Random sampling is the purest form of probability sampling. Each member of the population has an equal and known chance of being selected. When there are very large populations, it is often difficult or impossible to identify every member of the population, so the pool of available subjects becomes biased. Systematic sampling is often used instead of random sampling. It is also called an Nth name selection technique. After the required sample size has been calculated, every Nth record is selected from a list of population members. As long as the list does not contain any hidden order, this sampling method is as good as the random sampling method. Its only advantage over the random sampling technique is simplicity. Systematic sampling is frequently used to select a specified number of records from a computer file. Stratified sampling is commonly used probability method that is superior to random sampling because it reduces sampling error. A stratum is a subset of the population that share at least one common characteristic. Examples of stratums might be males and females, or managers and non-managers. The researcher first identifies the relevant stratums and their actual representation in the population. Random sampling is then used to select a sufficient number of subjects from each stratum. "Sufficient" refers to a sample size large enough for us to be reasonably confident that the stratum represents the population. Stratified sampling is often used when one or more of the stratums in the population have a low incidence relative to the other stratums. Convenience sampling is used in exploratory research where the researcher is interested in getting an inexpensive approximation of the truth. As the name implies, the sample is selected because they are convenient. This nonprobability method is often used during preliminary research efforts to get a gross estimate of the results, without incurring the cost or time required to select a random sample. Judgment...

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INTERMEDIATE MICROECONOMICS
SAMPLINGTECHNIQUES
INTRODUCTION
A sample is a unit or subset of selection from a larger population that is used in studying to draw conclusions regarding the whole population. A sample is usually selected from the population because it is not easy to study the entire population at once and the cost of doing so may be very high. The sample should be the best representation of the whole population to enable accurate outcomes and accurate decisions made from the findings. Before sampling, the population should be clearly defined to ensure that the correct sample is selected for accuracy.
Sampling, therefore, is the process used in statistics in which a predetermined number of observations will be taken from a large population. It is the selection of units from a population of interest so that by studying it, we may generalize the findings back to the population from which the sample was obtained. The methodology to be used in sampling will depend on the type of analysis being performed. The methods include the following:-
1. SIMPLE RANDOM SAMPLING
Simple Random Sampling is obtained in such a way that each element of the population is given equal probability of being selected as a subject. The process is done in a single step with each subject selected independently of the rest of the members of the population. There are...

...UNIVERSITY OF NAIROBI
COLLEGE OF EDUCATION AND EXTERNAL STUDIES
SCHOOL OF CONTINUING AND DISTANCE EDUCATION
DEPARTMENT OF EXTRA-MURAL STUDIES.
LDP603: RESEARCH METHODS GROUP ASSIGNMENT
GROUP 5 QUESTION: DISCUSS THE VARIOUS PROBABILITY AND NON-PROBABILITY SAMPLINGTECHNIQUES USED IN RESEARCH.
GROUP 5 (A) MEMBERS
|S/NO |SURNAME |OTHER NAMES |REG. NO |SIGNATURE |
| |GICHOHI |BENARD MUTAHI |L50/64207/2010 | |
| |AYUYA |ANDREW ANGAYA |L50/64684/2010 | |
| |WAHINYA |COSMUS KIRORI |L50/63829/2010 | |
| |OSUMBAH |LILIAN ACHIENG’ |L50/64090/2010 | |
| |CHEBOI |ANDREW KIMUTAI |L50/64237/2010 | |
| |OGUDI |PETER ONYANGO |L50/63654/2010 | |
| |NJAU |JOSEPH NJENGA...

...ANSWER:
Sampling is that part of statistical practice concerned with the selection of an unbiased or random subset of individual observations within a population of individuals intended to yield some knowledge about the population of concern, especially for making predictions based on the statistical inference (Ader, Mellenberg & Hand: 2008). There are quite a number of sampling methods that can be employed in research and these include simple randomsampling, systematic sampling, stratified sampling, cluster sampling, matched random sampling, quota sampling, convenience sampling, line intercept sampling, to mention just a few.
Simple Random Sampling:
In a simple random sample of a given size (elements are randomly chosen until a desired sample size is obtained), all such subsets of the frame are given an equal chance or probability. Each element of the population thus has an equal probability of selection: the frame is not subdivided or partitioned. Furthermore, any given pair of elements has the same chance of selection as any other pair and similarly for triples, quads and so on. This minimizes the bias and simplifies analysis of the results. However, simple random sampling method can be vulnerable to sampling error because the randomness of the selection may result in a sample that...

...a population is known as sample design. It describes various samplingtechniques and sample size. It refers to the technique or procedure the researcher would adopt in selecting items for the sample.
STEPS IN SAMPLE DESIGN
Type of universe
Sampling unit
Source List
Size of Sample
Parameters of Interest
Budgetary Constraint
Sampling Procedure
CRITERIA OF SELECTING A SAMPLING PROCEDURE
Inappropriate sampling frame
Defective measuring device
Non-Respondents
Indeterminancy principle
Natural bias in the reporting of data
CHARACTERISTICS OF A GOOD SAMPLE DESIGN
Sample design must result in a truly representative sample.
Sample design must be such which results in a small sampling error.
Sample design must be viable in the context of funds available for the research study.
Sample design must be such so that systematic bias can be controlled in a better way.
Sample should be such that the results of the sample study can be applied, in general, for the universe with a reasonable level of confidence.
Different types of sample designs
There are different type of sample designs based on two factors, the representation basis and the element selection technique. On the representation basis the sample may be probability sampling or it may be non probability sampling....

...Simple Random Sampling is done when every individual subject in the population has an equal chance of being selected for the sample, without any bias (Explorable). For example, if a researcher wants to represent the population as a whole, they can pick random numbers or names out a hat or use a program to randomly choose names so the information is not biased.
Stratified Sampling is performed by, dividing the population into at least two (or more) groups or sections, which share certain characteristics, called “strata” (Explorable). For example, a researcher who wants to compare the average economic status of different racial groups may use this technique in order to divide the population into groups based on race and ethnicities and then compare the whole average from each ethnic group.
Cluster Sampling is done by dividing the population into separate sections or “clusters” and then picks a cluster randomly and chooses all the members from those clusters for the sample (Explorable). For example, using a geographical cluster, in order to look at the academic performance of students. The researcher can divide Nassau County in Long Island into clusters based on the towns. Then, randomly select a certain number of these clusters or towns and include all the students from those clusters to be part of the sample.
Systematic Sampling is performed by, using and selecting a point at which to begin and then...

...Question 1:
discuss any five (5) common samplingtechniques used in business research. Support you answer with relevant examples.
Simple random sampling:
The simple random sampling is one of the most widely-used random sampling method. The term “random” here does not mean a haphazard selection as many people think. The “random” in this method means each member of the population has equal opportunities being chosen be subject and no one in the identified population who could not be selected in this method. For example, the teacher wants to choose 5 people in QTB class to stand up and introduce themselves.
In order to perform random sampling, each member has to have a specific number as an ID, and those number are put in a random sample list or termed sampling frame. In the example, sampling frame would be the class list. The mechanical and primitive method would be the lottery method. Each number is placed in a bowl or a container and mixed thoroughly. After that, the researcher picks numbers tags from the container without any awareness of what numbers that are. All the individuals bearing the numbers picks are the subjects for the study. Thank to advance technology; another way to perform this sampling would be using computer or calculator to do a random selection from the population.
There are two types: sampling...

...Sampling and Sampling Methods
There are many research questions we would like to answer that involve populations that are too large to consider learning about every member of the population. How have wages of European workers changed over the past ten years?
Questions such as this are important in understanding the world around us, yet it would be impractical, if not impossible, to measure the wages of all European workers. Generally, in answering such questions, social scientists examine a fraction of the possible population of interest, drawing statistical inferences from this fraction. The selection process used to draw such a fraction is known as sampling, while the group contained in the fraction is known as the sample.
It is not only statisticians or quantitative researchers that sample. Journalists who select a particular case or particular group of people to highlight in a news story are engaging in a form of sampling. Most of us, in our everyday lives, do some sampling, whether we realize it or not. Although you may not have listened to all the songs of a particular band or singer, you likely would be able to form an opinion about the songs from such artist by hearing a few of them. In making such inferences you've relied on a subset of entities (some songs of an artist) to generalize to a larger group (all songs by an artist). You've sampled.
Methods of Sampling
We may then...

...Probability Sampling Cultural Studies Essay
A probability sampling method is any method of sampling that utilizes some form of random selection. In order to have a random selection method, you must set up some process or procedure that assures that the different units in your population have equal probabilities of being chosen. Humans have long practiced various forms of random selection, such as picking a name out of a hat, or choosing the short straw. These days, we tend to use computers as the mechanism for generating random numbers as the basis for random selection.
Probability sampling methods are those in which every item in the universe has a known chance, or probability of being chosen for sample. This implies that the selection of the sample items is independent of the person making the study that is the sampling operation is controlled so objectively that the items will be chosen strictly at random.
Types of probability sampling
Simple Random Sampling: The simplest form of random sampling is called simple random sampling. Neither of these mechanical procedures is very feasible and, with the development of inexpensive computers there is a much easier way. Simple random sampling is simple to accomplish and is easy to explain to others. Because simple random sampling is a fair way to select a sample, it is...