Empirical Data Collection Methods

Explanation
The word 'Empirical' refers to knowledge or information that is based on observation, measurement, and verification. It emphasizes the importance of collecting data through careful observation, quantifying it through measurement, and then verifying the results to ensure accuracy. This approach is commonly used in scientific research to gather evidence and draw conclusions based on objective data rather than subjective opinions or assumptions.

Explanation
Primary data is the best type of data suited to empirical research. This is because primary data is collected directly from original sources through surveys, experiments, observations, or interviews. It is firsthand information that is specific to the research question and has not been previously collected or analyzed by others. Primary data allows researchers to have control over the data collection process and ensures that the data is relevant and accurate for the specific research study. Therefore, primary data is considered more reliable and valid for empirical research compared to secondary data, which is already existing data collected by others.

Explanation
Interviews are not an empirical/quantitative data collection tool because they involve direct interaction between the interviewer and the interviewee, allowing for open-ended responses and subjective interpretations. Unlike standardised tests, questionnaires, and rating scales, interviews do not typically involve structured or pre-determined questions with fixed response options. Instead, interviews allow for a deeper exploration of the interviewee's thoughts, feelings, and experiences, making them a qualitative data collection tool rather than a quantitative one.

Explanation
Fill in the blanks is not a close-ended type of question because it requires the respondent to provide their own answer instead of selecting from predetermined options. Close-ended questions, such as dichotomous, multiple choice, and ranking, provide a limited set of response options for the respondent to choose from.

Explanation
A Likert scale is a type of rating scale that is commonly used in surveys and questionnaires to measure people's attitudes, opinions, and perceptions. It consists of a series of statements or questions with response options ranging from strongly agree to strongly disagree. Each response is assigned a numerical value, typically ranging from 1 to 5, which allows for the conversion of qualitative data (attitudes and opinions) into quantitative data (numerical values). Therefore, the Likert scale is used to convert qualitative data to quantitative data.

Explanation
The combination of Multiple Choice (MC) and Rating questions is best suited for rich data collection. Multiple Choice questions provide a structured format that allows respondents to choose from a set of predefined options, ensuring consistency in responses. Adding a Rating question allows respondents to assign a numerical value or rate their satisfaction, preference, or opinion, providing more detailed and nuanced data. This combination enables researchers to gather both qualitative and quantitative information, leading to a more comprehensive understanding of the subject being studied.