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Research and Types

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Research:-Research is creative and systematic work undertaken to increase the stock of knowledge, including knowledge of humans, culture and society, and the use of this stock of knowledge to devise new applications. It is used to establish or
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  Research:- Research is creative and systematic work undertaken to increase the stock of  knowledge, including knowledge of humans, culture and society, and the use of this stock of knowledge to devise new applications. It is used to establish or confirm facts, reaffirm the results of previous work, solve new or existing problems, support theorems, or develop new theories. A research project may also be an expansion on past work in the field. Research projects can be used to develop further knowledge on a topic, or in the example of a school research project, they can be used to further a student's research prowess to prepare them for future jobs or reports. To test the validity of instruments, procedures, or experiments, research may replicate elements of prior projects or the project as a whole. The primary purposes of  basic research (as opposed to applied research)are documentation, discovery, interpretation, or the research and development (R&D) of methods and systems for the advancement of human knowledge. Approaches to research depend on epistemologies, which vary considerably both within and between humanities and sciences. There are several forms of research: scientific, humanities, artistic, economic, social, business, marketing, practitioner research, life, technological, etc. The scientific study of research practices is known as meta- research.  What are the types of research?  Following are the types of research methods: Basic research: A basic research definition is data collected to enhance knowledge. The main motivation is knowledge expansion. It is a non- commercial research that doesn’t facilitate in creating or inventing anything. For example: an experiment to determine a simple fact. Applied research: Applied research focuses on analyzing and solving real-life problems. This type refers to the study that helps solve practical problems using scientific methods. Studies play an important role in solving issues that impact the overall well-being of humans. For example: finding a specific cure for a disease. Problem oriented research: As the name suggests, problem-oriented research is conducted to understand the exact nature of a problem to find out relevant solutions. The term “problem” refers to multiple choices or issues when analyzing a situation. For example, revenue of a car company has decreased by 12% in the last year. The following could be the probable causes: there is no optimum production, poor quality of a product, no advertising, or economic conditions.  Problem solving research : This type of research is conducted by companies to understand and resolve their own problems. The problem-solving method uses applied research to find solutions to the existing problems. Qualitative research:  Qualitative research is a process that is about inquiry. It helps create in-depth understanding of problems or issues in their natural settings. This is a non-statistical method. Qualitative research is heavily dependent on the experience of the researchers and the questions used to probe the sample. The sample size is usually restricted to 6-10 people. Open-ended questions are asked in a manner that encourages answers that lead to another question or group of questions. The purpose of asking open-ended questions is to gather as much information as possible from the sample. The following are the methods used for qualitative research: 1.   One-to-one interview 2.   Focus groups 3.   Ethnographic research 4.   Content/ Text Analysis 5.   Case study research Quantitative research:  Qualitative research is a structured way of collecting data and analyzing it to draw conclusions. Unlike qualitative methods, this method uses a computational and statistical process to collect and analyze data. Quantitative data is all about numbers. Quantitative research involves a larger population —  more people means more data. With more data to analyze, you can obtain more accurate results. This method uses close-ended questions because the researchers are typically looking to gather statistical data. Online surveys, questionnaires, and polls are preferable data collection tools used in quantitative research. There are various methods of deploying surveys or questionnaires. Online surveys allow survey creators to reach large amounts of people or smaller focus groups for different types of research that meet different goals. Survey respondents can receive surveys on mobile phones, in emails, or can simply use the internet to access surveys.  Defining Research Data  Research data comes in many different formats and is gathered using a wide variety of methodologies. In this module, we will provide you with a basic definition and understanding of what research data are. We'll also explore how data fits into the scholarly research process. Many people think of data-driven research as something that primarily happens in the sciences. It is often thought of as involving a spreadsheet filled with numbers. Both of these beliefs are incorrect. Research data are collected and used in scholarship across all academic disciplines and, while it can consist of numbers in a spreadsheet, it also takes many different formats, including videos, images, artifacts, and diaries. Whether a psychologist collecting survey data to better understand human behavior, an artist using data to generate images and sounds, or an anthropologist using audio files to document observations about different cultures, scholarly research across all academic fields is increasingly data-driven. In our Data Literacy Modules, we will demonstrate the ways in which research data are gathered and used across various academic disciplines by discussing it in a very broad sense. We define research data as: any information collected, stored, and processed to produce and validate srcinal research results. Data might be used to prove or disprove a theory, bolster claims made in research, or to further the knowledge around a specific topic or problem. Types of Research Data  Data may be grouped into four main types based on methods for collection: observational, experimental, simulation, and derived. The type of research data you collect may affect the way you manage that data. For example, data that is hard or impossible to replace (e.g. the recording of an event at a specific time and place) requires extra backup procedures to reduce the risk of data loss. Or, if you will need to combine data points from different sources, you will need to follow best practices to prevent data corruption Observational Data  Observational data are captured through observation of a behavior or activity. It is collected using methods such as human observation, open-ended surveys, or the use of an instrument or sensor to monitor and record information -- such as the use of sensors to observe noise levels at the Mpls/St Paul airport. Because observational data are captured in real time, it would be very difficult or impossible to re-create if lost Experimental Data  Experimental data are collected through active intervention by the researcher to produce and measure change or to create difference when a variable is altered. Experimental data typically allows the researcher to determine a causal relationship and is typically projectable to a larger population. This type of data are often reproducible, but it often can be expensive to do so  Simulation Data  Simulation data are generated by imitating the operation of a real-world process or system over time using computer test models. For example, to predict weather conditions, economic models, chemical reactions, or seismic activity. This method is used to try to determine what would, or could, happen under certain conditions. The test model used is often as, or even more, important than the data generated from the simulation Derived / Compiled Data  Derived data involves using existing data points, often from different data sources, to create new data through some sort of transformation, such as an arithmetic formula or aggregation. For example, combining area and population data from the Twin Cities metro area to create population density data. While this type of data can usually be replaced if lost, it may be very time-consuming (and possibly expensive) to do so.
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