Student Development InstituteFaculty of Arts, Humanities and Languages

Selecting the Sample

Submitted to : Prean Sopheak

Students Kum visal

Khem socheat

Keom chanrozaLi meymey

Loun Voleak

Lem seha

Ko rina

Batch II, Group II , Year III, Semester IIAcademic year 2016-2017

CONTENTsI. The concept of sampling

II. Sampling terminology

III. Principle of sampling

IV. Factors affecting the interference drawn from a sample

V. Aim in selecting a sampling

VI. Type of sampling

Random /probability designs

Non –random/non-probability sampling designs

Mixed sampling designs

The calculation of sampling size

I. The Concept of Sampling

Nature and quality of the frame

Availability of auxiliary information about

units on the frame

Accuracy requirements, and the need to

measure accuracy

Whether detailed analysis of the sample is

expected

• Cost/operational concerns

The concept of sampling in qualitative Research

What is qualitative research?

Qualitative research is a type of scientific research. In general terms, scientific research consists of an investigation that:

• seeks answers to a question

• systematically uses a predefined set of procedures to answer the question

• collects evidence

• produces findings that were not determined in advance

• produces findings that are applicable beyond the immediate boundaries of the study

Con-

Qualitative research shares these

characteristics. Additionally, it seeks to

understand a given research problem or topic

from the perspectives of the local population

it involves. It is especially effective in

obtaining culturally specific information

about the values, opinions, behaviors, and

social contexts of particular populations

II. Sampling terminology

Sampling terminology is let us, again, consider

the examples used above. Our main aims are to find our

the average age of the class, the average income of the

families living in the city, and the likely election

outcome for a particular state or country.

In this process there are a number of

aspects:

population

Sample

Sample size

Sampling Design

Con-

Sampling unit

Sampling frame

Sample statistics

Population mean

Saturation point

III. Principle of sampling

• Principle one: In a majority of cases of sampling

there will be a difference between the same statistic

and the true population mean, which is attributable to

the selection of the units in the sample.

• Principle two: The greater the sample size, the

more accurate will be the estimate of the true

population mean.

• Principle three: The greater the difference in the

variable under study in a population for a given size,

the greater will the difference between the sample

statistics and the true population mean.

IV. Factor affecting the inference drawn from the sample

The two factors have influence:

Sample size used in a study is determined

based on the expense of data collection, and

the need to have sufficient statistical power.

Extent to change in sampling population

• The greater extent of is the process of taking a

subset of subjects that is representative of the

entire population.

V. Aim to selecting a sample

• Achieving the maximum precision in estimates

within given sample size

• Avoid bias in the selection of your sample

• Bias can occur if:

• Sampling in done by a non-random method

• The sampling frame

• A selection of a sampling population is

impossible to find or refuse to operate.

VI. Type of Sampling

A sample design is made up of two elements:

Sampling method refers to the rules and

procedures by which some elements of the

population are included in the sample.

Estimator is a estimated process for

calculating sample statistics. Different

sampling methods may use different

estimators.

Random/probability sampling designs

Methods of Drawing a Random Sampling

The fishbowl draw: the numbers identity and stand for specific elements in the populations and presumably the entire population of elements has been numbered and is presented in the bowl.

Computer program:

A table of random numbers: A random number table is a list of numbers, composed of the digits 0, 1, 2, 3, 4, 5, 6, 7, 8, and 9. Numbers in the list are arranged so that each digit has no predictable relationship to the digits that preceded it or to the digits that followed it. In short, the digits are arranged randomly

Drawing a Random Sample

Consisting of 2 methods for selecting a random sample:1. Sampling without replacement: Sampling is called without replacement when a unit is selected at random from the population and it is not returned to the main lot.

2. Sampling with replacement : Sampling without replacement is used to find probability with replacement. In other words, you want to find the probability of some event where there’s a number of balls, cards or other objects, and you replace the item each time you choose one.

The specific random /probability sampling

design

Consisting of 3 types of random sampling designs:1. Sample random sampling (SRS)

The most commonly used method of selecting a probability sample.

2. Stratified random sampling

Depending on the extend of variability or heterogeneity of study population.

3. Cluster sampling

The ability of classifying the sampling population in to groups.

Non-random/non-probability Non-probability sampling is a sampling technique

where the samples are gathered in a process that does not give all the individuals in the population equal chances of being selected. Non-random/non- probability sampling designs are used when the number of element in a population is either unknown or it isn’t specific. Those types of sampling can be used when demonstrating that a particular trait exists in the population.

There are four types of Non-random/non-probability

sampling designs

Convenience Sampling or Accidental Sampling

Quota Sampling

Judgmental Sampling or Purposive Sampling

• Snowball sampling

Con-

Convenience sampling is probably the most common of all

sampling techniques. With convenience sampling, the samples

are selected because they are accessible to the researcher.

Subjects are chosen simply because they are easy to recruit.

This technique is considered easiest, cheapest and least time

consuming

Con-

• Quota sampling is a non-probability sampling

technique wherein the researcher ensures equal or

proportionate representation of subjects depending on

which trait is considered as basis of the quota.

Con-

• Judgmental sampling is more commonly known as purposive sampling.

In this type of sampling, subjects are chosen to be part of the sample with a

specific purpose in mind. With judgmental sampling, the researcher

believes that some subjects are fit for the research compared to other

individuals. This is the reason why they are purposively chosen as subjects

Con-

• Snowball sampling is usually done when there is a

very small population size. In this type of sampling,

the researcher asks the initial subject to identify

another potential subject who also meets the criteria

of the research. The downside of using a snowball

sample is that it is hardly representative of the

population.

Mixed sampling designs:

Systematic sampling designs have been classified under

the “Mixed” sampling category because it has the characteristic of

both random and non-random sampling designs.

The procedure for selecting a systematic sample:+ Step 1: Prepare a list of all the elements in the study population

(N).

+ Step 2: Decide on the sample size (n).

+ Step 3: Determine the width of the interval (k) = total

population /Sample size

+ Step 4: Using the SRS, select an element from the first interval

(nth order).

+ Step 5: Select the same order element from each subsequent

interval

The calculation of simple size:

Calculation of exact sample size is an important

part of research design. It is very important to

understand that different study design need

different method of sample size calculation and

one formula cannot be used in all designs.

The size of the sample is important for testing a

hypothesis or establishing an association, but for

other studies the general rule is the large the

sample size, the more accurate will be your

estimates.

Con-

In determining the size of your simple forquantitative studies and in particular for causeand effect studies, you need to consider thefollowing

1. At what level of confidence do you want totest your results, finding or hypotheses?2. With what degree of accuracy do you wish toestimate the population parameters?3. What is the estimated level of variation(standard deviation), with respect to the mainvariable you are studying, in the studypopulation?

Thanks