What is the method of gathering data that provide consistent and more precise information?
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Published on June 5, 2020 by Pritha Bhandari. Revised on September 19, 2022. Data collection is a systematic process of gathering observations or measurements. Whether you are performing research for business, governmental or academic purposes, data collection allows you
to gain first-hand knowledge and original insights into your research problem. While methods and aims may differ between fields, the overall process of data collection remains largely the same. Before you begin collecting data, you need to consider: To collect high-quality data that is relevant to your purposes, follow these four steps. Before you start the process of data collection, you need to identify exactly what you want to achieve. You can start by writing a
problem statement: what is the practical or scientific issue that you want to address and why does it matter? Next, formulate one or more research questions that precisely define what you want to find out. Depending on your research questions, you might need to
collect quantitative or qualitative data: If your aim is to test a hypothesis, measure something precisely, or gain large-scale statistical insights, collect quantitative data.
If your aim is to explore ideas, understand experiences, or gain detailed insights into a specific context, collect qualitative data. If you have several aims, you can use a mixed methods approach that collects both types of data. You decide to use a mixed-methods approach to collect both quantitative and qualitative data. Based on the data you want to collect, decide which method is best suited for your research. Carefully consider what method you will use to gather data that helps you directly answer your research questions. Scribbr editors not only correct grammar and spelling mistakes, but also strengthen your writing by making sure your paper is free of vague language, redundant words and awkward phrasing. See editing example Step 3: Plan your data collection proceduresWhen you know which method(s) you are using, you need to plan exactly how you will implement them. What procedures will you follow to make accurate observations or measurements of the variables you are interested in? For instance, if you’re conducting surveys or interviews, decide what form the questions will take; if you’re conducting an experiment, make decisions about your experimental design (e.g., determine inclusion and exclusion criteria). OperationalizationSometimes your variables can be measured directly: for example, you can collect data on the average age of employees simply by asking for dates of birth. However, often you’ll be interested in collecting data on more abstract concepts or variables that can’t be directly observed. Operationalization means turning abstract conceptual ideas into measurable observations. When planning how you will collect data, you need to translate the conceptual definition of what you want to study into the operational definition of what you will actually measure. Example of operationalizationYou have decided to use surveys to collect quantitative data. The concept you want to measure is the leadership of managers. You operationalize this concept in two ways:
Using multiple ratings of a single concept can help you cross-check your data and assess the test validity of your measures. SamplingYou may need to develop a sampling plan to obtain data systematically. This involves defining a population, the group you want to draw conclusions about, and a sample, the group you will actually collect data from. Your sampling method will determine how you recruit participants or obtain measurements for your study. To decide on a sampling method you will need to consider factors like the required sample size, accessibility of the sample, and timeframe of the data collection. Standardizing proceduresIf multiple researchers are involved, write a detailed manual to standardize data collection procedures in your study. This means laying out specific step-by-step instructions so that everyone in your research team collects data in a consistent way – for example, by conducting experiments under the same conditions and using objective criteria to record and categorize observations. This helps ensure the reliability of your data, and you can also use it to replicate the study in the future. Creating a data management planBefore beginning data collection, you should also decide how you will organize and store your data.
Step 4: Collect the dataFinally, you can implement your chosen methods to measure or observe the variables you are interested in. Examples of collecting qualitative and quantitative dataTo collect data about perceptions of managers, you administer a survey with closed- and open-ended questions to a sample of 300 company employees across different departments and locations.The closed-ended questions ask participants to rate their manager’s leadership skills on scales from 1–5. The data produced is numerical and can be statistically analyzed for averages and patterns. The open-ended questions ask participants for examples of what the manager is doing well now and what they can do better in the future. The data produced is qualitative and can be categorized through content analysis for further insights. To ensure that high quality data is recorded in a systematic way, here are some best practices:
Frequently asked questions about data collectionWhat is data collection? Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations. What are the benefits of collecting data? When conducting research, collecting original data has significant advantages:
However, there are also some drawbacks: data collection can be time-consuming, labor-intensive and expensive. In some cases, it’s more efficient to use secondary data that has already been collected by someone else, but the data might be less reliable. What is operationalization? Operationalization means turning abstract conceptual ideas into measurable observations. For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations. Before collecting data, it’s important to consider how you will operationalize the variables that you want to measure. Sources in this articleWe strongly encourage students to use sources in their work. You can cite our article (APA Style) or take a deep dive into the articles below. This Scribbr article
Is this article helpful?You have already voted. Thanks :-) Your vote is saved :-) Processing your vote... What is the best method for collecting information from a source?The most commonly used methods are: published literature sources, surveys (email and mail), interviews (telephone, face-to-face or focus group), observations, documents and records, and experiments.
Which of the following is data gathering method?The main techniques for gathering data are observation, interviews, questionnaires, schedules, and surveys.
What methods and instruments will you use to gather data to answer your research problem describe them remember to cite your references?Case Studies, Checklists, Interviews, Observation sometimes, and Surveys or Questionnaires are all tools used to collect data. It is important to decide the tools for data collection because research is carried out in different ways and for different purposes.
What do you call the person who gathers data using the observation method?Participant observers conduct their observations “from the inside”; that is, the researcher is an integral part of the environment being observed. Nonparticipant observers conduct their observations “from the outside”; the researcher does not interact with those being observed.
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