Presentation Part II.

ISSUES TO CONSIDER: POPULATION, SAMPLING, ETHICS

Prepared By: Abdurrahman Abdalla

ID Number: 20145652

Supervised by: Dr. ÇİSE ÇAVUŞOĞLU

Fall 2014/2015

•Table of Contents

The difference between the Probability and Non-

probability sampling

The difference between sampling in quantitative and

qualitative research

The statistical sampling techniques

Concerns in Statistical Sampling and Sample error

The meaning of “data ethics”, ethical decision making

and Principles of research ethics

References

What is the difference between probability and non-probability

sampling?

The difference between Probability and Non-probability sampling

Probability sampling

Probability sampling involves the selection of a sample from a population, based on the principle of randomization or chance. Probability sampling is more complex, more time-consuming and usually more costly than non-probability sampling. There are several different ways in which a probability sample can be selected. The method chosen depends on a number of factors, such as the available sampling frame, how spread out the population is, how costly it is to survey members of the population and how users will analyze the data.

In non-probability sampling there is an assumption that there is an even distribution of characteristics within the population. This is what makes the researcher believe that any sample would be representative and because of that, results will be accurate. In non-probability there is no way to estimate the probability of any one element being included in the sample.

Non-probability sampling

Simple random sampling

Systematic sampling

Sampling with probability proportional to size

Stratified sampling

Cluster sampling

Multi-stage sampling

Multi-phase sampling

The most Common Types of Probability Sampling

Convenience or haphazard sampling

Volunteer sampling

Judgment sampling

Quota sampling

The most common types of Non-probability sampling :

The differences between sampling in quantitative and qualitative research

Quantitative research

In quantitative research you attempt to select a sample in such a way that it is unbiased and represents the population from where it is selected.

In qualitative research, number considerations may influence the selection of a sample such as: the ease in accessing the potential respondents; your judgement that the person has extensive knowledge about an event or a situation of interest to you; how typical the case is of a category of individuals or simply that it is totally different from the others.

Qualitative research

The purpose of sampling in quantitative research is to draw inferences about the group from which you have selected the sample.

In quantitative research you are guided by a predetermined sample size that is based upon a number of other considerations in addition to the resources available.

In qualitative research it is designed either to gain in-depth knowledge about a situation/ event or to know as much as possible about different aspects of an individual on the assumption that the individual is typical of the group and hence will provide insight into the group.

In qualitative research you do not have a predetermined sample size but during the data collection phase you wait to reach a point of data saturation.

Quantitative research Qualitative research

Considerable importance is placed on the sample size in quantitative research, depending upon the type of study and the possible use of the findings. This is based upon the principle that a larger sample size will ensure the inclusion of people with diverse backgrounds, thus making the sample representative of the study population.

In quantitative research, randomization is used to avoid bias in the selection of a sample and is selected in such a way that it represents the study population.

The sample size in qualitative research does not play any significant role as the purpose is to study only one or a few cases in order to identify the spread of diversity and not its magnitude.

In qualitative research no such attempt is made in selecting a sample .You purposely select ' information-rich' respondents who will provide you with the information you need.

Quantitative research Qualitative research

Statistical Sampling Techniques

Statistical sampling techniques: are the strategies applied by researchers during the statistical sampling process.

This process is done when the researcher aims to draw conclusions for the entire population after conducting a study on a sample taken from the same population.

Concerns in Statistical Sampling

Representativeness

Practicability

Sampling Risks

Representativeness

This is the primary concern in statistical sampling. The sample obtained from the population must be representative of the same population.This can be accomplished by using randomized statistical sampling techniques or probability sampling like cluster sampling and stratified sampling. The reason behind representativeness being the primary concern in statistical sampling is that it allows the researcher to draw conclusions for the entire population. If the sample is not representative of the population, conclusions cannot be drawn since the results that the researcher obtained from the sample will be different from the results if the entire population is to be tested.

Practicability of statistical sampling techniques allows the researchers to estimate the possible number of subjects that can be included in the sample, the type of sampling technique, the duration of the study, the number of materials, ethical concerns, availability of the subjects/samples, the need for the study and the amount of workforce that the study demands.All these factors contribute to the decisions of the researcher regarding to the study design.

Practicability

There are two types of sampling risks, first is the risk of incorrect acceptance of the research hypothesis and the second is the risk for incorrect rejection. These risks pertain to the possibility that when a test is conducted to a sample, the results and conclusions may be different from the results and conclusions when the test is conducted to the entire population.

The risk of incorrect acceptance pertains to the risk that the sample can yield a conclusion that supports a theory about the population when it is actually not existent in the population.

On the other hand, the risk of incorrect rejection pertains to the risk that the sample can yield a conclusion that rejects a theory about the population when in fact, the theory holds true in the population.

Sampling Risks

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

that constitute it:

The 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 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? 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 and probability 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 from the results of 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.

THE MEANING OF “DATA ETHICS”

Ethics: (derived from the Greek ethos, meaning character, custom, or usage), or morality (from the Latin synonym meaning manner, custom, or habit), is the philosophical study of normative behavior, the "shoulds" and "oughts," the "rights" and "wrongs," of our conduct. Research ethics is a kind of applied of practical ethics, meaning that it attempts to resolve not merely general issues but also specific problems that arise in the conduct of research. Its goal is to determine the moral acceptability or appropriateness of specific conduct and to establish the actions that moral agents ought to take in particular situation. Research ethics is therefore not merely theoretical. It aims to establish practical moral norms and standards for the conduct of the research. This is the most common way of defining "ethics": norms for conduct that distinguish between acceptable and unacceptable behavior.(David B. Resnik, J.D., Ph.D.).

Ethics: is commonly defined as the rule of behavior or norms of conduct that differentiate between acceptable and unacceptable practices. Guidance of scientists by an appropriate ethical compass is paramount in research because scientists occupy a unique position of trust with the readers/users of their data.(Mike Brown 2014)

THE MEANING OF “DATA ETHICS”

Ethics may be divided into three major areas of study:

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. 

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 anonymous where appropriate; and safety: participants should not be exposed to unnecessary or disproportionate levels of risk.

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.

Principles of research ethics

Thank You

Abdurrahman Abdalla

References

Creswell, J.W.& Miller, D,. (2002). Determining validity in qualitative

inquiry. Theory into Practice, 39(3), 124-130.

Creswell, J. W. (2002). Educational research: Planning conducting , and

quantitative and qualitative approaches to research Merrill/Education.

Explorable Psychology Experiments Published on Explorable.com

(https://explorable.com/statisticalsampling-techniques)

Mike Brown. (2014). Importance and impact of research ethics on industry.

Kansas City Convention Center.

Ranjit Kumar. (2011). Research Methodology, Third Edition.