RESEARCH WORK

1. Research Design
2. Types of Research Design
3. Data
4. Sources of Data
5. Descriptive Research Design
6. Types of Descriptive Research Design
7. Sampling
8. Population
9. Stratum
10. Sample
11. Sample Size
12. Randomization
13. Sampling Unit
14. Target Population
15. Respondent Population
16. Sampling Design
17. Margin of Error
18. Probability / Level of Confidence
19. Probability Sampling Designs
20. Simple Random Sampling
21. Systematic Sampling
22. Stratified Sampling
23. Cluster Sampling
24. Multi-stage Sampling
25. Non-Probability Sampling Designs
26. Purposive Sampling
27. Convenience Sampling
28. Quota Sampling
29. Snowball Sampling

1. Research Design

a. The research design is a comprehensive master plan of the research study to be undertaken, giving a general statement of the methods to be used. The function of a research design is to ensure that requisite data in accordance with the problem at hand is collected accurately and economically. Simply stated, it is the framework, a blueprint for the research study which guides the collection and analysis of data. The research design, depending upon the needs of the researcher may be a very detailed statement or only furnish the minimum information required for planning the research project.
b. The research design refers to the overall strategy that you choose to integrate the different components of the study in a coherent and logical way, thereby, ensuring you will effectively address the research problem; it constitutes the blueprint for the collection, measurement, and analysis of data
2. Types of Research Design
a. There are four types of research designs which are broadly classified as:
i. 1) Exploratory Designs ii. 2) DescriptiveDesigns iii. 3) Quasi-Experimental Designs iv. 4) Experimental Designs
3. Data
a. factual information (as measurements or statistics) used as a basis for reasoning, discussion, or calculation
4. Sources of Data
a. Primary data- Data observed or collected directly from first-hand experience.
b. Secondary data Published data and the data collected in the past or other parties is called secondary data.

5. Descriptive Research Design
a. Descriptive research designs help provide answers to the questions of who, what, when, where, and how associated with a particular research problem; a descriptive study cannot conclusively ascertain answers to why. Descriptive research is used to obtain information concerning the current status of the phenomena and to describe "what exists" with respect to variables or conditions in a situation.

6. Types of Descriptive Research Design
a. Observational Method
i. With the observational method (sometimes referred to as field observation) animal and human behavior is closely observed. There are two main categories of the observational method — naturalistic observation and laboratory observation.
b. Case Study Method
i. Case study research involves an in-depth study of an individual or group of indviduals. Case studies often lead to testable hypotheses and allow us to study rare phenomena. Case studies should not be used to determine cause and effect, and they have limited use for making accurate predictions.
c. Survey Method
i. In survey method research, participants answer questions administered through interviews or questionnaires. After participants answer the questions, researchers describe the responses given. In order for the survey to be both reliable and valid it is important that the questions are constructed properly. Questions should be written so they are clear and easy to comprehend.
7. Sampling
a. the act, process, or technique of selecting a suitable sample; specifically : the act, process, or technique of selecting a representative part of a population for the purpose of determining parameters or characteristics of the whole population

8. Population
a. a group of individual persons, objects, or items from which samples are taken for statistical measurement

9. Stratum
a. a statistical subpopulation
10. Sample
a. a representative part or a single item from a larger whole or group especially when presented for inspection or shown as evidence of quality : specimen
b. a finite part of a statistical population whose properties are studied to gain information about the whole

11. Sample Size
a. The number of elements in the obtained sample
12. Randomization
a. to select, assign, or arrange in a random way

13. Sampling Unit
a. This is that element or set of elements considered for selection in some stage of sampling (same as the elements, in a simple single-stage sample). In a multi-stage sample, the sampling unit could be blocks, households, and individuals within the households.
14. Target Population
a. A particular group of people that is identified as the intended recipient of an advertisement, product, or campaign. Also called target audience.
b. Target population refers to the ENTIRE group of individuals or objects to which researchers are interested in generalizing the conclusions. The target population usually has varying characteristics and it is also known as the theoretical population.
15. Respondent Population
a. This is any complete, or the theoretically specified aggregation of study elements. It is usually the ideal population or universe to which research results are to be generalized.
b. the population in research to which the researchers can apply their conclusions. This population is a subset of the target population and is also known as the study population. It is from the accessible population that researchers draw their samples.

16. Sampling Design
a. This refers to a set of rules or procedures that specify how a sample is to be selected. This can either be probability or non-probability.
17. Margin of Error
a. refers to the precision needed by the researcher. A margin of error of 5 percent means that the actual findings could vary by as much as 5 points either positively or negatively.
18. Probability / Level of Confidence
a. refers to the percentage of all possible samples that can be expected to include the true population parameter.
b. The probability of an event is a measure of the likelihood that the event will occur.
19. Probability Sampling Designs
a. 1) A simple random sample
b. 2) A stratified sample
c. 3) A cluster sample
20. Simple Random Sampling
a. The simple random sample is the basic sampling method assumed in statistical methods and computations. To collect a simple random sample, each unit of the target population is assigned a number. A set of random numbers is then generated and the units having those numbers are included in the sample. For example, let’s say you have a population of 1,000 people and you wish to choose a simple random sample of 50 people. First, each person is numbered 1 through 1,000. Then, you generate a list of 50 random numbers (typically with a computer program) and those individuals assigned those numbers are the ones you include in the sample.
21. Systematic Sampling
a. In a systematic sample, the elements of the population are put into a list and then every kth element in the list is chosen (systematically) for inclusion in the sample. For example, if the population of study contained 2,000 students at a high school and the researcher wanted a sample of 100 students, the students would be put into list form and then every 20th student would be selected for inclusion in the sample. To ensure against any possible human bias in this method, the researcher should select the first individual at random. This is technically called a systematic sample with a random start.
22. Stratified Sampling
a. A stratified sample is a sampling technique in which the researcher divided the entire target population into different subgroups, or strata, and then randomly selects the final subjects proportionally from the different strata. This type of sampling is used when the researcher wants to highlight specific subgroups within the population. For example, to obtain a stratified sample of university students, the researcher would first organize the population by college class and then select appropriate numbers of freshmen, sophomores, juniors, and seniors. This ensures that the researcher has adequate amounts of subjects from each class in the final sample.
23. Cluster Sampling
a. Cluster sampling may be used when it is either impossible or impractical to compile an exhaustive list of the elements that make up the target population. Usually, however, the population elements are already grouped into subpopulations and lists of those subpopulations already exist or can be created. For example, let’s say the target population in a study was church members in the United States. There is no list of all church members in the country. The researcher could, however, create a list of churches in the United States, choose a sample of churches, and then obtain lists of members from those churches.
24. Multi-stage Sampling
a. Multistage sampling is a complex form of cluster sampling.
b. Using all the sample elements in all the selected clusters may be prohibitively expensive or not necessary. Under these circumstances, multistage cluster sampling becomes useful. Instead of using all the elements contained in the selected clusters, the researcher randomly selects elements from each cluster. Constructing the clusters is the first stage. Deciding what elements within the cluster to use is the second stage. The technique is used frequently when a complete list of all members of the population does not exist and is inappropriate.

25. Non-Probability Sampling Designs
a. 1) Convenience Sampling:- Where the researcher questions anyone who is available. This method is quick and cheap. However we do not know how representative the sample is and how reliable the result.
b. 2) Quota Sampling:- Using this method the sample audience is made up of potential purchasers of your product. For example if you feel that your typical customers will be male between 18-23, female between 26-30, then some of the respondents you interview should be made up of this group, i.e. a quota is given.
c. 3) The judgement sample:- A judgement sample is obtained according to the discretion of someone who is familiar with the relevant characteristics of the population.
26. Purposive Sampling
a. A purposive, or judgmental, sample is one that is selected based on the knowledge of a population and the purpose of the study. For example, if a researcher is studying the nature of school spirit as exhibited at a school pep rally, he or she might interview people who did not appear to be caught up in the emotions of the crowd or students who did not attend the rally at all. In this case, the researcher is using a purposive sample because those being interviewed fit a specific purpose or description.
27. Convenience Sampling
a. Where the researcher questions anyone who is available. This method is quick and cheap. However we do not know how representative the sample is and how reliable the result.
28. Quota Sampling
a. A quota sample is one in which units are selected into a sample on the basis of pre-specified characteristics so that the total sample has the same distribution of characteristics assumed to exist in the population being studied. For example, if you a researcher conducting a national quota sample, you might need to know what proportion of the population is male and what proportion is female as well as what proportions of each gender fall into different age categories, race or ethnic categories, educational categories, etc. The researcher would then collect a sample with the same proportions as the national population.
29. Snowball Sampling
a. A snowball sample is appropriate to use in research when the members of a population are difficult to locate, such as homeless individuals, migrant workers, or undocumented immigrants. A snowball sample is one in which the researcher collects data on the few members of the target population he or she can locate, then asks those individuals to provide information needed to locate other members of that population whom they know. For example, if a researcher wishes to interview undocumented immigrants from Mexico, he or she might interview a few undocumented individuals that he or she knows or can locate and would then rely on those subjects to help locate more undocumented individuals. This process continues until the researcher has all the interviews he or she needs or until all contacts have been exhausted.

REFERENCES:
• http://xperiencemedia.blogspot.co.nz/2009/12/sampling-methods-probability-sampling.html
• Babbie, E. (2001). The Practice of Social Research: 9th Edition. Belmont, CA: Wadsworth Thomson.
• http://en.wikipedia.org/wiki/Multistage_sampling
• http://www.uic.edu/classes/socw/socw560/Sampling1.htm
• (© 2013 Merriam-Webster, Incorporated)
• ( http://libguides.usc.edu/content.php?pid=83009&sid=818072)
• http://www.businessdictionary.com/definition/target-population.html#ixzz2JuHd37Ap
• Research Population - The Focus Group of a Scientific Query(explorable.com/research-population)