Primary Data And Secondary Collection In Research Methodology Pdf
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- Primary Sources of Data and Secondary Sources of Data
- Data Collection Methods
- The Three Ways of Primary Data Collection
- Secondary Data Analysis: Ethical Issues and Challenges
Primary Sources of Data and Secondary Sources of Data
Already have an account? Log in. Sign up. If you need more help, please contact our support team. Today businesses and organizations are connected to their clients, customers, users, employees, vendors, and sometimes even their competitors.
Data can tell a story about any of these relationships, and with this information, organizations can improve almost any aspect of their operations. Although data can be valuable, too much information is unwieldy, and the wrong data is useless. Luckily, organizations have several tools at their disposal for primary data collection. The methods range from traditional and simple, such as a face-to-face interview, to more sophisticated ways to collect and analyze data.
Some of the methods covered here are quantitative, dealing with something that can be counted. Others are qualitative, meaning that they consider factors other than numerical values. In general, questionnaires, surveys, and documents and records are quantitative, while interviews, focus groups, observations, and oral histories are qualitative.
There can also be crossover between the two methods. With JotForm, you can successfully utilize several of these methods, especially by using ready to use questionnaires and survey templates! Data analysis can take various formats. The method you choose depends on the subject matter of your research.
This is where qualitative data collection methods come into play. Qualitative data collection looks at several factors to provide a depth of understanding to raw data. While qualitative methods involve the collection, analysis, and management of data, instead of counting responses or recording numeric data, this method aims to assess factors like the thoughts and feelings of research participants.
There are three commonly used qualitative data collection methods: ethnographic, theory grounded, and phenomenological. Through this method, researchers veer away from the specific and practical questions that traditional market researchers use and instead observe the participants in a nondirected way. Ethnography helps fill in the blanks when a participant may not be able to articulate their desires or the reasons for their decisions or behaviors.
Instead of, or in addition to, asking why a participant acts a certain way, researchers use observation to understand the why behind these desires, decisions, or behaviors. Before this method, qualitative data analysis was actually done before any quantitative data was collected, so it was disconnected from the collection and analysis process.
An example of phenomenology is studying the experiences of individuals involved in a natural disaster. To analyze data from such an event, the researcher must become familiar with the data; focus the analysis on the subject matter, time period, or other factors; and categorize the data. Completing these tasks gives the researcher a framework for understanding how the natural disaster impacts people. Together, the understanding, focus, and organization help researchers identify patterns, make connections, interpret data, and explain findings.
Each of these qualitative data collection methods sheds light on factors that can be hidden in simple data analysis. Qualitative data is one way to add context and reality to raw numbers. Often, researchers find value in a hybrid approach, where qualitative data collection methods are used alongside quantitative ones.
Marketers, scientists, academics, and others may start a study with a predetermined hypothesis, but their research often begins with the collection of data. Initially, the collected data is unstructured. Various facts and figures may or may not have context. Quantitative analysis relates to evaluating a numerical result. A classic example is a survey, which asks questions to collect responses that shed light on trends, preferences, actions, opinions, and any other element that can be counted.
Quantitative data collection methods are popular because they are relatively straightforward. Using these methods, researchers ask questions to collect sets of facts and figures. Quantitative data is measurable and expressed in numerical form.
While this seems like a fairly simple concept, like many aspects of research, there are various approaches to quantitative data collection that depend on the particular research being conducted. Often, the researcher begins without a hypothesis and lets the data steer the direction of the study. A simple example of quantitative descriptive research is a study that collects and tabulates test scores. Descriptive research frequently uses charts and tables to illustrate results.
While a descriptive approach is often quantitative, it can be qualitative. A positive correlation is one in which two variables either increase or decrease at the same time. A negative correlation is when an increase in one variable means a decrease in another.
There is also a zero correlation result, in which the relationship between two variables is insignificant. Correlation helps make predictions based on historical relationships and in determining the validity and reliability of a study.
This is a positive correlation. Using the experimental method, researchers randomly assign participants in an experiment to either the control or treatment groups. In both of these types of studies, independent variables are manipulated.
Experimental methods are known for producing results that are both internally and externally valid, meaning that the study is conducted, or structured, well internal validity and the findings are applicable to the real world external validity. Quasi-experimental methods, on the other hand, produce results of questionable internal validity. There are a number of ways researchers can put different types of quantitative data collection into action without using experiments. Quantitative surveys enable researchers to ask closed-ended questions with a provided list of possible answers.
This method is easier for respondents, as they just pick from a list of responses. Because the questions and answers are standardized, researchers can use the results to make generalizations.
Closed-ended questions, however, can be limiting. A respondent may not see their answer in the given choices. Quantitative interviews are typically conducted face to face, over the phone, or via the internet. They enable researchers to not only collect information but also tailor the questions to the audience on the spot.
Since most research involves the collection of data, there are several methods for direct, or primary, data collection, including surveys, questionnaires, direct observations, and focus groups. While primary data collection is considered the most authoritative and authentic data collection method, there are several instances where secondary data collection methods can provide value. What is secondary data collection, and why would a researcher employ it in addition to primary data?
Second-hand data can add insight to a research project, and using secondary data is more efficient and less expensive than collecting primary data. Answering this question involves understanding how a lot of research is initiated today. For a variety of reasons, lots of governmental entities and agencies collect demographic and other information on people. Governments collect data through various means, sometimes as part of other activities. The census is a primary example of valuable governmental primary data collection that can be used as a secondary data collection method in other research studies.
Several nonprofit and governmental entities specialize in collecting data to feed the efforts of other researchers. Commercial sources include research and trade associations, such as banks, publicly traded corporations, and others. Educational institutions are also reliable sources of secondary data. Many colleges and universities have dedicated research arms that leverage data for educational purposes. This data can often assist others in unrelated studies. There is more to secondary data than the fact that it is cheaper than primary data; however, cost is a major reason why this data is used.
Sometimes primary data is unnecessary for a particular research goal. You should first determine whether or not your research questions have already been asked and answered. If so, you can devote your data collection budget to expand on what has already been determined through other unrelated projects. The cost of collecting primary data can be considerable. While using secondary data is cheaper, it also saves time. Time has a value of its own in research, allowing for greater emphasis on studying results.
Ultimately, using secondary data saves time and money, which facilitates a more in-depth study of the subject. Combined with primary research, secondary data can help researchers better understand their subjects and more efficiently prepare and organize results. If you asked someone completely unaware of data analysis how to best collect information from people, the most common answer would likely be interviews.
Almost anyone can come up with a list of questions, but the key to efficient interviews is knowing what to ask. Efficiency in interviewing is crucial because, of all the primary data collection methods, in-person interviewing can be the most expensive. There are ways to limit the cost of interviews, such as conducting them over the phone or through a web chat interface.
But sometimes an in-person interview can be worth the cost, as the interviewer can tailor follow-up questions based on responses in a real-time exchange.
Interviews also allow for open-ended questions. Compared to other primary data collection methods, such as surveys, interviews are more customizable and responsive. Observation involves collecting information without asking questions.
This method is more subjective, as it requires the researcher, or observer, to add their judgment to the data. But in some circumstances, the risk of bias is minimal. For example, if a study involves the number of people in a restaurant at a given time, unless the observer counts incorrectly, the data should be reasonably reliable. Variables that require the observer to make distinctions, such as how many millennials visit a restaurant in a given period, can introduce potential problems.
In general, observation can determine the dynamics of a situation, which generally cannot be measured through other data collection techniques. Observation also can be combined with additional information, such as video.
Sometimes you can collect a considerable amount of data without asking anyone anything. Document- and records-based research uses existing data for a study.
Data Collection Methods
Research does not always involve collection of data from the participants. There is huge amount of data that is being collected through the routine management information system and other surveys or research activities. The existing data can be analyzed to generate new hypothesis or answer critical research questions. This saves lots of time, money and other resources. Also data from large sample surveys may be of higher quality and representative of the population. However, there are certain ethical issues pertaining to secondary data analysis which should be taken care of before handling such data. Secondary analysis refers to the use of existing research data to find answer to a question that was different from the original work 2.
One of the major elements and basis of statistical research is data collection, where the most basic data that can be collected in this process is primary data. In other words, we can say that data is the basis of all statistical operations and primary data is the simplest of all data. Primary data is one of the 2 main types of data, with the second one being the secondary data. These 2 data types have important uses in research, but in this article, we will be considering the primary data type. We will introduce you to what primary data is, examples, and the various techniques of collecting primary data. Primary data is a type of data that is collected by researchers directly from main sources through interviews, surveys, experiments, etc.
Data collection 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. The data collection component of research is common to all fields of study including physical and social sciences, humanities, business, etc. While methods vary by discipline, the emphasis on ensuring accurate and honest collection remains the same. The importance of ensuring accurate and appropriate data collection Regardless of the field of study or preference for defining data quantitative, qualitative , accurate data collection is essential to maintaining the integrity of research. Both the selection of appropriate data collection instruments existing, modified, or newly developed and clearly delineated instructions for their correct use reduce the likelihood of errors occurring. Consequences from improperly collected data include. While the degree of impact from faulty data collection may vary by discipline and the nature of investigation, there is the potential to cause disproportionate harm when these research results are used to support public policy recommendations.
The Three Ways of Primary Data Collection
This chapter examines prerequisites for enabling reuse or secondary analysis of qualitative data informally known as SAQD that has not been collected by the analyst. The first part of the chapter provides an overview of what people are doing with existing data, from new analysis to revisiting one's own data, and what challenges face them in their quest. The second part poses questions that a secondary analyst can ask of data, such as, are the data to hand a good fit for the proposed project? The role of detective comes to mind, appraising the materials and examining provenance to satisfy oneself that there is adequate context surrounding the data and that the limitations
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Primary data is when the data is gathered directly from the genuine source. Basically, every information you gather from first-hand experience is primary data.
Secondary Data Analysis: Ethical Issues and Challenges
Secondary research is contrasted with primary research in that primary research involves the generation of data, whereas secondary research uses primary research sources as a source of data for analysis. Common examples of secondary research include textbooks , encyclopedias , news articles, review articles , and meta analyses. When conducting secondary research, authors may draw data from published academic papers, government documents, statistical databases, and historical records. The term is widely used in primary research , legal research and market research. The principal methodology in health secondary research is the systematic review , commonly using meta-analytic statistical techniques, but other methods of synthesis, like realist reviews and meta-narrative  reviews, have been developed in recent years. Such secondary research uses the primary research of others typically in the form of research publications and reports.
Secondary data refers to data that is collected by someone other than the primary user. Secondary data analysis can save time that would otherwise be spent collecting data and, particularly in the case of quantitative data , can provide larger and higher-quality databases that would be unfeasible for any individual researcher to collect on their own. However, secondary data analysis can be less useful in marketing research, as data may be outdated or inaccurate. Government departments and agencies routinely collect information when registering people or carrying out transactions, or for record keeping — usually when delivering a service. This information is called administrative data. A census is the procedure of systematically acquiring and recording information about the members of a given population. It is a regularly occurring and official count of a particular population.
Data collection is a process of collecting information from all the relevant sources to find answers to the research problem, test the hypothesis and evaluate the outcomes. Data collection methods can be divided into two categories: secondary methods of data collection and primary methods of data collection. Secondary data is a type of data that has already been published in books, newspapers, magazines, journals, online portals etc. There is an abundance of data available in these sources about your research area in business studies, almost regardless of the nature of the research area. Therefore, application of appropriate set of criteria to select secondary data to be used in the study plays an important role in terms of increasing the levels of research validity and reliability.
Qualitative data collection methods
В зависимости от уровня допуска они попадали в те отсеки банка данных, которые соответствовали сфере их деятельности. - Поскольку мы связаны с Интернетом, - объяснял Джабба, - хакеры, иностранные правительства и акулы Фонда электронных границ кружат вокруг банка данных двадцать четыре часа в сутки, пытаясь проникнуть внутрь. - Да, - сказал Фонтейн, - и двадцать четыре часа в сутки наши фильтры безопасности их туда не пускают. Так что вы хотите сказать. Джабба заглянул в распечатку. - Вот что я хочу сказать.
Мидж всегда думала, что директорский кабинет следовало оборудовать здесь, а не в передней части здания, где он находился. Там открывался вид на стоянку автомобилей агентства, а из окна комнаты для заседаний был виден внушительный ряд корпусов АНБ - в том числе и купол шифровалки, это вместилище высочайших технологий, возведенное отдельно от основного здания и окруженное тремя акрами красивого парка. Шифровалку намеренно разместили за естественной ширмой из высоченных кленов, и ее не было видно из большинства окон комплекса АНБ, а вот отсюда открывался потрясающий вид - как будто специально для директора, чтобы он мог свободно обозревать свои владения. Однажды Мидж предложила Фонтейну перебраться в эту комнату, но тот отрезал: Не хочу прятаться в тылу. Лиланд Фонтейн был не из тех, кто прячется за чужими спинами, о чем бы ни шла речь. Мидж открыла жалюзи и посмотрела на горы, потом грустно вздохнула и перевела взгляд на шифровалку. Вид купола всегда приносил ей успокоение: он оказался маяком, посверкивающим в любой час суток.
Так вы обратили внимание. - Конечно. Он работает уже шестнадцать часов, если не ошибаюсь. Чатрукьян не знал, что сказать. - Да, сэр. Шестнадцать часов.