Areas of Research

  • Logistics
  • Costing
  • Suppliers
  • Contract Opportunities
  • Promotion
  • Staff Performance
  • Environmental Performance
  • Quality Assurance
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Research Basics

  • Research Proposal/Project
  • Literature Review
  • Critical Writing Methods
  • Research Philosophies/Methodologies
  • Sampling Techniques
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Qual & Quant


  • Action Research
  • Archival Research
  • Case Studies
  • Interviews
  • Focus Groups
  • Participant Observation
  • Coding/Decoding data


  • Using excel for Research
  • Understanding Descriptive Statistics
  • Implementing Descriptive Statistics
  • Understanding Tests & Significane
  • Implementing Tests & Significance
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Where do we get data from?

  • Primary Sources
  • Secondary Sources
  • Ensure it is balanced, relevant, reliable, ethical
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What is Research?

Systematic, Comprehensive, Thorough -  In order, covers everything that is relevant or choose an area of study to cover

Seeks to discover the truth - Finds questions that needs to be answered & answers them

Results should be trustworthy and meaningful - Meaningful = Value

Trustworthy = sensible approach to research that is repeatable

Builds on existing knowledege & understanding - Adds Layers

Considers what has happened (reflection) - Helps make more informed choices, improves efficency in relation to time and money

Considers what needs to happen (action) - No point if not going to be used or nothing changes

Donald Rumsfield - NATO 2002

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Virtuous Circle of Theory & Practise

  • Research on theory informs practise
  • Research on practise infroms theory
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Research Philopsophy

  • Philosophy adopted depends on the way we think about developing and creating knowledge (Saunders 2000)
  • Considers the practial considerations required for undertaking research
  • Certain philosophies are better suited to certain research problems

Positivism - considered a science, controlled by rules and laws, measuring world around us, emotionally detached, researcher is independant of the research, does not affect and is not affected by it

Interpretivism - science misses the rich details, too complex to be controlled by rules and laws, tries to understand the world around us, empathy, part of the research (sensing)

Realism - what we sense is reality. Direct Realism - operates on a single level in an unchanging world. Critical Realism - operates on multiple level in constantly changing world (processing and sensing)

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How we view reality?

  • Positivism - Objective, independant of social actors
  • Interpretivisim - Subjective, socially constructed upon social actors 
  • Realism - Objective, independant of social actors but interpretated through our social conditioning 
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What we deem as acceptable knowledge?

  • Positivism - observable phenomena to provide credible data and facts
  • Interpretivism - social pheenoma to provide subjective meaning 
  • Realism - focuses on explaining social world around us using observable phenomena (facts and data)
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Deductive Approach

  • Testing Hypotheses to find relationships
  • Collecting/analysing data (testing theory)
  • Quant
  • Researcher is independent of research
  • Characteristics are measurable 
  • Results are generalisable so large sample is required
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Inductive Approach

  • Exploring nature/context of the problem
  • Developing theory from data (creating theory)
  • Views and opinions
  • Qual
  • Researcher is part of the research
  • Generalisation not so important so small sample is accepted
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Abductive Approach

  • Moves from theory to data and data to theory
  • Starts with observation and develops contestable theory
  • Quan & Qual
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People to sample

Consider socio-economic groups (varying levels of disposable income)

  • Higher professionals/managers
  • Administrative/supervisor
  • Skilled/Semi-skilled/unskilled
  • Retired, Students, Unemployed

Understanding Generationns

  • Silent Generation - 65+ followed rules, very principled
  • Baby Boomers - 55-64 worked hard, golden times, high disposable income
  • Generation X - 35-55 IT aware, low disposable income
  • Generation Y - 20-35 grown up with tech, individualistic, value their own time
  • Generation Z - 0-19 mobile based apps, instant answers, saturated social media

Balancing Data

Religious Views, Political Views, Maritial Status, Home Owner vs Renter, Qualification & Education, Status, Gender

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Types of Data

  • Continous Data - can take any value  (e.g time or temp) 
  • Discrete Data - can only take values in a range (e.g integers: no of people)
  • Categorical Data - can be grouped but not measured
  • Numerical data - can be measured
  • Ranked (ordinal) Data - Data that can be grouped but also ranked (e.g agree to disagree, xs-xl)
  • Descriptive (nominal) Data - data can be grouped but not ranked (e.g types of vehicle)
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Why Sample?

  • A census collects data from everyone in a population
  • In reality this is not rational 
  • Extremely expensive, time consuming and often not accessible
  • Use a sample as it is representative of whole population as it considers a range of cases in a meaningful way (Saunders 2012)
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2 Forms of Sampling

non probability - 

  • characteristics often known therefore better for quantitative
  • moving from theory to data (testing theory)
  • generalisation possible
  • always facts/numbers

probabibility -

  •  characteristics often not known better for qualitative
  • moving from data to theory (creating theory)
  • generalisation possible but not on statistical grounds
  • views/opinions
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Types of Probability Sampling

  • Random Sampling - sampling at random across the data
  • Systematic Random Sampling - sampling at regular intervals throughout the data using formula
  • Stratifed Random Sampling - identifying layers in the data and then using random/systematic random in each layers
  • Cluster Sampling - indentifying groups in the data and then using random/systematic in each group
  • Multi-Stage Sampling - too many groups so first random/systematic random sampling but be used to decide which to include
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Fundamentals of Sampling

Saunders et al 2012

  • Larger sample size = lower levels of error
  • Probability Sampling is a compromise between acurracy and time/cost

Sample size therefore considers:

  • level of confidence in results
  • Tolerable level of error
  • Size of total population
  • Number of categories to be included in analysis 
  • 95% confidence = repeated 100 times 95 times would be fully representative of whole population
  • Margin of error usually = -/+3% or -/+5%
  • Smaller the margin of error required = Increased sample size
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Sampling Fraction

Sampling Fraction = Actual Sample Size / Total Population

e.g. 1/4 is every 4 

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Minimum Required Sample Calculation

n = p x q (z/e)2

n = sample size

p = % belonging to a category 

q = % not belonging to a category

z = confidence in results e.g 1.96 = 95%

e = margin of error

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Adjusting Sample Size Calculation

If population is less than 10,000 it is possible to adjust minimum sample size without compromising accuracy

n ' = n / 1 + (n/N)

n ' = adjusted sample size

n = sample size 

N = total population

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Types of Non - Probability Sampling

  • Quota
  • Haphazard - choosing those that are easiest to access for convenience
  • Volunteer - *********** works well when population is hidden/hard to reach. Self- Selection allows individuals to take part on own accord
  • Purposive - designed for specific goal - homogeneous, heterogenous, critical, theorectical, extreme
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Ethics in research

Ethics refers to good practise undertaken in reserach to consider:

  • the use of humans 
  • the use of animals
  • the use of intellectual property (ideas, themes, works)

Should be:

  • Honest
  • Integrity
  • Open to scrutiny from others
  • Respectual to participants
  • Not judge responses
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Physical Access - often granted or rejected by management (e.g. database)

Cognitive Access - recieving support from others involved in the research maybe gatekeepers. Winning hearts & minds

Continuing Access - although inital access has been granted may be an incremental process that requires additional access from other people at different levels

Virtual Access - use of chatrooms, blogs? do you trust them?

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Internal vs External Researcher

Internal vs External Researcher


  • knows the people and practises
  • low risk to organisation
  • may have developed previous relationships/bias perspectives
  • likely to gain required access


  • fresh eyes
  • unkown = increased risk to org
  • increased reliability & validity
  • objective
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Ethical Issues

  • do not monitor emails/calls
  • do not record without permission
  • do not photogragph without permission especially children
  • do not judge participant responses
  • no bribing/incentives
  • no punishment for non-compliance
  • adhere to data protection regulations whe storing personal data
  • opportunity for participants to withdraw at anytime
  • offensive/sensitive/ gender specific language
  • do not cause embarrassment/harm or death
  • Anonymity
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Difference between qual & quant


  • meaning derived from facts/number
  • collect results in the form of standardised numerical data
  • analysis in the form of diagrams/statistics


  • meaning derived from views/opinions
  • collect results through non standardised data requiring categorisation
  • analysis conducted through conceptualisation
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Methods to determine categorisation

1. use categories based on previous works and theories 

2. use categories based on terms used by participants

3. use categories that emerge from data analysis

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Patterns & Prepositions

1. seek relationships and patterns in the data

2. develop testable prepositions

3. test prepositions to ensure relationship exists

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An interview is a conversation between the interviewer asking questions and the interviewee answering them. 

Structured = QUANT

Unstructured = QUAL

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Structured Interview


  • Limited social interaction
  • Standardised questions
  • Pre coded - answers
  • Quantitative data 
  • Interviewer asks questions 
  • Interviewee answers 
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Semi - Structured Interview

  • Extended social interaction
  • Non - standardised
  • Themes to cover 
  • Qualitative
  • Questions may vary
  • Not everyone has same questions
  • Additional questions may be asked
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  • Inital social interaction
  • Agreed theme for interview
  • Interviewer allows intereviewees to speak (non directed)
  • Qualitiative 
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Standardised Questions with Pre-coded answers

  • opinion based questions - e.g agree to strongly disagree
  • belief based e.g always to never
  • behaviour based e.g once a week to everyday
  • fact based e.g age 0-65+
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Semi - Structured Questions

open question

  • normally about situation/event
  • encouraged developmental answer
  • reveals facts/attitudes
  • usually start with what, why or how?

probing questions

  • similar to open questions (what, why or how?)
  • but with a particular focus

closed questions

data gathering


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Should I record the interview?


  • Allows interviewer to focus on what is being said?
  • Ensures accuracy in interpretation as can be played multiple times
  • Enables quotes to be extracted
  • Permanent copy for other researchers to access


  • May adversely effect participants if they are aware they are being recorded
  • Should not solely rely on recording due to technical faults
  • May stop responses from being so open
  • Unsettling
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Problems with Interview Data


  • larger and more representable the sample = more generalisable the findings
  • ACTION ; careful sample selection


  • tone/non verbal behaviour
  • sensitive issues 
  • ACTION: plan & record


  • lack of standardisation = lack of variability 
  • ACTION: seek trends/issues not details

validity - ability to interpret correctly

  • ACTION: seek clarification reguarly
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Validity Matrix

Should you use PM?

1 significant characteristic

  • 1 manager uses + 1 manager does't use = 2 interviews

1 significant characteristic improved

  • 3 managers us + 3 don't use = 6 interviews

2 significant characteristics

  • 3 managers use female + 3 managers don't use female 
  • 3 managers use male + 3 managers don't use male      = 12 interviews

3 significant characteristic

  • 3 F junior use + 3 F junior don't use + 3 F senior use + 3 F senior don't use + 3 M junior use + 3 M junior don't use + 3 M senior use + 3 M senior don't use = 24 interviews
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Focus Groups/Group Interview

  • neutral setting to avoid interuptions/distractions
  • circular seating plan to ensure everyone is equal
  • organised by one person and recorded for data accuracy
  • usually 4-12 people - more complex issue less participants required
  • horizontal slicing - people with similar experiences 
  • vertical slicing - people with different experiences
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Group Interviews

  • wide breadth of points
  • questions asked but also challenge the opinions of others
  • ends when reach an agreed concensus 
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Focus Group

  • Narrow/clearly defined single topic
  • Tolerant environment where nobody's opinion is questioned
  • repeated with different participants to identify strong trends
  • end when saturation point is reached no more new points are made
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Co-ordinator of focus group/group interview

co-ordinator of group interview is FACILITATOR 

  • finding the balance between encouraging discussion and allowing freedom
  • ensures equal opportunity 
  • ensures structure whether that be highly structured (unlikely) to unstructured (likely)

co-ordinator of focus group is MODERATOR

  • dual roles between strictly ensuring participants do not deviate from topic and generating interest in the topic
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  • unpick data to see trends/patterns
  • allows for better understandings of issues/problems
  • ability to make better reccomendations for future action

large amounts of data use NVIVO 

manageable amounts of data use recursive abstraction

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Recursive Abstraction

1. Highlight important text

2. Extract important text

3. Paraphrase

4. Group into themes

5. Replace with codes

6. Check meaning, look for trends/patterns

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6 storage bins for organisational memory

(Walsh & Ungson)

  • individuals
  • cultures
  • transformations
  • structure
  • ecology 
  • archives
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7 types of Archives

  • (Laura Schmidt)
  • Special Collections
  • Historical Archives
  • Museum Archives
  • Corporate Archives
  • Government Archives
  • Religious Archives
  • College/Uni Archives
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5 Stages of Archives

1. Discovery

2. Access

3. Assessment

4. Sifting

5. Cross-checking

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What might you want to Archive?

  • HR records
  • Financial records
  • Payroll records
  • Meeting notes
  • Intellectual property ownership
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Locating Archives

worldcat (Laura Schmidt)

database that lists global archives

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General Data Protection Regulation

  • refers to any data that belongs to an identifiable living person

Actions inclusive of:

  • Manipulating
  • Erasure
  • Recording
  • Retrival
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Action Research

Lewin (1946)

  • social process facilitating change
  • addresses practical problems
  • solves real issues
  • collaborative apporoach (participant involved)
  • Implications for wider organisation

Saunders 2012 - Action Research Cycle

1. Diagnose Problem

2. Plan action

3. Take Action

4. Evaluate Action 

5. Repeat

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Characteristics & Benefits of Action Research

  • Participants must co-operate and become part of the research
  • Descisions are joint
  • Selecting the right participants is essential


  • Participant part of generating outcome means more likely for it to be adopted
  • Increase success = desired impact
  • More likely to be embedded and change behaviours
  • Once noted that behaviour needs to change it is hard to ignore
  • Bottom up approach = positive impact = "fit for purpose"
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(Saunders 2012) Focused on understanding the social world around us through first hand field study

involves looking into people, cultures, habits and mutual differences

  • study groups and relationships that occur within groups
  • output is in the form of cultural account
  • uses language they use to describe themselves
  • detached approach treating participants as subjects
  • researchers often live amongst those being studie e.g. street gangs
  • occurs in their own environment
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3 Types of Ethnography

1. Realist 

  • objective, fact finding
  • meaning through processes, practises, artefacts based on observation
  • 3rd person
  • supported by quotations

2. Interpetive

  • subjective
  • collects impressions to find multiple meanings
  • 1st person
  • supported by quotations and present perspectives

3. Critical

  • investiages the impact of power, privelige and authority on those that are subjected to it
  • may also adopt an advocate role (support)
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Case Study Research

case is a real life situation/event. case study is analysis of this situation/event (Van der Ham 2016)

empirical investigation into particular phenomena in its real life setting (Saunders at al 2012)

one thing in its entirety (Thomas 2011)

  • don't consider details instead consider whole situation
  • consider a large amount of inter-related features oppose to a survey that looks at a small amount
  • consider time, people and contet
  • specify your case to study (is it a thing or situation?)
  • Define parameters (physical/emotional)

Two distinct sections:

the case itself the area of research

the object of research that requires illuminating

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4 approaches to case studies

  • single case often critical/extreme cases
  • sometimes typical case
  • novel investigation or one that very few have covered
  • mutliple case - more than one case covered
  • Are all finding replicated in all studies?
  • similar charecteristics = literal replication
  • differing charecteristics = theoretical replication
  • holistic case - focuses on a single department/org
  • embedded case -  focuses on multiple departments or multiple organisations
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Phase 1 Case Study Research

Description - gathering key facts and establishing context

  • what is being said/done?
  • do others agree? does it contribute to the problem?
  • who is saying/doing it?
  • are they stakeholders?/what is their role?/what is their relationship to others?
  • why is it being said/done?
  • is there a lack of leadership?
  • where is it being said/done?
  • what environment?/does the environment have constriants?/what products/services affected?
  • when is it being said/done?
  • chronologically?/is there a noticeable before/after/is it incremental over time?
  • how is it being said/done?
  • threatening behaviour?/tone?/
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Phase 2 Case Study Research

Analysis, to find how the facts fit together

Van der Ham 2016 - structuring your data

  • identify underlying causes of issue? what contributes, why?
  • develop action plan - who is involved, steps needed, how to monitor success?
  • brainstorm solutions - for org/individual
  • evaluate solutions - due to opportunities of context
  • identify best practise - what does the literature say about best practise?
  • best fit solution - to individuals/org, justify using literature
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Unstructured Participant Observation

saunders 2012

oberservation where researcher becomes member of subjects grouo/org/community participating in life/actvities

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Participant Observation

welch 2000

  • qualitative technique
  • overt observation - awrare of researchers role/identity
  • covert observation - concealed, discovers meaning social actors attach to actions, raises ethical issues
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4 types of Participant Observation

participant as observer 

  • takes part in activity
  • identity revealed
  • e.g joins strikes/shares emotions

observer as participant

  • observes activity
  • identity is revealed
  • purpose is known to those studied
  • e.g. observing team building exercise

complete participant

  • researcher takes part - fully immerses
  • identity concealed

complete observer - oberserves, identity not known, purpose not known

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3 Phases of participant activity

descriptive phase - concentrate on observing describing physical setting, activities & emotions

narrative phase - write up findings & develop framework of theory that helps to explain it

focused phase - concentration on particualar people/events 

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4 types of Data in Participant Observation

contextual data - places research in its setting key roles, org structure etc

experimental data - own views and opinions on what you have witnessed?

primary data - things you have seen e.g. diary noting what/when

secondary data - info from others on thiing you didn't see. Their own interpretation

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Structured Observation

  • predetermined structure to measure observed behaviour
  • quantitative - how often things happen but not why
  • easy to repeat allowing comparision across days and other events
  • researcher is detached focus on observation

e.g. how many times someone accesses a website as a marketing strategy

recording sheet

  • coded responses
  • check everyone understands the code and is using it the same way 
  • make sure it doesn't overlap
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Reliability/Validity Participant Observation

  • ecological validity is HIGH due to social actors being observed in natural setting
  • until observer fully understands research setting may misunderstand
  • but once over familiar may lead to:
  • observer error - lack of understanding or over familiarity with setting
  • oberserver bias - so comfortable with setting no longer objective becomes subjective
  • oberserver effect - change in behaviour as observants know they are being watched

specifically relating to STRUCTURED:

  • informant error - data may be unreliable if observing when under staffed or staff are ill as behaviour may change
  • time error - time data is recorded must be typical period not peaks and troughs in activity
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L8 why quantitative method?

  • data is all around us
  • nearly everything we do leaves a data imprint. (e.g. making decisions, performing effectively, competitive edge)
  • reliable
  • objective
  • reduces complex problems into fewer variables
  • tests hypotheses
  • assumes representative of population
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Questionnaire Design

  • adapt to type of respondent (business, consumer, children)
  • consider method of data collection (postal, face to face, online)
  • keep length to a minimum (max 20 questions)
  • conduct pilot study on small representative sample 
  • don't leave highly important questions till last
  • be as specific as possible
  • don't ask two questions at once
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Types of closed questions

  • dichotomous - only 2 answers (yes or no)
  • multiple choice - 3 + options 
  • numeric - asks for single number (e.g. distance to work)
  • rank order - asks participants to rank in order (e.g. preference)
  • likert scale - asks participants how much they agree with statement
  • personal question - e.g. salary or age. best to use range
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Question Structure in Questionnaires

  • screens - identifies early on whether participant should undertake questionnaire
  • ice breaker/warm up - easy to answer, generates interest in questionnaire
  • transition question - allows questions to flow and link easily
  • skips - e.g. if yes answer Q3
  • difficult - should be positioned in the middle when participant is in the flow (online = progress bar)
  • categorical - often personal questions so should be left till last to avoid participant feeling uncomfortable
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Adv & Disadv of questionnaire


  • practical
  • large amounts of info can be collected in short amount of time at low cost
  • can be carried out by researcher or any number of people without infulencing validity/reliability
  • results quickly/easily quantifitable by researcher or software
  • allows for comparison


  • inadequate to understand some forms of info
  • no way to tell how truthful respondent is being
  • no way to tell how much time they have put into their answer and if they understood context
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Validity & Reliability of Questionnaire


  • questions understood/misunterpretated?
  • undertake pilot study to check they understand questions in the same way
  • construct validity is it measuring what you think it is measuring?
  • internal validity does it cover key points & balanced viewpoint?


  • does data collection techniques provide consistent findings?
  • transparent reporting?
  • repeated by someone else same results?
  • repeated by yourself again on another day same results?
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What are variables? What is data?

  • variables - characteristic of sample that is of interest to research. attribute describing person, place or thing. varies between entities
  • data - actual value of variables, needs to be processed to be extracted and understood

continuous - falls on continuum can have fractions or decimals

discrete - finite number of possible values

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5 scales of quantitative data

  • nominal - categorised but no intrinsic order. No measure of distance between values e.g. eye colour
  • ordinal - categories can be ranked and ordered. Distances between values may be different e.g. education
  • interval - orders values, ability to quantify difference between each one. e.g. temp
  • ratio - order, interval values, calculate ratios due to their being a true & neutral 0. 
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Types of variables

  • dependant - measured in the study. If A influences B then B is independant variable?
  • independant - changed/controlled to test dependant variable?
  • control - held constant, not of primary interest
  • moderator - qual/quant affects direction/strength of relationship between independant/dependant variable
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