Research Skills & Analysis - LIB116 Lecture 1

Research Skills & Analysis - LIB116, Lecture One

• Lecture presented by Assoc. Prof. Emam Omar, Physics Department, New Mansoura University, on September 28, 2024.
• Course name: Research Skills & Analysis
• Course code: LIB116
• Lecture number: One

Data

• Data are individual facts, observations, statistics, characters, symbols, images, numbers.
• Raw data lacks context and meaning.
• Data types: Quantities, numbers, facts, observations, graphs, and measurements.

Types of Data

• Research data is often classified into quantitative and qualitative.
• Quantitative data can be counted or expressed numerically (e.g., number of students, age, grades, test scores).
• Qualitative data is descriptive and doesn't have numerical values (e.g., attitude, perception, feelings).

Types of Data (Based on Sources)

• Primary data (first-hand information): Data originated by a researcher for the specific purpose of addressing a research problem and collected directly from subjects.

• Secondary data: Existing data collected by others; it may be published or unpublished.

• Secondary data sources include: Files/records, computer databases, industry/government reports, documents (budgets, organizational charts, policies, procedures, maps, monitoring reports), newspapers and television reports.

Data Collection Methods

• Methods for collecting data: Forms and questionnaires, interviews, observations, documents and records, focus groups.
• Other methods include: Oral histories, combination research, online tracking, online marketing analytics, and social media monitoring.

Methods of Data Collection

• Observation: A research technique involving direct observation of phenomena in their natural settings.

  • Types of observation:
    • Non-controlled, participant observation (observer becomes part of the group).
    • Non-controlled, non-participant observation (observer observes the group from a distance)
    • Controlled, systematic observation (researcher pre-determines study variables and controls all elements).

• Questionnaire: A series of written questions given to subjects.

  • Types of questionnaires
    • Structured (closed-ended) questionnaires: Predetermined answers.
    • Unstructured (open-ended) questionnaires: Open responses.

• Interview: Conversation with a purpose, more than just an oral exchange of information.

  • Types of interviews:
    • Non-directive (unstructured): Flexible, open-ended questions.
    • Directive (structured): Predetermined questions, standardized technique.
    • Repeated interviews: Track changes in phenomenon over time.
    • Focused interviews: Limited by relevant theories and evidence.
    • Depth interviews: Qualitative research involving intensive individual interviews.

• Surveys: Research method where subjects respond to statements or questions in questionnaires or interviews.

  • Often involves closed-ended or open-ended questionnaires.
  • Techniques use statistical methods to analyze data.
  • A representative sample, a subset of the population, is studied.

• Experimental devices: Laboratory equipment used in research (e.g., glassware, microscopes, analytical instruments).

Information

• Data, in itself, lacks meaning but once processed, it becomes information.
• Information is a collection of processed data presented in a meaningful form within a given context.
• Information depends on data, context, and meaning. Processing turns data into information.
• Different figures present examples of data and how it transforms to information. A good example is the ice cream sales data (raw) and creating the chart and conclusion from it.

Data Processing

• Raw data is not directly useful for organizations.
• Data processing translates raw data into usable information through stages like collection, preparation, input, processing, output, and storage.
• Data processing operations: Includes data collection (observation, questionnaires, interviews, surveys, experimental devices), data preparation (ensuring data correctness), sorting (arranging data based on characteristics), input (converting sorted data into machine-readable format), processing (analyzing data), and output/interpretation (making data usable for the larger community).
• Types of data processing: Batch processing, real-time processing, online processing, and time-sharing.

This quiz covers the key concepts presented in the first lecture of Research Skills & Analysis (LIB116) by Assoc. Prof. Emam Omar. Learn about data types, their classifications, and the distinctions between quantitative and qualitative data. Enhance your understanding of primary data sources and their relevance in research.