Quantitative Method

• Research


  A systematic and unbiased way of solving a problem (by answering questions or supporting hypothesis) through generating verifiable data
• Research


  • It is a systematic and organized process of inquiry that aims to discover, interpret, and develop knowledge or understanding of a particular subject or phenomenon
• Why research?

  • Cite evidence challenges or any challenges that we experienced during the pandemic period or any future challenges that involved/will involve research
  • Expand Knowledge
  • Solve Problems
  • Inform Decision-Making
  • Improve Practices
  • Innovate
  • Address Societal Challenges
  • Foster Critical Thinking
• Research in various disciplines

  • Business
  • Humanities
  • Natural and Applied Science
  • Social Issue
• How to do research?

  1. Develop and select a topic (develop research question, identify keywords, find background information)

  2. Locate Information

  3. Evaluate and analyze information

  4. Write, organize, and communicate information

  5. Cite sources
• Characteristics of good research


  • Rigorous
  • Controlled
  • Accurate
  • Clear
  • Concise
  • Valid
  • Verifiable
  • Sequential
  • Precise
  • Original
  • Coherent
  • Generalizable
• Quantitative research methods

  • Survey
  • Experiment
  • Observational Studies
  • Secondary Data Analysis
  • Content Analysis
  • Statistical Analysis
• Survey


  • Gather data from a group of people through questionnaires or interviews, focusing on numerical information like ratings or likert scale responses
  • Helps understands people's opinions or experiences in a structured way
• Experiment


  • Involve changing variables to see how they affect other variables, aiming to determine cause-and-effect relationships
  • Usually assign randomly to experimental and control groups for a fair comparison
• Observational Studies


  • Entail watching and documenting behaviors or events without altering variables, and they can occur in either natural settings (naturalistic observation) or controlled settings (control observation)
  • Understand phenomena as they naturally occur, without external influence
• Secondary Data Analysis


  • Analyze data already gathered by others or organizations
  • Offers valuable insights and helps answers research questions without needing to collect fresh data
• Content Analysis


  • About studying written, visual, or audio information to find patterns and themes
  • Often used in media and communication studies for qualitative analysis
• Statistical Analysis


  • Use math methods to study and explain data
  • They look at numbers like averages, comparisons, and patterns to understand things better
• Research Design


  • It outlines the steps and methods that researchers will use to collect and analyze date to answer their research question or test hypotheses
  • A well developed research design is crucial for ensuring the validity and reliability of the research findings
• Types of Research Designs


  • Mixed-method Design
  • Cross-sectional design
  • Quasi-method design
  • Experimental design
  • Descriptive design
  • Longitudinal design
  • Correlational design
• Ethical considerations in data collection

  • Informed consent
  • Privacy and confidentiality
  • Voluntary participation
  • Minimization of harms
  • Respects for diversity
  • Beneficence
  • Compliance with regulations
• Designing a data collection method

  1. Define objectives

  2. Select Data Collection Techniques

  3. Develop Instruments

  4. Pilot testing

  5. Sampling

  6. Data Collection Procedure

  7. Quality Assurance

  8. Ethical Consideration

  9. Data Management

  10. Data Analysis Plan
• Population


  The entire group under study for drawing conclusion
• Sample


  A specific subset from which data is collected
• Sampling methods

  • Probability sampling
  • Non-probability sampling
• Probability sampling


  • Involves randomly selecting a sample, or a part of the population that you want to research
  • To qualify as being random, each research unit (e.g., person, business, or organization in your population) must have an equal chance of being selected
• Non-probability sampling


  • Uses non-random criteria like the availability, geographical proximity, or expert knowledge of the individuals you want to research in order to answer a research question
  • Used when the population parameters are either unknown or not possible to individually identify
• Non-probability sampling


  Sampling method that uses non-random criteria like the availability, geographical proximity, or expert knowledge of the individuals you want to research in order to answer a research question
• Probability sampling


  The samples are randomly selected and everyone in the population has an equal chance of getting selected
• Probability sampling methods

  • Simple random sampling
  • Systematic sampling
  • Stratified sampling
  • Cluster sampling
• Non-probability sampling methods

  • Convenience sampling
  • Voluntary response sampling
  • Purposive sampling
  • Snowball sampling
  • Quota sampling
• Simple random sampling


  • Every member of the population has an equal chance of being selected
• Systematic sampling


  • Similar to simple random sampling, but slightly easier to conduct
• Stratified sampling


  • Involves dividing the population into sub-populations that may differ in important ways
• Cluster sampling


  • Involves dividing the population into subgroups, but each subgroup should have similar characteristics to the whole sample
• Convenience sampling


  • Simply includes the individuals who happen to be most accessible to the researcher
• Voluntary response sampling


  • Mainly based on ease of access
• Purposive sampling


  • Involves the researcher using their expertise to select a sample that is most useful to the purpose of the research
• Snowball sampling


  • Used to recruit participants via other participants
• Quota sampling


  • Relies on the non-random selection of a predetermined number of proportion of units
• Graphical data summarization


  Presenting complex data in visual format to communicate key findings and insights effectively
• Common types of graphical data summarization

  • Bar charts
  • Line charts
  • Pie charts
  • Summary tables
  • Histograms
  • Polygraphs
  • Scatter plots
• Range


  Difference between the maximum and minimum values
• Variance


  Average squared deviation of each data point from the mean
• Standard deviation


  Measure of the dispersion of data points around the mean (square root of the variance)