Cluster Sampling
Cluster sampling, also called block sampling. In cluster sampling, the population that is being sampled is divided into groups called clusters. Instead of these subgroups being homogeneous based on selected criteria as in stratified sampling, a cluster is as heterogeneous as possible to matching the population. A random sample is then taken from within one or more selected clusters. For example, if an organization has 30 small projects currently under development, an auditor looking for compliance to the coding standard might use cluster sampling to randomly select 4 of those projects as representatives for the audit and then randomly sample code modules for auditing from just those 4 projects. Cluster sampling can tell us a lot about that particular cluster, but unless the clusters are selected randomly and a lot of clusters are sampled, generalizations cannot always be made about the entire population. For example, random sampling from all the source code modules written during the previous week, or all the modules in a particular subsystem, or all modules written in a particular language may cause biases to enter the sample that would not allow statistically valid generalization.

Advantages
üThere is no need to have a sampling frame for the whole population. üusually less costly comparing to random sampling such as stratified üresearcher can increase sample size with this technique

Disadvantages
üSelection may be biased since the sampling is not random
üTechnique is the least representative of the population
üThis is also probability sampling with a possibility of high sampling error Quota Sampling
In quota sampling, the population is first segmented into mutually exclusive sub-groups, just as in stratified sampling. Then judgment is used to select the subjects or units from each segment based on a specified proportion. For example, an interviewer may be told to sample 200 females and 300 males between the age of 45 and 60. It...

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DataCollectionMethods.
Introduction
Datacollection is the process of gathering and measuring information on variables of interest, in an established systematic fashion that enables one to answer stated research questions, test hypotheses, and evaluate outcomes.
DataCollection Techniques include the following:
Personal Interviews
Conducting personal interviews is probably the bestmethod of datacollection to gain first hand information. It is however, unsuitable in cases where there are many people to be interviewed and questioned.
Questionnaires
Questionnaires are good methods of datacollection when there is a need for a particular class of people to be questioned. The researcher can prepare a questionnaire according to the data he requires and send it to the responders.
Detailed observation
Data can also most effectively be obtained with means of observational skills. The researcher can visit a place and take down details of all that he observes which is actually required for aiding in his research. Here, the researcher has to make sure that what he is observing is real.
Group Discussions
Group discussions are good techniques where the researcher has to know what the people in a group think. He can come to a conclusion based on the group...

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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 samplingmethods:
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 Random Sampling
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 Random sampling:
In systematic sampling, we...

...Samplingmethods[edit]
Within any of the types of frame identified above, a variety of samplingmethods can be employed, individually or in combination. Factors commonly influencing the choice between these designs include:
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
Simple random sampling [edit]
Main article: Simple random sampling
In a simple random sample (SRS) of a given size, all such subsets of the frame are given an equal probability. Furthermore, any given pair of elements has the same chance of selection as any other such pair (and similarly for triples, and so on). This minimises bias and simplifies analysis of results. In particular, the variance between individual results within the sample is a good indicator of variance in the overall population, which makes it relatively easy to estimate the accuracy of results.
However, SRS can be vulnerable to sampling error because the randomness of the selection may result in a sample that doesn't reflect the makeup of the population. For instance, a simple random sample of ten people from a given country will on average produce five men and five women, but any given trial is likely to overrepresent one sex and underrepresent the...

...the researcher used Quantitative datacollectionmethods. Using qualitative datacollectionmethod, it rely on random sampling and structured datacollection instruments that fit diverse experiences into predetermined response categories. They produce results that are easy to summarize, compare, and generalize. Quantitative research is concerned with testing hypotheses derived from theory and/or being able to estimate the size of a phenomenon of interest. Depending on the research question, participants may be randomly assigned to different treatments. If this is not feasible, the researcher may collect data on participant and situational characteristics in order to statistically control for their influence on the dependent, or outcome, variable. If the intent is to generalize from the research participants to a larger population, the researcher will employ probability sampling to select participants.
From this research, the researcher used questionnaires and surveying technique in collecting data. In the surveying techniques, it involves direct questioning of respondents about price. The researcher can choose whether to present the respondent with a range of possible prices, or force a response with no point of reference other than the concept and the question. While, for the questionnaires, researcher...

...Sampling and SamplingMethods
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...

...METHODS OF DATACOLLECTION
BY
ADEDOYIN SAMUEL ADEBAYO
INTERNATIONAL BLACK SEA UNIVERSITY TBILISI - GEORGIA
MA IN EDUCATION
STUDENT NO:12500151
LECTURER: PROF. IRINA BAKHTADZE
METHODS OF COLLECTING DATA
Introduction:
DataCollection is an important aspect of any type of research study. Inaccurate datacollection can impact the results of a study and ultimately lead to invalid results.
Datacollectionmethods for impact evaluation vary along a continuum. At the one end of this continuum are quantitative methods and at the other end of the continuum are qualitative methods for datacollection.
Bakhtadze (2012:82) ‘When you have decided on a topic, refined it and specified objectives, you start considering the ways of collecting the evidence you require. The initial question that guides you is: “What do I need to know to answer my research problem? Why do I need it?” After you have answered the question you start choosing the best ways of collecting information. Researchers next decide how they are going to collect their empirical research data. That is they decide what method of datacollection (test, questionnaires, focus group, observation, interviews) they are going...

...DRC 24 Marketing Research
1. Explain with appropriate examples the basic methods of collection of marketing data?
DataCollection in Marketing Research is a detailed process in which a planned search for all relevant data is made by researcher. Datacollection is an important step in the market research process. It involves gathering information about customers, competitors, and the market to help companies improve existing products and services and launch new products or services, expand into new markets, and create marketing plans. This process can be performed on a large or small scale and can involve both qualitative and quantitative data. By utilizing the Internet, datacollection allows for a broad range of consumer feedback on behaviours, perceptions, needs, attitudes, and opinions. Datacollection projects range from simple habits and attitudes questionnaires, which gather data from large number of consumers, to complex in-home product testing, which gather in-depth consumer insight. Though datacollection by means of the Internet provides a cost-effective approach to market research, at times traditional...

...1.Single random sampling :
a. Definition:
Simple random sampling is the basic sampling technique where we select a group of subjects (a sample) for study from a larger group (a population). Each individual is chosen entirely by chance and each member of the population has an equal chance of being included in the sample. Every possible sample of a given size has the same chance of selection; i.e. each member of the population is equally likely to be chosen at any stage in the sampling process.
b. Advantage:
There are some advantages of using single random sampling :
Firstly, collecting the sample easily since every member is given equal opportunities of being chosen.
Another it requires minimum advance knowledge of the population.
And the key factor of simple random sampling is its representativeness of the population.
c. Disavantage :
However, sometimes random samplingmethod application impossible in practical terms.
First, it is difficult to be able to have a complete list of all the objects in the target population. For example, when you want prospective study on the injuries caused by traffic accidents, we can not know how many emergency patients will be there day or during the time we gather data.
Second, even with the full list of subjects it is sometimes difficult to randomly select a object. Suppose if we want to measure the...