Research Methods Flashcards
Qualitative data
Non-numerical info, nominal or ordinal data
Methods of collection: interviews, focus groups, observations
Example: background info for comp, neighborhood, or transportation plan
ordinal v nominal data
nominal = non-numerical, non ranked ie. male or female, single or married
-weak measurement can’t use mean etc.
non-numerical = ranked categories in orders
Quantitative data
numerical; interval or ratio data
Methods of collection: surveys, censuses, records; to id patterns/correlations
continuous v discrete data
continuous= a range of values which can change ie. time; ie. height, GPA
discrete= one single measurement, finite number of values; ie. # of people
interval v ratio scale
interval= dif b/w numbers but no 0, i.e. temperature, properties of magnitude
ratio= dif b/w number has absolute zero point, used for ordering numbers
mean
average- total of #s divided by amount of #s
median
middle value of #s when in order
mode
value that shows up the most (most repeated value)
range
largest # - smallest #
standard deviation
Average amount of variability in your dataset. *sq root of variance
On average, how far each value lies from the mean.
high standard deviation = values are generally far from the mean
low standard deviation i= values are clustered close to the mean
variance
measure of dispersion, how far a set of numbers is spread out from their average value
z-score
of standard deviations a value is from the mean of a given distribution; ids outliers in a set of data
negative z-scores = value lies below the mean
positive z-scores = value lies above the mean
Independent v dependent variable
Ind= cause, what the researcher wants to explain
Dep= effect, its value depends on changes in ind variable
Linear regression
Finding best fitting line between data points plotted on graph y=bx+a
y= predicted score, b=slope of line, a=Y intercept
Used to find relationship b/w 1 dep variable and 1 or more ind variables
*dif from T-test (hypothesis test) = if dif b/w averages of two groups are significant or not)
decennial census
Every 10 years
age, sex, race, Hispanic origin, migration, ancestry, language use, veterans
population estimates and projections
American Community Survey (ACS)
Nationwide survey used to understand changes in the population (3.5 mil sample size)
detailed social and economic characteristics; education, housing, jobs, and more
Help policymakers, planners, business owners, to make decisions
Experiential learning
Hands-on experience in communities; chance to apply theoretical concepts to real world contexts
Methods: fieldwork, case studies, simulations
Participant observation/ethnography
research methodology where the researcher is immersed in the day-to-day activities of the participants
Oral Histories
Personal stories & firsthand accounts; documents historical and cultural elements of community
experimental
quasi/non-experimental
mixed-methods
experimental = manipulating one variable to determine if this causes changes in another variable, random assignment
quasi/non-experimental = manipulation but not random assignment
mixed-methods = both quantitative and qualitative data used within the same study
Case study v pilot study
Case study= study of specific group, very small scale, on existing conditions, can gain general knowledge
Pilot study = Small implementation before larger project, can give insight to pros & cons
Precedents & examples
Examine previous projects, case studies and models for references
Best Practices
Methods that are superior alternatives; proven to work and provide optimal results
Usually seen as APA guides; PAS reports
Analysis & Reporting
Examining data and info to draw conclusions; both qualitative and quantitative
Surveying
Techniques: questionnaires, interviews, observational studies
*relevance of info depends on collection method
Sources of Data
Where the info comes from
Sources: census, gov reports, surveys, academic studies, spatial data, community feedback
*good sources = better data = better decisions
Metadata
Data about data; will enhance usability and speak to reliability of the data
Unconscious bias
social stereotypes formed outside an individual’s own awareness
*this may affect research and in turn effected communities
GIS
Used to capture, store, manipulate, analyze, manage, and present spatial or geographical data.
Helps to visualize and interpret spatial relationships, patterns, and trends, facilitating informed decision-making
Layered data
Mapping
Visual rep of spatial data
must have - N arrow, scale, legend, title, credits
Spatial analysis
Modeling location-specific problems, identifying patterns, and assessing spatial data to make decisions
Remote sensing
detecting and monitoring the physical characteristics of an area by measuring its reflected and emitted radiation at a distance
Cadastral maps
precise and comprehensive data about specific land parcels in a certain area
ie. plat maps
Modeling
Representations of urban environments to simulate and analyze spatial dynamics
Can predict impact of planning scenarios on transportation, land use, environmental sustainability, and urban growth
Relevance
Does the data directly address questions and objectives? Needs to to inform effective decisions
Validity
Degree to which a study accurately reflects the specific concept intended to measure
Want high validity
Reliability
Consistency of a measure or method; you get same results under consistent conditions
You want dependable data, to greatest extent possible
Data quality
Assessed via accuracy, completeness, reliability, and relevance
Essential to produce valid research outcomes
Implicit bias in data
Could be bias in the actual collection of info, ensure this doesn’t happen so data is accurate
Passive data gathering
collection w/out direct interaction to understand conditions and trends
Ie. traffic cameras, social media, sensors, public records
Active data gathering
Direct engagement with participants to actively solicit information
Ie. surveys, interviews, focus groups: Field research
Community involvement in data collection
Engaging residents & stakeholders in the planning process; must know their needs, concerns, preferences
Ie. public meetings, workshops, community advisory boards
Stakeholder engagement
identifying, understanding and involving people who have a stake in the outcome of the plan
includes ongoing communication, listening, and collaboration
Civic engagement
focuses on participation in either political activities, community activities or both for the good of the whole community
Alinsky organizations (Saul Alinsky)
Community members participate, lead, and engage in change-making, rather than acting as observers through employing social action
*helped poor people fighting power and privilege
Ladder of Citizen Participation
citizen involvement in planning processes showed participation ranging from low to high
1 Manipulation and 2 Therapy. Both are non participative. The aim is to cure or educate the participants. The proposed plan is best and the job of participation is to achieve public support through public relations.
3 Informing. A most important first step to legitimate participation. But too frequently the emphasis is on a one way flow of information. No channel for feedback.
4 Consultation. Again a legitimate step attitude surveys, neighborhood meetings and public enquiries. But Arnstein still feels this is just a window dressing ritual.
5 Placation. For example, co-option of hand-picked ‘worthies’ onto committees. It allows citizens to advise or plan ad infinitum but retains for power holders the right to judge the legitimacy or feasibility of the advice.
6 Partnership. Power is in fact redistributed through negotiation between citizens and power holders. Planning and decision-making responsibilities are shared e.g. through joint committees.
7 Delegation. Citizens holding a clear majority of seats on committees with delegated powers to make decisions. Public now has the power to assure accountability of the program to them.
8 Citizen Control. Have-nots handle the entire job of planning, policy making and managing a program e.g. neighborhood corporation with no intermediaries between it and the source of funds.
- Privacy & Confidentiality concerns w/ data
Ethical and legal obligations to protect individuals’ personal info, to ensure trust and compliance
Ie. anonymizing data, obtaining informed consent, follow data protection regulations
Participatory Action Research (PAR) techniques
engaging community members as active participants in research process through cycles of reflection – data collection – action
Survey design & implementation for community feedback
Questionnaires need to be clear, unbiased and relevant
Select appropriate distribution methods ie. online v in person, to get max engagement
Max engagement = more valuable insights = informed decision making
Focus groups & community workshops
Interactive sessions to discuss planning issues, need to be diverse to have all perspectives id needs & build consensus
Facilitates open dialogue & fosters community involvement
