RMP 80/20

What is Research?

Research is a detailed, systematic inquiry into a particular concern or problem using scientific methods.

Core Characteristics: Systematic approach for accurate data, logical reasoning (inductive and deductive), reliance on real-time observations, in-depth analysis to avoid anomalies, and the ability to generate new questions.

Main Purposes:

Exploratory: To investigate new problem areas that haven't been explored before, often using an unstructured approach by asking questions1.

Descriptive: To expand knowledge on current issues by collecting data that describes the behavior of a sample population, typically through structured questions.

Explanatory: To understand the impact of specific changes on existing procedures, often using hypotheses and a highly structured approach2.

What are Qualitative Research Methods?

Qualitative methods analyse observed events, often associated with inductive approaches. They collect non-numerical responses using conversational, open-ended questions to understand participants' thoughts and reasoning.

• Examples: Interviews, focus groups, ethnographic studies, text analysis, and case studies.

What are Quantitative Research Methods?

Quantitative methods verify observed events and are commonly associated with deductive approaches. They pertain to numbers and measurable forms, using a systematic approach to investigate data to explain, predict, or control a phenomenon.

• Examples: Survey research, descriptive research, and correlational research.

What is Saunders’ Research Onion Layer 1: Research Philosophy?

Research philosophy is the foundation of any study, reflecting on reality and knowledge acquisition.

• Three main philosophies:

  • Positivism: Asserts knowledge exists independently of the researcher and can only be studied objectively through empirical observation.

  • Interpretivism: Emphasizes understanding social and cultural contexts, with researchers actively interpreting meaning from participants' perspectives.

  • Pragmatism: Prioritizes practical methods and values usefulness and outcomes over strict adherence to a single worldview, allowing for a blend of subjective and objective analysis.

What is Saunders’ Research Onion Layer 2: Research Approach?

• The research process is divided into two methods: inductive and deductive.

  • Inductive Research: Starts with specific observations and data, gradually developing broader theories or patterns. This is common in qualitative research where limited prior knowledge exists.

  • Deductive Research: Begins with existing theories and tests them through structured research, often aligned with quantitative methods and positivist philosophy.

What is Saunders’ Research Onion Layer 3: Research Strategy?

• This layer consists of various research designs and strategies, depending on the study's objectives.

  • Examples:

    • Experimental research: Uses controlled settings to observe the impact of variables.

    • Action research: Emphasizes collaborative problem-solving.

    • Case study research: Examines a single subject within its real-life context.

What is Saunders’ Research Onion Layer 4: Choices?

• This layer involves choosing the type of data collection methods, whether qualitative, quantitative, or both.

  • Mono method: Uses only one type of data.

  • Mixed-methods approach: Combines both qualitative and quantitative data.

  • Multi-method approach: Uses multiple techniques within both qualitative and quantitative research, such as applying thematic and content analysis to archival documents.

What is Saunders’ Research Onion Layer 5: Time Horizon?

• This layer focuses on the time frame for data collection, with two main options.

  • Cross-sectional approach: Involves collecting data at a single point in time to capture a snapshot of a phenomenon (e.g., analyzing language used in memes during 2020).

  • Longitudinal approach: Involves collecting data at multiple time points to observe changes or developments over time (e.g., studying how meme language evolves over several months or years).

  • The choice depends on whether the study aims to explore patterns at a moment in time or track them over a period.

What is Saunders’ Research Onion Layer 6: Techniques and Procedures?

• This layer represents the practical design of a study, involving key decisions that align with the overall methodology.

  • Decisions include: Determining data type, selecting appropriate methods, choosing a sampling strategy, deciding on data analysis techniques, and preparing essential study materials.

What is a Target Population?

The target population refers to a specific group of people with distinct characteristics that the research aims to study, for example, Parents whose children use school services if researching school fees; women aged 18-25 who use perfume if launching a new perfume; all customers of a business if measuring customer satisfaction.

What are Sampling Methods, Population, and Sample?

When conducting research, it's often impossible to collect data from everyone in a group, so researchers select a sample.

• Sample: The group of individuals who will participate in the research.

• Sampling Method: The way this sample is selected.

• Population: The entire group that you want to draw conclusions about.

• To draw valid conclusions, the sample must be representative of the entire population.

• A lack of a representative sample can affect the validity of results and lead to sampling bias.

What is a Sampling Frame?

The sampling frame is the actual list of individuals that the sample will be drawn from. Ideally, it should include everyone in the target population and no one who isn't.

Example: For research on working conditions at a company with 1000 employees (the population), the company's HR database listing all employees would be the sampling frame.

What are Probability Sampling methods?

Probability sampling is a method where every member of a population has an equal chance of being selected. Used in quantitative research to make strong statistical inferences.

• Four main types:

  • Simple Random Sampling: Ensures equal chance selection.

  • Systematic Sampling: Selects individuals at regular intervals.

  • Stratified Sampling: Divides the population into subgroups based on characteristics.

  • Cluster Sampling: Randomly selects entire clusters, useful for large, dispersed populations, but may carry a higher risk of error.

What are Non-Probability Sampling methods?

Non-random sampling techniques are used in exploratory and qualitative research to gather initial insights into small or under-researched populations. These methods are cost-effective but prone to sampling bias, which can lead to weaker inferences about the population.

Examples: Convenience sampling, voluntary response sampling, purposeful sampling, snowball sampling, and quota sampling.

What are the Eight Steps of the Research Process?

• Identifying the Research Problem: Recognizing a discrepancy that requires thorough investigation.

• Reviewing the Literature: Examining existing scholarly sources to understand background, avoid duplication, and identify gaps.

• Setting Research Questions, Objectives, and Hypotheses: Formulating clear statements of what the research aims to achieve and predict.

• Choosing the Study Design: Creating a blueprint for collecting, processing, and analyzing data.

• Deciding on the Sample Design: Selecting a representative subset (sample) from the total group (population) to draw conclusions.

• Collecting Data from the Research Sample: Obtaining necessary information using various techniques.

• Process and Analyze the Collected Research Data: Reducing, summarizing, and interpreting data to find patterns and insights.

• Writing Research Report: Presenting the findings, analysis, and conclusions in an understandable format.

What are Research Questions?

Research questions are broad statements that guide the overall direction of the research and identify the main problem. (e.g. Focused, researchable, feasible, specific, complex, arguable, relevant, and original.) They should not be based on value judgments or demand a conclusive solution.

What are Research Objectives?

Research objectives are specific, measurable goals that the research aims to achieve, defining what the study intends to accomplish. Crucial for guiding methodology choice and ensuring relevance. Should follow the SMART criteria (Specific, Measurable, Achievable, Relevant, Time-based). Typically developed from the broader research aim and can be general or specific. A well-defined research question should lead to specific objectives necessary to answer that question.

What is a Hypothesis?

A hypothesis is an unproven statement or proposition that can be refuted or supported by empirical data, asserting a possible answer to a research question.

• Characteristics: Must be testable, suggesting a relationship between variables (independent and dependent).

• When conducting statistical testing, both a null hypothesis (H₀), which states no relationship, and an alternative hypothesis (H₁), which proposes a relationship, are formulated.

What is Primary Data?

Primary data is original data collected directly from its source for a specific research purpose. It is real-time and firsthand.

• Common methods: Surveys/questionnaires, interviews, observations, experiments, focus groups, and case studies.

What is Secondary Data?

Secondary data is data that has already been collected through primary sources and is readily available for researchers to use.

• Sources: Books, published articles (journals, newspapers), government records, and websites.

• Advantages: Ease of access, lower costs, and time savings.

• Disadvantages: Researchers must be mindful of potential data quality issues, irrelevance, or outdated content.

What is Qualitative Data Analysis?

The process of gathering, organizing, and interpreting non-numerical data (e.g., interview transcripts, open-ended survey answers) to uncover patterns, themes, and insights, understanding the 'whys' and 'how’s'.

What is Quantitative Data Analysis?

A systematic process of examining, interpreting, and drawing conclusions from numerical data. It deals with structured datasets and uses statistical methods (e.g., mean, median, mode, percentages, correlations, regressions) to identify patterns, test hypotheses, and make predictions.

• Combining approaches: Using both qualitative and quantitative data analysis together can provide deeper insights, showing the 'what' (quantitative) and explaining the 'why' (qualitative).

What is a Research Report and its typical structure?

A research report is a comprehensive, formal document that presents the findings, analysis, and conclusions of a study.It serves as a permanent record and a means of communication, knowledge sharing, and decision support.

• Standard structure typically includes:

  • Title Page, Abstract/Executive Summary, Table of Contents, ntroduction (Background, problem statement, research questions/objectives, significance), Literature Review (Overview and analysis of existing studies, highlighting knowledge gaps), etc.

What are Research Ethics and why are they important?

Research ethics are principles that guide the design and practice of research, particularly when collecting data from people. Crucial for protecting participants' rights and welfare, preventing harm, ensuring voluntary participation, and maintaining the integrity and credibility of research findings. Institutional Review Boards (IRBs) review research proposals to ensure ethical acceptability.

What are the Core Ethical Principles in Research?

• Voluntary Participation: Participants must freely choose to participate without coercion and can withdraw at any time without negative consequences.

• Informed Consent: Participants must fully understand the study's purpose, benefits, risks, and their rights before agreeing, typically through a consent form.

• Anonymity: The researcher does not know the identity of participants and cannot link individual data to them.

• Confidentiality: The researcher knows participant identities but keeps that information hidden from everyone else, protecting privacy.

• Potential for Harm: Researchers must consider and mitigate all possible forms of harm (psychological, social, physical, legal) and disclose risks.

• Authenticity, Honesty, and Avoiding Misconduct: Ensuring participants provide genuine responses and that researchers accurately represent results, avoiding plagiarism, falsification, or fabrication of data.

• Conflict of Interest: Researchers must disclose any potential conflicts that could influence the study's outcomes.

• Fair Payment: Compensating participants fairly for their time and effort.

Cultural Sensitivity: Considering cultural differences to ensure respectful and valid research across diverse populations.