Data Collection & Analysis Flashcards
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Read the first 9 Data Collection & Analysis flashcards as text
What is the purpose of data collection in research?
Answer: To gather information for analysis
Data collection is the systematic process of gathering and measuring information on variables of interest in a research study. Its primary purpose is to obtain raw data that can then be analyzed to answer research questions, test hypotheses, and ultimately draw meaningful conclusions.
Which of the following is a quantitative data collection method?
Answer: Surveys with closed-ended questions
Quantitative data collection methods focus on numerical data that can be statistically analyzed. Surveys with closed-ended questions, such as multiple-choice or rating scales, are designed to collect measurable data from a large sample, making them a prime example of a quantitative approach.
What is data triangulation?
Answer: Using multiple methods or data sources to ensure accuracy
Data triangulation is a research technique that involves using multiple data sources, methods, investigators, or theories to study the same phenomenon. This approach enhances the validity and reliability of research findings by providing a more comprehensive and robust understanding of the subject matter.
What tool is commonly used in statistical data analysis?
Answer: SPSS
SPSS (Statistical Package for the Social Sciences) is a widely used software program for statistical analysis in social science, health, and business research. It provides a comprehensive set of tools for data management, statistical analysis, and reporting, making it invaluable for quantitative researchers.
Why is it important to analyze data after collection?
Answer: To identify patterns and make informed conclusions
Data analysis is crucial after collection because it transforms raw data into understandable insights. By systematically examining, cleaning, transforming, and modeling data, researchers can identify significant patterns, trends, and relationships, which are essential for drawing valid and informed conclusions related to their research questions.
What is the role of coding in qualitative data analysis?
Answer: To group data into meaningful categories
In qualitative data analysis, coding is the process of identifying, organizing, and categorizing segments of text or other data into themes or concepts. This systematic process helps researchers to make sense of large amounts of unstructured data, uncover patterns, and develop deeper insights into the research topic.
What is reliability in data collection?
Answer: Consistent and repeatable measurements
Reliability in data collection refers to the consistency and stability of a measurement tool or method. A reliable measure will produce the same or very similar results if the measurement is repeated under the same conditions, indicating that the data collected is dependable and free from random error.
Which type of variable is measured on a numeric scale?
Answer: Quantitative
Quantitative variables are those that can be measured numerically, representing quantities or amounts. These variables can be discrete (e.g., number of children) or continuous (e.g., height, weight), and they allow for mathematical operations and statistical analysis.
What is the first step in data analysis?
Answer: Cleaning and preparing data
Before any meaningful analysis can occur, data must be cleaned and prepared. This crucial first step involves identifying and correcting errors, handling missing values, removing duplicates, and transforming data into a suitable format, ensuring the accuracy and integrity of subsequent analytical processes.