representative of total population}

 _{See all characteristics of total population}

in same relationship

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Sampling Strategy

 _{The degree to which your sample mirrors the}

population from which it comes will depend to a large extent on your sampling strategy.

 _{The sampling strategy is the way in which}

you select units from the population for inclusion into your study.

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Why is sampling

important?

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Sample Quant. Research

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Sampling Frame

Sampling Frame: A list of all the individuals (units) in the population from which the

sample is taken; the actual list of sampling units (or elements).

Examples of Sampling Frames:

 _{Students of Yogyakarta State University}

 _{List of businesses registered with the Chamber of}

Commerce

 _{The phone book}

 _{List of students served by the ILLC}

 _{List of labor migrants registered with authorities in a}

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Sampling Techniques

NON-RANDOM SAMPLING (Non-Probability): each member of the sampling frame does not have an equal chance of being selected as a participant in the study.

 _{Convenience Sampling}  _{Snowball Sampling}

 _{Purposive Sampling}  _{Quota Sampling}

 _{Self-Selected/Voluntary}

RANDOM SAMPLING (Probability): each member of the sampling frame has an equal chance of being selected.

 _{Simple Random Sampling}  _{Stratified Random Sampling}  _{Systematic Sampling}

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Convenience Sampling

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Snowball Sampling

 _{Typically used in qualitative research}

 _{When members of a population are difficult}

to locate, for covert sub-populations, non-cooperative groups

 _{Recruit one respondent, who identifies}

others, who identify still others,….

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Snowball Sampling

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Why Snowball Sampling?

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Other Non-Probability

Sampling

PURPOSIVE SAMPLING

 _{Select the sample on the basis of knowledge}

of the population: suitability with the

purpose, or use expert judges to identify candidates to select

 _{Typically used for very rare populations, such}

as deviant cases

SELF-SELECTED/VOLUNTARY SAMPLING

 _{Give the candidates opportunity to}

voluntarily participate in a survey

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Quota Sampling

 _{A stratified convenience sampling strategy}  _{Begins with a table that describes the}

characteristics of the target population

 _{e.g. the composition of postgraduate}

students at UNY in terms of faculty, race, and gender

 _{Then select on a convenience basis,}

postgraduate students in the same proportions regarding faculty, race, and gender than in the population

 _{Of course, the quota frame (the proportions in}

the table) must be accurate

 _{And biases may be introduced when selecting}

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Simple Random Sampling

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Selecting Simple Random Sample-

MS

Excel

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Selecting Simple Random Sample -

SPSS

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Margin of Error

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Margin of Error

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Stratified Random

Sampling

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Systematic Sampling

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Cluster Sampling

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Generating a Random

Sample

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Generating Random

Number

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Sampling Error (Bias)

The reliability and internal validity of your research can be effected by:

 _{Sampling errors (Bias)}  _{Non-sampling errors}

Sampling error occurs when an abnormally large number of units with unusual characteristics are chosen from a given population.

Influence disturbing randomness of sample population

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Sampling Error (Bias)

Most often the result of:

 _{Flawed sampling frame}

 _{Poor sampling strategy}

 _{Small sample size}

Protecting against sampling error:

_{Use a large sample size}

_{Probability sampling}

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Sample Size

Quantitative Research:

A function of the variability or variance one expects to find in the population (standard deviation), and the statistical level of confidence (usually 95%) one

wishes to use.

Qualitative Research: As big as possible

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Sample Size

• _{The larger the sample, the better}

• _{Guidelines (for professional research):}

 _{< 100 survey entire population}

 _{~ 500 survey 50% of population}

 _{~ 1,500 survey 20% of population}

 _{> 5,000 survey 400}

• _{Larger sample may be necessary for}

heterogeneous population

• _{For undergrad: approx.30 or more}

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That’s all for today

…

Prepare for the next material:

How and Why of the

Research