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Data is a broad notion that involves any piece of information and comes in a wide range of formats, including numbers, text, and images. In general, data can be categorized as quantitative or qualitative. |
Data collection is the process of gathering information from various sources to answer research questions or test hypotheses. The importance of this process lies in its ability to provide reliable and valid data that can significantly influence the outcomes of a study. Data ought to be accurately reflected by using suitable methods, such as surveys and interviews, and ethical considerations should also be made.
Primary vs Secondary Data Collection
Primary data collection refers to collecting firsthand data on your own. This includes the gathering of data through surveys, interviews, observations, experiments, etc. Primary data is valuable and mostly customized for your research needs.
Secondary data collection involves the collection of data through secondary sources. For instance, assembling data from library databases like Statista or text from general databases and retrieving data from open sources like the HKSAR Census & Statistics Department.
Check out some recommended databases subscribed to by the library which you can export quantitative datasets for research purposes:
The database provides access to real-time market data, news, and company and industry information traded in more than 400 exchanges around the world. Coverage includes historical data for stocks, bonds, and currencies.
Maximum simultaneous user(s): 1
The database provides statistical data on many topics including media, business, finance, politics, society, technology and education. Sources include market reports, trade publications, scientific journals, and government databases. Data can be accessed by searching or browsing by industry, topic, country, digital market or infographic.
Data analysis is the process of examining, interpreting, and drawing conclusions from collected data, and it plays a critical role in transforming raw data into meaningful insights. Depending on the nature of research questions and the type of data collected, such as statistical or qualitative data, different methods would be applied for accurately interpreting results and presenting them in a compelling manner.
Various softwares are installed in library workstations with analytics and visualization features. They includes SAS, SPSS and Tableau. Visit this webpage for more information and where to locate them.
Effective data management is crucial for organising, storing, and securing research data, which directly impacts the integrity and accessibility of the research. A well-structured data management plan helps researchers maintain consistency and organisation, making it easier to retrieve and analyse data later. This aspect is vital for ensuring compliance with data sharing policies and for the long-term preservation of research findings, ultimately enhancing the reproducibility and credibility of the work.
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