Applied research is a research done with the intention of applying the results of the findings to solve specific problems ...
Quantitative Research attempts to measure something in precise. Quantitativeresearch methodologies answer questions like h...
Cluster Sampling is a probability sampling design in which the sample compromises   groups or chunks of elements with intr...
1. Primary sources - Primary sources are raw data without interpretation that represents an official opinion. Examples of ...
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Glossary

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  1. 1. Applied research is a research done with the intention of applying the results of the findings to solve specific problems that are currently being experienced in the organization. Basic Research is research done chiefly to enhance the understanding of certain problems that commonly occur within an organization and seek methods of solving them Business research is a systematic and organized effort to investigate a specific problem encountered in the work setting that needs a solution A descriptive study is undertaken in order to ascertain and be able to describe the characteristics of the variables of interest in a situation. An exploratory study is undertaken when not much is known about the situation at hand, or no information is available on how similar problems or research issues have been solved in the past.The study is conducted to better comprehend the nature of the problem because very few studies might have been conducted in that area. Industry research is an important thing to do by a company to survive and succeed in today’s tight competition market. To do a research about a certain industry, the first thing to do is to collect all necessary data related to the industry. Here are the steps of conducting an Industry Research 1. Identify the industry 2. Locate industry surveys, overviews and reports 3. Find current news and in-depth articles about the Industry 4. Visit industry web sites and leading industry and trade associations 5. Look for business-to-business marketplaces 6. Make a list of leading companies/rankings 7. Find market share data and other industry statistics 8. Use 10-Ks from leading companies to gain industry insight 9. Compare company/industry norms and financial ratios 10. Putting it all together Research design is the blueprint for achieving objectives and answering questions. Choosing a design can be complicated because there are many varieties of methods, techniques, procedures, protocols, and sampling plans available. Research methodology is a conceptually broad array term that generally refers to strategies, techniques, or procedures used in applied, descriptive, or experimental studies. The main distinguishing characteristics of scientific research are:1. Purposiveness2. Rigor3. Testability4. Replicability5. Precision and Confidence6. Objectivity7. Generalizability8. Parsimony 0
  2. 2. Quantitative Research attempts to measure something in precise. Quantitativeresearch methodologies answer questions like how much, how often, how many,when, and who. Quantitative research is often used for theory testing.Quantitative research is often used for theory testing.Qualitative Research is designed to tell the researcher how and why things happenas they do. It aims to achieve an in-depth understanding of a situation.Qualitative research draws data from many sources, including the following:1. Published texts2. Organizations3. People4. Settings and environment5. Objects, artifacts, media products6. Events and happeningsQualitative research is also known as interpretive research because it seeks todevelop understanding through detailed description. If often builds theory but rarelytests it.Qualitative techniques are used at data collection and data analysis stages of aresearch project.Deduction- Deduction is a form of argument that intent to be conclusive. Theconclusion must necessarily follow from the reasons given.A deduction is valid if it is not possible for the conclusion to be false if the premisesare true. Induction- In Induction, there is no such strength of relationship between reasonsand conclusions.In Induction, we draw a conclusion from one or more particular facts or pieces ofevidence. The conclusion explains the facts, and the facts support the conclusion.Sampling is the process of selecting items from the population so that the samplecharacteristics can be generalized to the population. This process involves design choice andsample size decisions. Cluster Sampling is a probability sampling design in which the sample compromises groups or chunks of elements with intra-group heterogeneity and inter-group homogeneity. Double Sampling is a probability sampling design that involves the process of collecting information from a set of subjects twice, such as using a sample to collect preliminary information and later using a sub-sample of the primary sample for more information. Complex Probability Sampling is some probability sampling designs, which offer an alternative to the cumbersome, simple random sampling design.
  3. 3. Cluster Sampling is a probability sampling design in which the sample compromises groups or chunks of elements with intra-group heterogeneity and inter-group homogeneity. Convenience Sampling is a non-probability sampling design in which information or data for the research are gathered from members of the population that are conveniently accessible to the researcher. A Judgment Sampling is a purposive, non-probability sampling design in which the sample subject is chosen based on the individual’s ability to provide the type of special information needed by the researcher.Data mining is the process of discovering knowledge from databases that are beingstored in data marts or data warehouses. The purpose is to identify valid, novel,useful, and understandable patterns in data. Data mining searches large databasesfor essential information for managing an organization. Data mining involves five step processes: - Deciding between census and sample data - Identifying relationship within the data. - Modifying or transforming data. - Developing a model that explains the data relationship. - Testing the model’s accuracy. A data warehouse is an electronic storage for databases that organizes large volumes of data into categories to support retrieval, interpretation, and sorting by end users. It provides an accessible archive to support dynamic organizational intelligence applications. Data in a data warehouse must be continually updated to ensure that decision makers have access to the appropriate data for real-time decisions. The more accessible the databases in the data warehouse, the more likely a researcher will use them to reveal patterns.The dependent variable is the variable of primary interest to the researcher. It is the mainvariable that lends itself for investigation as a viable factor.An independent variable is one that influences the dependent variable. The influence can bein positive or negative way.An intervening variable is one that surfaces between the time the independent variables startoperating to influence the dependent variable and the time their impact is felt on it. It surfacesas a function of the independent variable(s) operating in any situation, and helps to explainthe influence of the independent variable(s) on the dependent variableThe moderating variable is one that has a strong contingent effect on the relationshipbetween independent variable and dependent variable.Information Sources are categorized into 3 levels:
  4. 4. 1. Primary sources - Primary sources are raw data without interpretation that represents an official opinion. Examples of primary sources are memos, letters, interviews, laws, regulations, census, etc. 2. Secondary sources - Secondary sources are interpretations of primary data. Examples of secondary data are encyclopedias, textbooks, handbooks, magazine articles, newspaper articles, etc. 3. Tertiary sources - Tertiary sources may be interpretations of a secondary source, but generally represented by indexes, bibliographies, and other finding tools such as Internet search engines. In organizational research, the following rating scales are often used:1. Dichotomous Scale2. Category Scale3. Likert Scale4. Numerical Scale5. Semantic Differential Scale6. Itemized Rating Scale7. Fixed or Constant Sum Rating Scale8. Stapel Scale9. Graphic Rating Scale10. Consensus Scale

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