CRJ 301

• Data sources that do not normally mean the use of numbers
• Collect numerical data to explain, predict, and/or control phenomena of interest 
•  

• Types of designs
•    Survery: Interviews, Mail, Telephone
•    Field research: How many vehicles run a certain stop sign 
•    Existing data (secondary data): data has already been gather by a researcher for another purpose

• Closed ended- List of answer choices
•    Number of Points of Scale
•    Don't Know Response
•    Unbalances scale
•   

• Open ended
• -provide participants an opportunity to respond using their own words or numbers
• -preferred over closed-ended questions when the researcher does not want to influence the participants’ answer by offering them a response choice
• -obtaining richer data than if researchers had asked the same question in a closed-ended format
• Conflicting opinions•
•     Cons•the cost outweighs the benefits because they add little additional information
• •correlated with closed-ended ones or provide no additional predictive information
• Pros•open-ended responses to be more valuable than closed-ended ones•
• Often skipped

• Question Wording
• Complexity
• Double- Barreled Questions
• Valence
• Respondent Demographics
• Referent

• Research ethics
• A general category of how the moral rights and responsibilities will be managed throughout the project
• Emotions-Will anyone be harmed psychologically, what sort of issues might the researcher and researched confront?
• Politics- Who says how the research is conducted and what happens to the findings once published
• Danger- Will the researchers or participants be placed in any physical or psychological danger as a result of the project?

• Required of research done at universities receiving federal funding
• Formally designated to approve, monitor, and review research involving humans
• Can approve, require modifications in planned research prior to approval, or disapprove research
• Must complete a lengthy approval process
• Must provide board with several pieces of information
•   All questionnaires
•   Recruitment language
•   Debriefing forms
•   Number of participants needed

• Population- all of the elements we are interested in studying
• Sample - subset of elements fromt the larger population

• Single- stage sample
•   sampling units are the same as the elements Multi- stage sample 
•   multiple sampling units, but only one smapling unit may be the study's element

• 2 types
•   sample generalizability- ability to generalize from a sample to the population the sample was taken from 
•   cross- population- commonly referred to external validity
•    ability to generalize form finding about one group, population, or setting to other groups, populations, or setting
•      Ex: UNR students to All college students

• 2 types
•   Probability Sampling- know in advance the likelihood of selectin any element of a population
•   Probability of selection
•      Ex: coin toss>>.50 probability
• Random selection- every element of the population has a known and independent chance of being selected into sample

• Incomplete lists
• Inadequate response rate

• Simple Random Sampling
•   Random digit dialing
•   Replacement sampling 
•   Sampling withou replacement

• Systematic Random Sample
•   Randomly select first element and then every nth element selected after
•       3 steps

•  Infor known about population beforehand
•    All elements in population distinguished according to some relevant characteristic
•  Proportionate stratifies sampling- selecting participants based on proportion of size in the population 
• Disproportionate stratifies sampling- selecting particpants regardless of proportion of size in the population
•  

• Naturally occurring aggregate of elements of the population
•    2 stages

• Elements do not have know probability of being selected
•   4 methods 
•     Availability Sampling
•     Quota Sampling 
•     Purposive Sampling
•     Snowballing Sampling

• Unit of analysis
•   the thing being studied
•     Typically people/individuals in criminal justice
• Level of analysis•
•    location, size, or scale of a research target
•    typically “individual” versus “aggregate”

Making inferences about individuals based on aggregate level data

• Ratio- interval with a  true zero
• Interval- 0 to 10
• Ordinal- rank order
• Nominal- label

• Whether particular measure will get the same results after being applied several times•
• Reliability does not ensure accuracy
• Reliability problems come up often
•     Single observer
•     Two observers
•     Questions people don’t know answers to
•     Questions that aren’t relevant
• Checks on reliability•
•  Test-Retest
•  Interrater Reliability
•  Split-Half

• Are you measuring what you say you are measuring?
• Face validity
•   Criterion-Related validity
•   Construct validity
•   Content validity
• Multiple measures
•  Using more than one measure to validate responses
•  Example à survey asking people how many crimes they have committed

a set on interconnected statements or propositions that explain how two or more events or factors are related to one another

• Has all the answers
• Avoids tests
• Blind to opposing evidence
• Highly partial
• Has contradictions

• Incomplete
• Welcome tests
• Changes based on evidence
• Neutral
• Seels logic

• Similarities
•   Assumption
•   Explains the social world
•   Offers a system of concepts/ ideas
•   Specifies relationships among concepts

Abstract ideas that are created to explain our reality

• 1. Idea Formulation- beginning state of research design
• 2. Conceptualiztion- general to specific
• 3. Operationalization- abstract concepts into "real world" measures
• 4. Sample Selection- need to select a represetative group of the population
• 5. Data Collection
• 6. Data Analysis