QM UT2 Review w/ Quiz

Research Questions

• A research question is a clear, focused, and specific question a researcher aims to answer
• It directs the course of the study and helps in determining the methods used, defining the problem or issue being addressed
• Research questions are used before conducting research to guide the study, determine methods, and analyze data
• A good research question should be clear, focused, researchable, and feasible
• Social science: How does social media use affect teenagers' self-esteem?
• Healthcare: Does exercise reduce anxiety symptoms in individuals diagnosed with depression?
• Education: How does student engagement impact academic performance in online learning?

Hypothesis

• A hypothesis is a testable statement or prediction about the relation between variables
• Hypotheses are based on prior knowledge or theory, they guide the research process
• Hypotheses are used before data collection to provide direction, test relationships, and validate or refute theories
• Null Hypothesis (H₀) suggests no effect or relationship between variables
• Example of Null Hypothesis: The new drug has no effect on blood pressure
• Alternative Hypothesis (Ha) suggests an effect or relationship exists
• Example of an Alternative Hypothesis: The new drug decreases blood pressure
• Two-tailed hypotheses predict a difference but do not specify a direction
• One-tailed hypotheses predict the direction of the effect
• Research questions ask what you want to investigate, they are open-ended
• Hypotheses predict the outcome of the investigation, they are specific and testable
• Research questions lead to forming hypotheses
• Hypotheses narrow the focus of the questions and guide data collection and analysis

Qualitative Research Questions

• Qualitative research questions explore, understand, or interpret experiences, phenomena, or meanings in depth
• Qualitative research focuses on the "how" or "why" instead of numerical data
• Qualitative research questions are open-ended, exploratory, context-specific, and focus on experiences
• Hypothesis is not typically used in qualitative research, because it focus on exploration over assumptions
• Central Question is a broad, exploratory inquiry
• Subquestions narrow the focus of the study
• Phenomenological question: "What is the lived experience of individuals recovering from a heart attack?"
• Ethnographic question: "How do traditional healing practices influence health-seeking behavior in rural African communities?"
• Grounded Theory question: "What are the factors that influence women to leave abusive relationships?"
• Narrative question: "What stories do refugee children tell about their journey to safety?"
• Qualitative research provides deep insights into human behavior, experiences, and perceptions

Quantitative Research Questions

• Quantitative research questions collect numerical data and measure variables through statistical methods
• The questions establish relationships, test hypotheses, or quantify differences between groups
• Quantitative research questions are close-ended and yields numerical or categorical data
• Quantitative research questions focus on measurement and involves defining and measuring variables
• Quantitative research questions analyze correlations, causations, or comparisons
• Quantitative research questions are objective, specific, and minimizes subjective interpretation, they are hypothesis-driven
• Aims to confirm or reject predictions based on data
• Descriptive question: "What is the average age of university students?"
• Comparative question: "Do male and female employees differ in job satisfaction levels?"
• Relational question: "Is there a correlation between hours of sleep and academic performance?"
• Provides objective, measurable data for decision-making, theory testing, and trend analysis

Descriptive and Inferential Research Questions

• Descriptive research questions aim to describe characteristics, behaviors, or situations without exploring relationships
• Example: "What are the students' achievement levels in science classes?"
• Inferential research questions investigate relationships between variables or explore their impact
• Example: "How does critical thinking ability relate to student achievement?"
• Descriptive questions focus on describing individual variables
• Inferential questions explore relationships between variables and test hypotheses

Mixed Methods Research Questions

• Mixed methods research combines both quantitative and qualitative approaches
• This provides a more comprehensive understanding of the research problem
• Example: "How does technology use affect students’ grades, and what are their views on its effectiveness?"
• Example: "What is the link between teachers' experience and classroom management, and how do they describe their challenges?"
• Separate qualitative and quantitative questions can be used to narrow and focus the purpose statement
• Mixed methods questions can emphasize both approaches or combine them into a single integrated question
• Provides a fuller picture of complex research problems
• Quantitative data shows what happens, while qualitative insights explain why it happens

Defining Surveys and Experiments

• Surveys collect data using structured questions to understand opinions or behaviors
• Example: Customer feedback on a product
• Experiments test cause-and-effect relationships by manipulating variables in controlled conditions
• Example: Testing a new teaching method's impact on student performance

Characteristics of Surveys

• Purpose: Collect data about opinions, behaviors, or demographics
• Design: Uses structured questions like multiple-choice or scales
• Methods: Online, phone, or in-person surveys

Characteristics of Experiments

• Purpose: Test cause-and-effect relationships
• Design: Involves control and experimental groups and manipulates variables to observe outcomes
• Types: Laboratory or field experiments

Comparing Surveys and Experiments

• Surveys describe characteristics or opinions of a population
• Experiments determine causal relationships between variables
• Surveys collect self-reported data via questionnaires/interviews
• Experiments observe outcomes under manipulated conditions
• Surveys are used in market research, social sciences, and healthcare
• Experiments are applied in psychology, education, and agriculture

Components of a Survey Study

• Method Plan outlines approach to collecting data using surveys
• Research Problem identifies the key issue or question to explore
• Objectives define what the survey aims to achieve (e.g., understanding customer satisfaction)

Designing the Survey Instrument

• Designing the survey instrument involves question types which can be open-ended or closed-ended
• Types of Questions can use a Likert scale, multiple choice or yes/no questions
• Pre-testing runs the survey on a small sample to refine questions

Selecting the Sample

• Target Population defines the group from which data will be collected
• Sampling Method: Random, stratified, or convenience sampling
• Sample Size ensures reliability of results

The Survey Design

• Clearly state the purpose and identify respondents (age, location, occupation, etc.)
• Ensure relevance to research goals

Crafting Effective Survey Questions

• Open-Ended questions allow detailed responses
• Closed-Ended questions provide specific options (yes/no, multiple choice)
• Likert Scale questions measure agreement levels
• Ranking questions prioritize choices

Survey Format & Distribution must consider informed consent, anonymity, and survey validity

• Informed Consent: Participants must voluntarily agree with full understanding
• Anonymity & Confidentiality: Protect respondent identity and responses
• Survey Validity: Ensure accurate and reliable measurements

Data Analysis and Reporting

• Data Cleaning removes errors, incomplete, or duplicate responses
• Statistical Analysis: Descriptive statistics, correlations, regressions
• Result Interpretation: Link findings to research objectives

Ensuring Survey Validity

• Content Validity: Questions cover all aspects
• Criterion Validity: Compare to existing measures
• Construct Validity: Measure intended concept

Variables in the Study

• Variables are characteristics that change, examples include age, income, and education
• Dependent Variables measure the outcomes (e.g., exam scores)
• Independent Variables cause change (e.g., study time)
• Control Variables are kept constant to avoid interference
• Categorical (Qualitative) Variables are groups or categories (e.g., gender, race)
• Continuous (Quantitative) Variables are numeric values (e.g., height, weight)
• Ratio measurement: Numeric with absolute zero (e.g., income)
• Interval measurement: Numeric but no true zero (e.g., temperature)
• Ordinal measurement: Ordered categories (e.g., satisfaction ratings)
• Nominal measurement: Categories without order (e.g., colors, names)

The Population and Sample

• Data Collection involves use in statistical studies
• Understanding the difference of Population vs. Sample is crucial
• Accurate Analysis with Reliable results depend on correct sampling

Defining Population

• Population is the entire group of individuals or items being studied
• A population can be finite or infinite (e.g., students in a school versus stars in the universe)

Defining Sample

• A Sample is a subset of Population, which is more practical and cost-effective
• Example: 500 students from different schools in a country
• Saves time, money, and effort
• Sampling Methods should focus on probability based sampling and non-probability sampling
• Choosing the right sampling method is key for reliable results

Types of Probability Sampling

• Random sampling gives an equal chance for all
• Systematic sampling selects every nth person
• Stratified sampling has data divided by characteristics
• Cluster sampling has random groups selected

Types of Non-Probability Sampling

• Convenience sampling is based on availability
• Judgmental sampling is based on the researcher’s judgment
• Quota sampling is based on specific proportions
• Snowball sampling uses referrals

Choosing Sample Size

• Larger sizes improve accuracy
• Samples that are too small leads to biased results
• Formulas can be used to determine the correct number

Avoiding Sampling Bias

• Random methods avoid selection bias
• Diversity in selection ensures representation
• Proper Selection following statistical guidelines is key

Characteristics of Qualitative Research

• Qualitative research seeks to understand human experiences, behaviors, and interactions in their natural settings
• It is exploratory and focuses on meaning rather than numerical data
• Subjectivity: The researcher’s interpretation plays a key role in data analysis
• Contextual Understanding: Focuses on participants' experiences within their environment
• Inductive Approach: Observations lead to patterns, themes, and theories
• Descriptive & Narrative Data: Emphasis on words, emotions, and interpretations rather than statistics
• Holistic Perspective: Captures the complexity of social interactions and human experiences

Qualitative Research Designs

• Qualitative research designs help explore various phenomena based on context and research goals
• Case Study: In-depth examination of a single case (person, organization, event)
• Phenomenology: Focuses on understanding individuals' lived experiences
• Ethnography: Studies cultural or social groups through immersion
• Grounded Theory: Develops theories based on observed data
• Narrative Research: Uses storytelling to explore individuals’ experiences

The Researcher’s Role and Reflexivity

• The researcher is an active participant in qualitative studies, making reflexivity crucial
• Researcher’s Influence: Acknowledging biases and perspectives that may affect data collection and analysis
• Self-Reflection: Continuous evaluation of one’s role in the study
• Transparency: Documenting how personal biases may shape interpretations

Data Collection Procedures

• Qualitative research involves various flexible and adaptive methods

Key Methods for data collection

• Interviews: Structured, semi-structured, or unstructured discussions with participants
• Focus Groups: Group discussions to gather diverse perspectives
• Observations: Watching behaviors in real-world settings
• Document Analysis: Reviewing existing records, letters, or media

Data Recording Procedures

• Accurate data recording ensures credibility and completeness of information

Key Methods for recording data

• Audio/Video Recordings: Captures verbal and non-verbal communication
• Field Notes: Observations and reflections recorded by researchers
• Transcriptions: Converting audio into written text

Data Analysis Procedures

• Analyzing qualitative data involves iterative processes to identify themes and insights

Key Methods for data analysis

• Thematic Analysis: Identifies recurring themes
• Grounded Theory: Develops theories based on emerging patterns
• Content Analysis: Examines meanings in text or media

Interpretation in Qualitative Research

• Interpretation involves making sense of qualitative data by linking findings to research questions and theories

Validity and Reliability in Qualitative Research

• Qualitative research emphasizes trustworthiness rather than traditional validity and reliability
• Credibility: Confidence in findings (e.g., participant verification)
• Transferability: How findings apply to other contexts
• Dependability: Consistency in the research process
• Confirmability: Findings should reflect participants’ experiences rather than researcher bias

Writing the Qualitative Report

• A qualitative report presents the research process, findings, and analysis in a structured and narrative-driven format

Key Sections in a Qualitative Report

• Introduction: Research background and purpose
• Methodology: Data collection and analysis procedures
• Findings: Themes, patterns, and participant quotes
• Discussion: Interpretation and implications

The Qualitative Research Paradigm

• Qualitative research follows interpretivist and constructivist paradigms, viewing reality as socially constructed