BAA290/OMA291 Chapter 4 - Types of Research Data - PDF

Chapter 4 – Types of Research Data BAA290/OMA291 Research Skills  Types of Data Classification According to its Source 1. Primary Data 2. Secondary Data  Primary Data Primary Data: Data collected by the investigator for a specific pur...

Chapter 4 – Types of Research Data BAA290/OMA291 Research Skills  Types of Data Classification According to its Source 1. Primary Data 2. Secondary Data  Primary Data Primary Data: Data collected by the investigator for a specific purpose. Such as: 1. Questionnaires 2. Interview 3. Observation 4. Case Studies 5. Life Histories 6. Action Research 7. Others  Advantages of Using Primary Data 1. The investigator collects data specific to the problem being studied. 2. No doubt on the quality of the data collected. 3. Get additional data during the study period; if needed. Disadvantages of Using Primary Data 1. The investigator has to deal with all the difficulties of data collection. - deciding why, what, how, when to collect - getting the data collected (personally or through others) - getting funding and dealing with funding agencies - ethical considerations (consent, permissions, etc.) 2. Making sure that the data collected is of a high standard. - all desired data is accurate - in required format - no fake or cooked up data - useless data 3. Cost of obtaining the data; Expensive  Secondary Data Secondary Data: Data collected by someone else for another purpose; but utilized by the investigator for another purpose. Data that already exists. Such as: 1. Previous Research 2. Official Statistics 3. Mass Media Products 4. Diaries 5. Letters 6. Government Reports 7. Web Information 8. Historical Data and Information  Advantages of Using Secondary Data 1. The data is already there; no difficulties of data collection. 2. Less expensive. 3. The investigator is not personally responsible for the quality of data.  Disadvantages of Using Secondary Data 1. The investigator cannot decide what is collected (if specific data about something is required). 2. Unsure of data quality; good or bad. 3. Getting additional data or clarification about something is not possible; most often.  Classification of Data Classifications according to its Nature 1. Quantitative: made with instruments such as rulers, balances, graduated cylinders, beakers, and thermometers. Numerical information; measurable numbers. 2. Qualitative: made with the use of your senses by observing the results. Descriptive information. Differences Between Qualitative Data and Quantitative Data