• INTRODUCTION

Definition of Social Research

• Scientific understanding that seeks, through rational and organized methods, to find unknown information or confirm and analyze existing data
• Examines order, relationships, and theoretical interpretations
• Creates innovative scientific methods, frameworks, and hypotheses for trustworthy research on human behavior

➣ Social Research Definition (Comprehensive)

A methodical approach to investigating, analyzing, and conceptualizing aspects of social life to:

• Expand knowledge
• Correct existing knowledge
• Verify existing knowledge

Kerlinger’s Definition of Research: “An organized, controlled, empirical, and critical exploration of natural phenomena guided by theory and assumptions concerning the presumed links among such phenomena”

➥ Key Characteristics of Research

1. Logical and systematic effort
2. Aims to answer specific questions
3. Systematic process from problem articulation to conclusions
4. May result in solutions or theoretical formulations

• QUANTITATIVE METHODS

A systematic, formal, and objective method to:

• Collect numerical data
• Obtain information about ideas and concepts
• Test theories objectively
• Generalize findings

Stages in Quantitative Research Structure

1. Theory

• Definition: Standardized principle to explore relationships between variables, ideas, or concepts
• Two Levels:
  • Abstract Level: Idea exists but lacks concrete existence
  • Empirical Level: Observations and experiences can be verified
• Two Processes of Theory Development:
  • Induction: Bottom-up reasoning; concludes generalizations
  • Deduction: Top-down; theory is tested

2. Hypothesis

• Definition: Tentative proposition/statement tested in the field
• Discusses association/relationship between variables
• Should be clear and short

Types of Hypotheses:

• Null Hypothesis (H₀):
  • Hypothesis of no difference
  • States no difference between groups
• Alternative/Research Hypothesis (Hₐ):
  • Based on theory and literature review
  • Can be directional
  • Shows significant difference between groups

Important Note:

• Both hypotheses cover population parameters, not sample
• Null hypothesis should be tested and either retained or rejected

➥ THEORY TO HYPOTHESIS

Process

1. Researchers observe phenomena (e.g., men talk less than women)
2. These discoveries can be replicated:
   • In same manner as originally conducted
   • With modifications

Theory Functions

• Understanding and interpretation of phenomena
• Can be tested
• Generate new research through new questions
• Enable critical thinking
• Multiple theories may explain single phenomenon

Hypothetico-Deductive Method

• Psychologists start with phenomena
• Construct or examine theory
• Test through hypothesis
• Use observational data for testing

➥ CONCEPTS TO VARIABLES

Concepts

• Nature: Subjective
• Characteristics:
  • Difficult to measure
  • No uniformity in understanding
  • Examples: excellence, rich, violence, achievers, effectiveness

Variables

• Nature: Objective
• Characteristics:
  • Measurable
  • Depend on scale of measurement
  • Examples: gender (male/female), age (years/months), income (hundreds/thousands), weight (kg/grams), height (inches/cm)

Operationalization Process

1. Identify indicators (criteria for conversion)
2. Convert concepts into measurable variables
3. Example: “Rich” → Income + Material belongings → Currency units + Assets

Importance in Research Types

• Qualitative: Studies perceptions, feelings; less emphasis on measurement
• Quantitative: Focuses on commonalities; both measurement and variables important

➥ TYPES OF VARIABLES

A. Based on Causal Relationship

1. Independent Variables
   • Bring change in the study/situation
   • The “cause”
2. Dependent Variables
   • Effects or consequences of change
   • The “outcome”
3. Extraneous Variables
   • Responsible for cause and effect
   • May increase/decrease association strength
4. Intervening/Confounding Variables
   • Act as link between independent and dependent
   • Mediate the relationship

B. Based on Study Design

1. Active Variables
   • Can be controlled, measured, manipulated by experimenter
   • Examples: teaching methods, program-related services
2. Attribute Variables
   • Cannot be controlled, measured, or manipulated
   • Population characteristics
   • Examples: age, gender, religion, attitudes, motivation level

C. Based on Unit of Measurement

1. Categorical Variables
   • Nominal scale
   • Ordinal scale
2. Continuous Variables
   • Interval scale
   • Ratio scale
3. By Nature
   • Qualitative
   • Quantitative

➥ SAMPLE DECISION AND DATA COLLECTION

Sample Selection Steps

1. Decide the population
2. Ensure sample is true representative
3. Choose sampling technique:
   • Probability: Simple random, stratified random, systematic
   • Non-probability: Convenience, snowball, quota

Data Collection Methods

A. Personal/Face-to-Face Interview

• Advantages:
  • Rapport formation possible
  • Can motivate respondent
  • Can clarify doubts
  • Can add more questions
  • Non-verbal cues can be noted
  • Data becomes rich
• Disadvantages:
  • Requires much time
  • Interviewer needs adequate training

B. Telephonic Interview

• Advantages:
  • Less costly
  • Requires less time
  • Wide geographic coverage
  • Maintains anonymity
• Disadvantages:
  • Non-verbal cues cannot be utilized
  • Interviews may be short
  • May not cover detailed information

C. Self-Completion Questionnaire

• Advantages:
  • Less expensive for different groups
  • High confidentiality
  • 100% response rate (when administered)
• Disadvantages:
  • (Not specified in detail)

D. Postal Questionnaire

• Advantages:
  • Very wide geographic reach
  • Maintains anonymity
  • Respondent can take time
  • Fill at convenience
• Disadvantages:
  • Doubts can’t be cleared
  • Further questions cannot be asked

E. Participant Observation

• Advantages:
  • Less cost
  • More accuracy
  • Can record non-verbal cues
  • Useful for illiterate participants
• Disadvantages:
  • Time-consuming
  • Doesn’t include motivation, feelings, perception data

F. Non-Participant Observation

• Characteristics:
  • Observer doesn’t participate directly
  • Remains outside the group
• Disadvantages:
  • Lack of interaction between observer and observant

➥ DATA ANALYSIS

Types of Information

• Demographic details: Gender, income, age, place (straightforward)
• Other information: Needs conversion into numbers

Uses of Data Analysis

• Study differences among groups
• Study differences across cultures
• Study correlations between variables
• Find significant relationships
• Find significant differences

Statistical Techniques

• t-test
• ANOVA
• Chi-square
• Other relevant techniques based on study design

➥ INTERPRETATION AND CONCLUSION

Process

1. Interpret results after data analysis
2. Lead to findings
3. Conclude whether hypothesis is:
   • Accepted
   • Rejected

Components

• Reasons supporting findings
• Implications for theoretical ideas
• Background for theory of research

➥ STEPS INVOLVED IN QUANTITATIVE RESEARCH

Step 1: Determining the Research Issue

• Clear definition of research problem/inquiry
• Identify specific area of interest
• Formulate research questions or hypotheses
• Establish purpose and objectives

Step 2: Review of Literature

• Conduct comprehensive review of existing literature
• Understand current knowledge
• Identify gaps in literature
• Focus research questions/hypotheses

Step 3: Creating a Research Design

• Select appropriate study design based on objectives
• Popular Designs:
  • Survey design
  • Descriptive design
  • Correlational design
  • Experimental design
• Design Choice Depends On:
  • Nature of research question
  • Level of regulatory requirements
  • Feasibility of data collection

Step 4: Creating Research Instruments

• Design and build measurement tools:
  • Tests
  • Questionnaires
  • Surveys
  • Structured observation protocols
• Requirements:
  • Reliability: Consistent results
  • Validity: Measures required quantity precisely

Step 5: Sampling

• Select subset from target population
• Sampling Techniques:
  • Convenience sampling
  • Stratified sampling
  • Random sampling
• Importance: Representative sample ensures generalizability

Step 6: Information Gathering

• Use specific instruments and sampling strategies
• Collect numerical data
• Methods include:
  • Conducting experiments
  • Distributing surveys
  • Observing behavior
  • Using pre-existing datasets
• Key: Standardizing data collection to reduce biases

Step 7: Analysis of Data

• Use statistical techniques
• Descriptive Statistics: Mean, median, standard deviation
• Inferential Statistics: t-tests, ANOVA, regression analysis
• Multivariate Techniques: For examining relationships

Step 8: Examining Results

• Address research questions
• Test theories
• Analyze for:
  • Patterns
  • Effect sizes
  • Statistical significance
• Draw conclusions from data analysis

Step 9: Explaining and Presenting Outcomes

• Write research report/paper
• Summarize:
  • Methodology
  • Findings
  • Conclusions
• Create visual representations:
  • Tables
  • Charts
  • Graphs

• STRENGTHS OF QUANTITATIVE RESEARCH

1. Objectivity and Reliability
   • Systematic, objective, reliable
   • Emphasis on measurable data
   • Improves reliability of findings
   • Enables replication and validation
2. Generalizability
   • Uses large sample sizes
   • Results easier to extrapolate to larger populations
   • Can make conclusions about broader groups
3. Statistical Analysis
   • Precisely detect patterns, correlations, trends
   • Test hypotheses
   • Assess relevance and strength of correlations
   • Determine statistical significance
4. Clear and Precise Results
   • Numerical results easy to interpret
   • Easy to disseminate to larger audience
   • Helpful for data-driven decisions
   • Useful for policy development
5. Depth and Scope
   • Address large number of variables simultaneously
   • Thorough understanding of complex phenomena
   • Examine interactions between components
   • Develop causal relationships and predictive models
6. Efficiency
   • Collect large sample sizes quickly
   • Methods include: surveys, experiments, observations
   • Compare responses from different groups easily
7. Evidence-Based Decision-Making
   • Supports various fields:
     • Social sciences
     • Business
     • Education
     • Healthcare
   • Provides empirical data
   • Statistical analysis for evaluation
   • Assessment of outcomes
   • Informed decision-making

• WEAKNESSES OF QUANTITATIVE RESEARCH

1. Limited Contextual Comprehension
   • Emphasis on numerical data and statistics
   • May not offer comprehensive contextual understanding
   • Challenges with complex social, cultural, psychological subjects
   • Requires qualitative research for depth
2. Challenges in Investigating Subjective Experiences
   • Difficulty capturing:
     • Subjective experiences
     • Emotions
     • Perceptions
   • May disregard:
     • Distinctive perspectives
     • Sentiments
     • Nuances essential for understanding human behavior
3. Potential for Oversimplification
   • Complex phenomena simplified to measurable variables
   • May lead to oversimplification
   • Aspects may be disregarded or distorted
   • Constraints of quantification
4. Incapable of Managing Special Circumstances
   • Challenges with atypical or outlier events
   • May not conform to statistical studies
   • Important for understanding population variability
   • May fail to detect unusual patterns
5. Reliance on Predefined Measures
   • Uses predefined measures and instruments
   • May not comprehensively capture all factors
   • Could impede exploration of novel aspects
   • Limits researcher’s ability to discover unexpected findings
6. Potential for Measurement Mistakes
   • Biases in survey replies
   • Imprecise data collection
   • Confounding variables
   • Undermines validity and reliability
7. Determining Causality Challenges
   • Can establish correlations
   • Difficult to establish causality
   • Additional factors (confounders) may affect relationships
   • Correlation ≠ causality
8. Ethical Considerations
   • Large datasets or experimental designs
   • Concerns:
     • Potential harm to participants
     • Privacy concerns
     • Need for informed consent
   • Must follow ethical guidelines
   • Consider impact on individuals and society

• QUALITATIVE METHODS

Definition

Explores, describes, and interprets participant’s personal and social experiences. Researchers understand limited participants’ frames of reference rather than testing hypotheses on broad samples.

Purpose

• Understanding people’s motivations (Henn et al., 2006)
• Examining ideas, attitudes, motives, intents
• Actions guided by meanings

➥ STEPS IN CONDUCTING QUALITATIVE RESEARCH

General Steps of Conducting Research

Step 1: Selection of Topic

• Based on personal, professional, or societal importance
• Fill gaps in literature
• Investigate further

Step 2: Establishing Research Question

• Narrow down topic
• Focus on what needs addressing
• Qualitative: Questions evolve during study
• Quantitative: Achieve solution to research problem

Step 3: Design the Study Research

• Plan the study
• Choose appropriate methodology
• Know constraints/restrictions

Step 4: Gathering/Collecting Data

• Collect in appropriate settings
• Use methods yielding relevant information
• Obtain effective information

Step 5: Analysis of Data

• Qualitative: New ideas and patterns narrowed into condensed form
• Give meaning and understanding to large data set
• Identify new concepts, ideas, patterns

Step 6: Interpreting the Data

• Investigate alternate causes
• Compare current data to prior studies
• Draw wider conclusions
• Qualitative: Emphasizes new notions and theoretical interpretations
• Researcher alternates collection, analysis, interpretation

Step 7: Reporting Findings

• Present in required format
• Publish material
• Add to literature
• Allow evaluation and discipline building

➥ Specific Steps in Conducting Qualitative Research

Step 1: Acknowledging the Social Self

• Self-assessment
• Place topic in socio-historical framework
• Depends on researcher’s:
  • Personal beliefs
  • Biography
  • Contemporary issues

Step 2: Adopting a Perspective

• Consider theoretical-philosophical paradigm
• Position inquiry within framework
• Select course of action with potential questions
• Different from limiting focus

Steps 3, 4, 5: Designing, Collecting, Analyzing, Interpreting Data

• Similar to quantitative but more simultaneous
• Qualitative Researcher:
  • Collects, analyzes, interprets data simultaneously
  • Iterative process
  • Goes back and forth between steps
  • May use/test existing theory OR construct new theory
  • Comes up with new ideas and theoretical interpretations

Step 6: Inform Others

• Same as quantitative
• Format differs based on methodology applied

➥ CHARACTERISTICS OF QUALITATIVE RESEARCH

1. Real-Life Settings

• Research conducted in natural environments
• Observe human behavior in natural setting
• Minimal inconvenience to daily life

2. Multiple Subjective Realities

• Quantitative: Assumes one universal, measurable, objective reality
• Qualitative: Believes various subjective realities exist
• Reality approximated in numerous ways
• Human understanding and interpretation constitute reality
• Complex reality understood as a whole
• Research must be broad and contextual

3. Specific Description

• Describe people’s actions and ideas specifically
• Emphasize social significance
• Insider Perspective:
  • Close relationship between researcher and subjects
  • Not impersonal and distant

4. Data Determines Framework

• Theorizing and concept creation start with rich data
• Data prioritized in qualitative methods

5. Flexible Strategy

• Research questions may not be specified initially
• Research concepts may not be specified
• Focus can shift during data collection
• New ideas might occur
• Topics might become more important

6. Contextual Consideration

• Respondents shaped by history and temporality
• Time, place, conditions matter
• Real-life events and behavior examined
• Economic, political, cultural contexts considered
• Data must be contextualized to avoid misinterpretation

7. Formulation of Theories

• Involves formulation rather than testing
• Theory development approach

8. Understanding Participant’s World

• Researcher observes, questions, listens
• Describe culture by focusing on process
• How people interact
• How people create/modify rules
• Track progress
• Examine preconceptions
• Pose as naive outsiders
• Analyze participant’s reality
• Engage with respondent’s life
• Investigate circumstances

9. Cumulative Process

• Initial data leads to theoretical concepts
• Leads to additional data acquisition
• Grows into cumulative spiral
• Induction Method:
  • Start with broad topic of interest
  • Generate and test hypotheses after data collection/analysis
  • Data collection and analysis most important

10. Focus on Limited Cases

• Attention on single instance or limited cases
• Study for lengthy period
• Labor-intensive data gathering
• Extremely in-depth study
• Vast amounts of data from limited informants
• Analyze results thoroughly

11. Primary Data Sources

• Main Sources: Unstructured interviews and observations
• Additional Sources:
  • Public and private documents
  • Official statistics
  • Questionnaire data

12. Unstructured Data

• Data undergoes cursory pre-structuring
• Observations and interviews described as ‘unstructured’
• Minimal prior organization

13. Verbal Presentation

• Findings typically given verbally
• Descriptions and explanations of phenomena
• Quantification: Employed infrequently
• Statistical Analysis: Used quite infrequently

14. Observer from Participant’s Perspective

• Observe from informant’s perspectives
• Social reality is subjective
• Reveal people’s interpretations and meanings

➥ STRENGTHS AND WEAKNESSES OF QUALITATIVE RESEARCH

STRENGTHS

1. In-Depth Understanding

• In-depth understanding of people and phenomena
• Includes meanings individuals ascribe to events
• Data often gathered in natural environments:
  • Places where people live
  • Where people work
  • Where people spend time
• Gives insight into:
  • Respondent’s views
  • Attitudes
  • Situations
• Uses questions developed on the spot

2. Flexibility

• Method carried out in flexible manner
• Researcher can make adjustments based on emerging data
• Helps gather exceptional or uncommon circumstances
• Beneficial to examine specific isolated instances

3. Aids in Developing Theories

• Useful for exploratory research
• Can be initial stage in quantitative research
• Highly helpful in theory development
• Considers environment where behavior occurred
• Acknowledges behavior cannot be studied in isolation
• Other elements (organism) equally significant

4. Provides Explanation

• Offers explanations of underlying causes
• Can be verified by quantitative techniques afterward

5. Aids in Tracing Behavioral Changes

• Examines behavior as dynamic process
• Person observed over extended period
• Enables tracing changes in behavior over time

6. Adaptable

• Enables adjustment/omission of processes
• According to research requirements
• According to data needs
• Example: Face-to-face interview allows:
  • Quick changes to interview schedule
  • More probes in subsequent interviews
  • Additional lines of enquiry
• Researcher determines aspects of context and setting

WEAKNESSES

1. Expensive

• More expensive despite smaller sample sizes
• Requires significant:
  • Time
  • Effort
  • Money

2. Findings Cannot Be Generalized

• Limited sample size
• May not be representative of community
• Generalizing outcomes extremely challenging
• Replicating outcomes extremely difficult

3. Protracted and Time-Consuming

• Process is drawn out
• Takes lot of time
• Expensive
• Requires expertise of qualified professional

4. Does Not Have Sufficient Reliability and Validity

• Both difficult to determine
• Coefficients cannot be computed
• Absence of standard and consistent questions
• Absence of standard and consistent responses

5. Requires Extensive Training

• Researcher needs extensive expertise
• Otherwise data can be overwhelming
• Difficult to distinguish relevant from irrelevant
• Without training, hard to identify what’s important

6. Biased

• Findings affected by researcher’s:
  • Personal preferences
  • Peculiarities
• Makes them less reliable

• DIFFERENCES IN QUALITATIVE AND QUANTITATIVE METHODS

Definitions

Quantitative Research

• Inquiry into identified problem
• Based on testing a theory
• Measured with numbers
• Analyzed using statistical techniques
• Goal: Determine if predictive generalizations hold true

Qualitative Research

• Purpose: Understanding social/human problem from multiple perspectives
• Conducted in natural setting
• Involves building complex and holistic picture
• Studies phenomenon of interest

COMPARISON TABLE

Aspect	Quantitative Research	Qualitative Research
Sample Size	Can handle very large number of cases	Cannot easily deal with large number of cases
Overview	Provide broad overview of situation	Do not always provide overview
Generalizability	Produce generalizable findings	Produce findings more specific to context
Analysis Methods	Use established, standardized methods	Do not have well-established rules for analysis
Comparison	Enable comparison across different data sources	Generate data harder to compare
Aggregation	Enable aggregation and summarization	Do not allow easy aggregation or summarization
Data Recording	Result in data easy to record, store, process	Generate data hard to store and process
Decision-Maker Value	Generate findings valued by many decision-makers	Generate findings may be treated with suspicion

• ETHICS IN RESEARCH TRADITIONS

Definition

Moral standards that guide research activity. Ethical dilemmas occur when opposing standards must be resolved.

Professional Organizations

• American Psychological Association (APA)
• British Psychological Society (BPS)
• Provide extensive ethical principles with substantial overlap

➥ INFORMED CONSENT

Definition: Principle requiring potential participants to receive information before data collection

Requirements:

• Participants aware of expected outcomes
• Information provided before data collection
• Allows informed decision about participation

Special Cases: For infants or children: Parents must be informed and provide consent

➥ VOLUNTARY PARTICIPATION

Principles:

• Participants should choose between participating or not
• Free choice without coercion
• No excessive inducement
• Can withdraw without penalty:
  • Once study begins
  • At any stage of study

➥ MINIMIZING HARM

Researcher Responsibilities:

• Take reasonable precautions
• Reduce harm where predictable
• Reduce harm where unavoidable
• Ensure safety of:
  • Research participants
  • Others they work with

Areas of Concern:

• Research equipment
• Tasks
• Handling of sensitive information
• Must be done with utmost care and responsibility

➥ CONFIDENTIALITY

Principles:

• Study participants entitled to privacy
• Researcher must protect privacy
• Maintain strict confidentiality over disclosed information

Rules:

• Information only used for research purposes
• Never share with other interested parties
• Under no circumstances should information be shared

➥ USE OF DECEPTION

General Principle:

• Researcher should refrain from misleading participants
• Should not deceive about study purpose
• Unless no other option exists

When Deception May Be Necessary:

• Certain research cannot be conducted otherwise
• Too much information beforehand would skew results
• Required to obtain valid data

Requirements:

• Decision must be approved by third-party expert
• Considerable thought over consequences
• Must consider legitimate reasons

➥ DEBRIEFING

Definition: Providing information to participants after study concludes

Purpose:

• Aid understanding of research
• Especially crucial if study involved deception

Requirements:

• Guarantees participants leave in same condition as arrival:
  • Physical condition
  • Mental condition
• Should provide comfort
• Should provide relevance
• Occur as soon as possible
• Encompass as much information as possible

➥ SHARING THE RESULTS

Researcher Obligations:

• Follow up with participants
• Inform them of study’s findings
• Meet participants’ expectations

Benefits:

1. Meet Expectations: Provide closure to participants
2. Feedback Opportunity:
   • Get feedback from participants
   • Occasionally provides fresh perspective
   • Can offer new insights on findings

• REFLEXIVITY IN RESEARCH

Definition (Wilkinson, 1988)

Reflecting on oneself as researchers:

• How subjectivities influence research
• How biases influence research
• How perspective is affected by investigation
• Vice versa

Key Concepts

Positionality:

• What we are aware of
• What we have come to believe

Reflexivity:

• How we deal with information we have

➥ Reflexivity as Analytical Reflection (Willig, 2013)

Encourages Thinking About:

• “Hows” of study
• “Whys” of study
• Critical evaluation of:
  • Usefulness
  • Morality
  • Worth of participants
  • Worth of subjects
  • Worth of methods

➥ Core Question (Lazard and McAvoy, 2020)

“What is the research process and how am I impacting it?”

Process (Barrett et al., 2020)

“Process of disciplined self-reflection”

• Continuous process
• Forces researcher to:
  • Modify thinking continuously
  • Reconstruct thinking continuously

REFLEXIVITY VS. REFLECTION

Aspect	Reflexivity	Reflection
Timing	Conscious, active during research	Often done in past tense
Focus	Acknowledgment of belief, prejudice, judgment at any stage	Insights on specifics “lost” during initial study
Nature	Critical	Retrospective
Nature	Throughout all research stages	After initial research process

Applications Across Research Types

Traditional View:

• Reflexivity = defining characteristic of qualitative studies
• Essential component for many years

Contemporary View:

• Growing literature on reflexivity in quantitative research
• Helpful tool for quantitative research as well

Particularly Useful For:

• Social psychologists
• Personality psychologists
• Those dealing with sensitive issues:
  • Prejudice
  • Stereotyping
  • Discrimination
  • Socioeconomic class
  • Gender
  • Voting behavior
  • Group violence

Capacity of Reflexivity

Advantages:

• Larger ability to direct research methodology
• Across all research epistemologies
• Across all research techniques
• More powerful than simple reflection

Why Important:

• Can actively engage divergent ideas
• Different perspectives can work towards shared objective
• Shared objective: Expanding understanding