Outlines Definition Background Types of sampling Quantitative & Qualitative The sample size Sample Error Ethical in “ Data Collection “ Principle of ethics.

Issues to consider:Population, Sampling, Ethics

PREPARED BY:

HISHAM HABIL & ABDURRAHMAN ABDALLA

Outlines•Definition•Background•Types of sampling•Quantitative & Qualitative•The sample size•Sample Error•Ethical in “ Data Collection “•Principle of ethics

Definition•What is sampling? Sampling is the process of selecting a few (sample) from a bigger group (sampling population) so that estimation or prediction is made with regard to the prevalence of a particular unknown piece of information, situation or outcome concerning the big group

BackgroundThe European Historical Population Samples Network (EHPS-Net) brings together scholars to create a common format for databases containing non-aggregatedinformation on persons, FAMILIES and households. This format or Intermediate Data Structure (IDS) aims to form an integrated and joint interface between many European databases in order to transcend the currently regional and national studies. EHPS-Net started in June 2011. Since some of our goals are still in the initial stage, some major items of this portal are still under development. This holds especially for the e-journal and the repository 

How many types of sampling Probability(Random) samples• simple random sample• Systematic random sample• stratified random sample• multistage sample• multiphase sample• cluster sample

NON-Probability samples• Convenience sample• Purposive sample• Quota sample

Probability samplesThis is the best overall group of methods to use as you can subsequently use the most powerful statistical analyses on the results.

Best when Method

Whole population is available. Simple random sampling

There are specific sub-groups to investigate (eg. demographic groupings).

Stratified sampling (random within target groups)

When a stream of representative people are available (eg. in the street). Systematic sampling (every nth person)

When population groups are separated and access to all is difficult, eg. in many distant cities.

Cluster sampling (all in limited groups)

NON-ProbabilityQuota methods:For a particular analysis and valid results, you can determine the number of people you need to sample. In particular when you are studying a number of groups and when sub-groups are small, then you will need equivalent numbers to enable equivalent analysis and conclusions.

Best when Method

You have access to a wide population, including sub-groups

Quota sampling (get only as many as you need)

You know the population distribution across groups, and when normal sampling may not give enough in minority groups

Proportionate quota sampling (in proportion to population sub-groups)

There is likely to a wide variation in the studied characteristic within minority groups

Non-proportionate quota sampling (minimum number from each sub-group)

Purposive methods

Best when Method

You are studying particular groups

Purposive sampling (based on intent)

You want expert opinion Expert sampling (seeking 'experts')

You seek similar subjects (eg. young drinkers)

Snowball sampling (ask for recommendations)

When sought 'typical' opinion may get lost in a wider study, and when you are able to identify the 'typical' group

Modal instance sampling (focus on 'typical' people)

You are specifically seeking differences, eg. to identify sub-groups or potential conflicts

Diversity sampling (deliberately seeking variation)

Convenience methodsGood sampling is time-consuming and expensive. Not all experimenters have the time or funds to use more accurate methods. There is a price, of course, in the potential limited validity of results.

Best when Method

You are ethically and socially able to ask and seek similar subjects.

Snowball sampling (ask for recommendations)

You cannot proactively seek out subjects.

Convenience sampling (use who's available)

You are expert and there is no other choice.

Judgment sampling (guess a good-enough sample)

Ethnographic methodsWhen doing field-based observations, it is often impossible to intrude into the lives of people you are studying. Samples must thus be surreptitious and may be based more on who is available and willing to participate in any interviews or studies.

Best when Method

Focus is needed in particular group, location, subject, etc. Selective sampling (gut feel)

Theories are emerging and focused sampling may help clarify these.

Theoretical sampling (testing a theory)

You cannot proactively seek out subjects.

Convenience sampling (use who's available)

Type of Sampling

When to use it

Advantages

Disadvantages

Probability Strategies Simple Random Sampling

When the population members are similar to one another on important variables

Ensures a high degree of representativeness

Time consuming and tedious

Systematic Sampling

When the population members are similar to one another on important variables

Ensures a high degree of representativeness, and no need to use a table of random numbers

Less random than simple

random sampling

Stratified Random Sampling

When the population is heterogeneous and contains several different groups, some of which are related to the topic of the study

Ensures a high degree of representativeness of all the strata or layers in the population

Time consuming and tedious

Cluster Sampling

When the population consists of units rather than individuals

Easy and convenient

Possibly, members of units are

different from one another,

decreasing the techniques

effectiveness

Non-Probability Sampling

Convenience Sampling

When the members of the population are convenient to sample

Convenience and inexpensive

Degree of generalizability is

questionable

Quota Sampling

When strata are present and stratified sampling is not possible

Insures some degree of representativeness of all the strata in the population

Degree of generalizability is

questionable

Quantitative v.s Qualitative

Quantitative research has a much heavier burden than qualitative research when it comes to determining the sample group and assuring its similarities to the population. Quantitative research is about stating a particular hypothesis and then testing it by collecting data. Qualitative research explores and describes what is observed and then generates a theory based upon those observations.

The sample size of a statistical sample is the number of observations that

constitute itThe sample size is typically denoted by n and it is always a positive integer. No exact sample size can be mentioned here and it can vary in different research settings. However, all else being equal, large sized sample leads to increased precision in estimates of various properties of the population.

What should be the sample size?• Determining the sample size to be selected is an important

step in any research study. For example let us suppose that some researcher wants to determine prevalence of eye problems in school children and wants to conduct a survey.

• The important question that should be answered in all sample surveys is "How many participants should be chosen for a survey"? However, the answer cannot be given without considering the objectives and circumstances of investigations.

• The choosing of sample size depends on non-statistical considerations and statistical considerations. The non-statistical considerations may include availability of resources, manpower, budget, ethics and sampling frame. The statistical considerations will include the desired precision of the estimate of prevalence and the expected prevalence of eye problems in school children.

Sample Error Sampling error is the deviation of the selected sample from the true characteristics, traits, behaviors, qualities or figures of the entire population.Why Does This Error Occur? Sampling process error occurs because researchers draw different subjects from the same population but still, the subjects have individual differences. Keep in mind that when you take a sample, it is only a subset of the entire population; therefore, there may be a difference between the sample and population.The most frequent cause of the said error is a biased sampling procedure. Every researcher must seek to establish a sample that is free from bias and is representative of the entire population. In this case, the researcher is able to minimize or eliminate sampling error.Another possible cause of this error is chance. The process of randomization andprobability sampling is done to minimize sampling process error but it is still possible that all the randomized subjects are not representative of the population.The most common result of sampling error is systematic error wherein the results from the sample differ significantly from the results from the entire population. It follows logic that if the sample is not representative of the entire population, the results from it will most likely differ from the results taken from the entire population.

Sample Size and Sampling Error

Given two exactly the same studies, same sampling methods, same population, the study with a larger sample size will have less sampling process error compared to the study with smaller sample size. Keep in mind that as the sample size increases, it approaches the size of the entire population, therefore, it also approaches all the characteristics of the population, thus, decreasing sampling process error.

Ethical considered in”Data collection”ETHICS:: rules of behavior based on ideas about what is morally good

and bad .ethics : an area of study that deals with ideas about what is good and

bad behavior : a branch of philosophy dealing with what is morally right or wrong. .

a belief that something is very important Ethics may be divided into three major areas of study :

[1]

Meta-ethics, about the theoretical meaning and reference of moral propositions and how their truth values (if any) may be determinedNormative ethics, about the practical means of determining a moral

course of actionApplied ethics draws upon ethical theory in order to ask what a person

is obligated to do in some very specific situation, or within some particular domain of action (such as business)

Ethical Decision Making in Research

Although codes, policies, and principals are very important and useful, like any set of rules, they do not cover every situation, they often conflict, and they require considerable interpretation. It is therefore important for researchers to learn how to interpret, assess, and apply various research rules and how to make decisions and to act in various situations. The vast majority of decisions involve the straightforward application of ethical rules.

Principles of research ethics1.1 Participants’ rights Participants have a right to: • consent to participate, withdraw from, or refuse to take part in research projects; confidentiality: personal information or identifiable data should not be disclosed without participants’ consent; • security: data and samples collected should be kept secure and anonymised where appropriate; and safety: participants should not be exposed to unnecessary or disproportionate levels of risk. 1.2 Researchers’ obligations Researchers have an obligation to ensure that their research is conducted with: • honesty; • integrity; • minimal possible risk to participants and to themselves; and • cultural sensitivity.

References• Barnett, V. (2002). Sample survey: Principle and Methods (6thed). London: Arnold.

• Creswell, J. W. (2002). Educational research: Planning conducting , and quantitative and qualitative approaches to research Merrill/ Education.• Creswell, J.W.& Miller, D.(2002). Determining validity in qualitative inquiry. Theory into Practice,39(3),124-130• Heering, S.G.,West,B.(2010). Applied survey Data Analysis. Boca Raton:Chapman & Hall/ CRC.• Lynn, P. (2009). Methodology of Longitudinal Surveys: chichester:Wiley.