There are many ways to select a random sample. Four of them are discussed below: Simple Random Sampling: In this sampling technique, each sample of the same size has the same probability of being selected. Such a sample is called a simple random sample. One way to select a simple random sample is by a lottery or drawing. For example, if we need to select 5 students from a class of 50, we write each of the 50 names on a separate piece of paper. Then, we place all 50 names in a hat and mix them thoroughly. Next, we draw 1 name randomly from the hat. We repeat this experiment four more times. The 5 drawn names make up a simple random sample. The second procedure to select a simple random sample is to use a table of random numbers, which has become an outdated procedure. In this age of technology, it is much easier to use a statistical package, such as Minitab, to select a simple random sample. Systematic Random Sampling: The simple random sampling procedure becomes very tedious if the size of the population is large. For example, if we need to select 150 households from a list of 45,000, it is very time consuming either to write the 45,000 names on pieces of paper or then select 150 households or to use a table of random numbers. In such cases, it is more convenient to use systematic random sampling. Stratified Random Sampling: Suppose we need to select a sample from the population of a city, and we want households with different income levels to be proportionately represented in the sample. In this case, instead of selecting a simple random sample or a systematic random sample, we may prefer to apply a different technique. First, we divide the whole population into different groups based on income levels. Thus, whenever we observe that a population differs widely in the possession of a characteristic, we may prefer to divide it into different strata and then select one sample from each stratum. We can divide the population on the basis of any characteristic, such...

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Sampling methodologies
Sampling
It may be defined as a process of selecting units that may be people, organizations etc, from a larger whole i.e. from a population of interest, so that by studying the sample we may come up with general characteristics of the entire population under consideration.
Types of sampling methods:
Probability sampling
Probability sampling is a type ofsampling that includes random selection. And in order to achieve random selection, it must be made sure that different units of population have equal probability of being chosen.
Some relevant terms:
N = the number of cases in the sampling frame
n = the number of cases in the sample
f = n/N = the sampling fraction
I] Simple RandomSampling
It is the simplest type of probability sampling, wherein the probability of an element getting selected is directly proportional to its frequency. It is equivalent to say that every element has the same probability of getting chosen if they have the same frequency. For example in a random number generator each element has the same frequency and hence the same probability i.e. f=n/N.
It may be the simplest method but it is not considered as the statistically efficient.
II] Systematic Randomsampling:...

...Simple random sample (SRS)
In statistics, a simple random sample from a population is a sample chosen randomly, so that each possible sample has the same probability of being chosen. One consequence is that each member of the population has the same probability of being chosen as any other. In small populations such sampling is typically done "without replacement", i.e., one deliberately avoids choosing any member of the population more than once. Although simple randomsampling can be conducted with replacement instead, this is less common and would normally be described more fully as simple randomsampling with replacement.
Conceptually, simple randomsampling is the simplest of the probability samplingtechniques. It requires a complete sampling frame, which may not be available or feasible to construct for large populations. Even if a complete frame is available, more efficient approaches may be possible if other useful information is available about the units in the population.
Advantages are that it is free of classification error, and it requires minimum advance knowledge of the population. It best suits situations where the population is fairly homogeneous and not much information is available about the population. If these conditions are not true, stratified sampling may be a better...

...SAMPLINGSampling is the act, process, or technique of selecting a suitable sample, or a representative part of a population for the purpose of determining parameters or characteristics of the whole population.
REASONS FOR SAMPLING
There are six main reasons for sampling instead of doing a census. These are;
* Economy
* Timeliness
* The large size of many populations
* Inaccessibility of some of the population
* Destructiveness of the observation
* Accuracy or Reliability
Economy
The economic advantage of using a sample in research obviously, taking a sample requires fewer resources than a census. Unit cost of collecting data in the case of census is significantly less then in the case of sampling for example: In case of census is taka 200, while in the case of sampling is taka 1,000 but due to the larger number of items the total cost involve in the case of census of census is significantly higher then in the case of sampling.
Timeliness
Unit time involve in the case of sampling then in the case census but due to the larger size of population total time involve in the case of census in significantly higher then in the case of census.
Large size of many populations
In some cases the size of the population is extremely large. All of them are not treaseable due in traveling, disease, death, mental abnormality, prisoners etc....

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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 RANDOMSAMPLING
Simple RandomSampling 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...

...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...

...Types of Sampling
In applications:
Probability Sampling: Simple RandomSampling, Stratified RandomSampling, Multi-Stage Sampling
* What is each and how is it done?
* How do we decide which to use?
* How do we analyze the results differently depending on the type of sampling?
Non-probability Sampling: Why don't we use non-probabilitysampling schemes? Two reasons:
* We can't use the mathematics of probability to analyze the results.
* In general, we can't count on a non-probability sampling scheme to produce representative samples.
In mathematical statistics books (for courses that assume you have already taken a probability course):
* Described as assumptions about random variables
* Sampling with replacement versus sampling without replacement
What are the main types of sampling and how is each done?
Simple RandomSampling: A simple random sample (SRS) of size n is produced by a scheme which ensures that each subgroup of the population of size n has an equal probability of being chosen as the sample.
Stratified RandomSampling: Divide the population into "strata". There can be any number of these. Then choose a simple random sample from each...

...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 RandomSampling: The simplest form of randomsampling is called simple randomsampling. Neither of these mechanical procedures is very feasible and, with the development of inexpensive computers there is a much easier way. Simple randomsampling is...

...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...