CJ 280-002 Final Exam Study Guide
CJ 280-002 Final Exam Study Guide CJ 280
Popular in Research Methods
Popular in Criminal Justice
This 25 page Study Guide was uploaded by Jennifer Gintovt on Sunday May 1, 2016. The Study Guide belongs to CJ 280 at University of Alabama - Tuscaloosa taught by Matthew Dolliver in Spring 2016. Since its upload, it has received 83 views. For similar materials see Research Methods in Criminal Justice at University of Alabama - Tuscaloosa.
Reviews for CJ 280-002 Final Exam Study Guide
Report this Material
What is Karma?
Karma is the currency of StudySoup.
You can buy or earn more Karma at anytime and redeem it for class notes, study guides, flashcards, and more!
Date Created: 05/01/16
CJ 280002 Final Exam Study Guide Test 1 material: The point of arguing: Argumentation is o “Reason giving” –Aristotle Ethos, pathos, logos o Care about answers o It could be otherwise o A way to support claims o Helps us to make sense of the world Purpose of research? Exploration – taking a deeper look at the things that happen around us look at something that hasn’t really been looked at before Description – the story of scope and process help explain something to someone else Explanation – why, exactly? help us gain a deeper understanding Application – evaluation v. problem analysis testing it out o Evaluation –knowing what’s happening when you go into the application o Problem analysis – after the fact analysis; digging deeper into fixing what may not be working Making information known Dialogue o Ultimate building process Inductive vs. deductive logic/argument o Inductive – from specific to general o Deductive – from general to specific All a’s are B’s and all B’s are C’s…and therefore all A’s must be C’s Problem: can’t learn anything new The Diversity Bonus Cognitive Thinking differently, but working together o Ex. Number of Nobel Prizes handed out vs. how many people have received them Individual vs. teamwork Fallacies Systematic error in argument o Authority –should we always be turning to experts? Ex. Doctor tells you to do something… Not always right Lack info Difference of opinions The “halo effect” o Tradition, common sense, and crowds Ex. Shaking hands, 2+2 Dismiss evidence, validate assumption? Can we think about it in different ways? Post Hoc ergo propter hoc (after, therefore, because) o Simply because one thing follows another doesn’t mean that the first thing caused the second Ex. Sports The key to causation False dichotomy (duck or bunny problem) o Two options (yes/no, right/wrong…etc.) Ex. Thirsty? You have to drink Coke because you don’t want to drink sewer water Causation, creative and exhaustive Personal experiences o Inaccurate Observation – Change Blindness o Overgeneralization samples and replication One experienced defines your view on possible future experiences o Attribution Errors belief and behavior? Attributing a behavior to something that doesn’t quite work o Selective Observation – Confirmation received! Choosing to ignore or pay attention to specific aspects Is it what it looks like? Reliability dependability or consistency o Ex. Weight on a scale o Having many different kinds! Validity – “true/correct” or the fit between… o Ex. IQ testing? o “Am I measuring what I think I’m measuring?” R & V – both at the level of the study or the measurement Measurement Validity Face – judgment of others… dialogue! o Ex. 2+2 and other problems… Content – Definitions on their face o Ex. Police performance o What if you leave something out? Criterion – using the standard o Concurrent – Association Ex. SAT scores and college o Predictive – distinct but related o Pilot testing for prediction! Null Hypothesis The status quo is going to win Point of stasis o Starting place o Null isn’t changing (nothing is going on here) We assume for the status quo we’re assuming that nothing is going to happen Valuable because you want to prove null hypothesis wrong Valuable for exploring new areas, supportive of a research hypothesis Research Hypothesis Your statement o More narrow and directed set of possibilities A statement, not THE statement Directional? o EX. Group X’s average score will be different (or higher/lower) than group Y on test Z o Falsification if I don’t take a stand then I can never be wrong which makes theory invaluable to us Want to make a good hypothesis Be clear State the expected relationship Reflect theory and/or literature To the point Testable Control Variables Strain them out Ceteris Paribus o “all things being equal” EX. IQ, age, race, and SES – the crime connection Moderator Variables Impacts the strength of the relationship/effect EX. Stress coping crime Mediator Variables Explains the relationship/effect Spuriousness The “lurking variable” EX. Ice cream and crime o If ice cream sales (represents hot temperature) increase, then crime increases (due to the fact that there is higher levels of interaction between victims and offenders) Putting the cause in because Causation prediction and retrodiction o Hume (1700s) Treatise on Human Understanding Causation doesn’t exist just see one thing after another 3 parts Must be correlated, or vary together (when we see one thing change, we see another thing change) o Complexity means looking at aggregates and patterns Time order o Post Hoc No outside factors o Makes causation hard Necessary and Sufficient conditions o Necessary –must be present o Sufficient – numerous ways to do something Constraints on data: Units of analysis o Nominal (“name”) grouped by quality Breaking things into groups by NAME ONLY EX. Political parties divided within a room o Ordinal (“order”) – group + order EX. Tall people ordered separate from short people o Interval (“spaces between walls”) – difference is obvious EX. Grade on an exam (units) 70% v. 80% o Ratio (“calculation”) just add zero gives true starting point Might not demonstrate any of the behaviors For example, if measuring height, no one will be 0 height Theory and Research Dynamic tension QTE o Questiontestexplain The job of a theory is to explain o Variables and attributes EX. Eye color o Classification and clusters EX. Democracy v. gender, sex, GID Independent v. dependent o Independent variable, dependent variable Independent Variable Dependent Variable Stress Crime Internal consistency Support, modify, replace Research grounds us in observation Critical factors Has this been done before? Can we add to our understanding? Is it doable? What new questions do we have? Hypothesis Take the risk, make an educated guess Measurement Then go out and collect information Analysis Testing the hypothesis Work with hypothesis Look at Reliability & Validity again Consider theory Making sense of all the information Failure to fit? o Is there consistency? Do we need to rework/ modify/ replace something? Generate a “grounded theory” Operationalization P.W. Bridgman (1927) Looking to get at a latent construct Something we are constructing but you cant see it directly o Crime is a latent construct Its an idea that you can’t see How to increase V & R o Standardize and replicate Increase the number of items or observations Gives you a wider range of behavior Eliminate unclear items or measurements Standardize test conditions Prevents external factors effecting your results Minimize the impact of external events Standardize instructions Script for experiments Methods for reliability TestRetest o Same test, same people, different times EX. Observing recruits before and after academy training ParallelForms o 2 forms of the same test correlated EX. Detractor tasks – like memorizing a list InterRater reliability o Compares to raters/ings EX. Training people to observe behaviors Internal consistency o Correlation between items EX. Instead of just observing behaviors, you look at things like a score on a survey Validity method o MTMM (MultitraitMultimethod) Error Anything that cause true score and observed score to differ Types of error o Systematic and random Systematic Bias in the measurement or process Something in the process is wrong every time Random All by chance o Method v. Trait Method From the test, or situation o EX. Hungry or sleepy Trait Something about that person o EX. Someone drinks a lot so they are generally suffering from a hang over and this effects your measurements Sampling Why sample? o Sample – subset of the population to be studied Want sample to be representative of the population o Population – group you want to learn information about o The more elaborate the population is, the bigger the sample will need to be to make an accurate representation 2 basic strategies o Probability v. NonProbability – making inferences Define the population EX. Juveniles, serial killers, etc. Access members Can we actually look at the population we’ve chosen? Select from members “Sampling frame” o Move from overall population to actual people within the sample Drawing from the sample Probability strategies o EPSEM –Equal Probability of Selection Method Simple random sampling – from each member o Randomly selecting individuals o Equal and independent o Must be similar in ALL important respects Problems? Could end up with a sample that doesn’t look like your population Systematic random sampling– start with random point o Allows you to cover area o No need to randomize o Similar members o Equal because the first selection is still random Stratified – proportional “strata” o Intentionally take samples from different groups o Used when you can’t rely on the chance of missing something with randomization o EX. Gender Cluster – when individuals are grouped o Big and structural o Cover a lot of ground quickly and easily o Members might be different EX. Police districts Nonprobability Strategies – chances become unknown Bias Convenience Sampling Quick and easy Not representative and may be bias We can’t know if they really represent the population EX. Being stopped on the street and asked to fill out a survey SLOP – Self Selective Opinion Poll Choosing to be in the sample as opposed to being randomly chosen to be in the sample Automatically a problem o Purposive quota – first people you find that meet the characteristics you’re looking for o Snowball Sampling– gets bigger as you go Access hard to reach populations Hard to get a list and define the people within the population Not representative Test 2 material: Ethnography Comes from anthropology o Putting whole story together o Naturalistic (setting) Field Research o Observation o Complete participation EX. Homeless Researcher becomes homeless for 5 years to fully participate in research o Participantasobserver: taking part of research, making yourself known o Observerasparticipant: taking step back to observe but only participating a little; making no effort to participate o Complete observer EX. Court open to public Good for description/ particular types of motivations Helps get past socially desirable results because researcher eventually disappears into background Good for measuring behavior within cultural contexts, naturalistic interpretation Provides us with the ability to get out into the natural settings Transition between full emersion and complete observation Social Desirability: Ethnography v. other methods o EX. Seat belts Time is great camouflage researcher begin to disappear into the surroundings Once researcher disappears into the background, a person’s natural behavior begins to reemerge …such as not using a seat belt What this means for validity is that… o In some situations you can push past and get more reliable results o EX. Asking questions Reliability and fieldwork Always ways around what we’ve seen The Qualitative Approach: Adds richness + depth of understanding 2 basic approaches Idiographic v. nomothetic o Specific gang v. multiple gangs What is qualitative research? Focus on the way people interpret + make sense of world o Interpretive meaning o Naturalistic – setting Why qualitative? Depth of understanding Trades generalizability for detail Generate new theory/hypothesis Includes a number of particular methodologies Ethnography, Interviews, Historical work Grounded theory: Glaser and Strauss (1967) “Reading” theory out of data Key features o Adaptive sampling Younger sex workers o Theoretical saturation You know where its going Guiding principle: “Truth” v. meaning Ground theory: 4 stages o Codes – what counts o Concepts – groups of codes o Categories – collection of concepts Theory o Relationship b/tw categories of interest EX. Masculinity + gangs Interviews Different type of qualitative approach Can have a number of different structures o Better understanding of personal experiences o Combine depth of understanding o Challenge naturalistic assumption (Qualitative) Interview Verbal interaction between a researcher + participant Follows some type of plan o Themes and codes o Go in with themes with codes that you are trying to confirm EX. Masculinity in the gang Have some ideas and trying to research same/similar ideas Why interview? Increased control over what is known and what can be known Ask questions Going deeper, getting a look inside Structuring the interview: Structured – Q and A w/ a twist o Often prewritten questions o Strictly stick to the questions written, lots of control o Reliability and validity o Closing the ends o Usually used when researchers feel they have a strong theoretical base Semistructured – beings w/ a structure, but then o Not as solid of a theoretical base as the structured interview But need to have some type of evidence Unstructured – (this does not mean no structure at all) o I don’t particularly know what’s going on here, but I want to know To do that I have to be open to possible outcomes o Conversational Back and forth conversation between interviewer and interviewee, flexible o Interview guide – setting limits on scope of the conversation Need to be aware of how to ask questions and get answers… Key decisions Setting o Where can they talk o Providing an environment where they are most comfortable opening up Insider/outsider status o Developing a rapport yes and no EX. Drug dealers and Convict Criminology Recording data o EX. Hidden camera, something you tell them is there but its less intrusive and they eventually forget its there Analysis Cleaning and coding – increased flexibility Themes have a different meaning here Historical Research Time Historiography o Time is important because it helps us to understand the strength of our research The Time Dimension in Research: Crosssectional o Looking at a specific area of time or time frame Longitudinal o Looking over years of data o Trend studies UCR o Cohort studies Growing up o Panel studies NCVS There are drawbacks Time At work in all research o Historical research make particular use of time Historical research: development of context around issues EX: Delinquency, IPA Follows scientific method o Defining topic o Hypothesis o Seeking evidence Sources of evidence Primary o Documents Legal papers, newspapers records o Oral histories 1 person accounts o Artifacts/remains Tools, buildings, etc. Secondary o Summary stats, oral history Test 3 material: Quantitative research Nomothetic o Looking at generalizability and link cases Role of numerical modeling o The use of numbers o Type of measurement is key Wanting to generalize and link things together o Using numbers up front 2 major types Observational Experimental Best for standardization o Why does it matter? You don’t want somebody to be different “all things being equal” courts, opinions, sensitivity, characteristics what numbers are good for ___% is white ___ amount of population is against death penalty Survey methodology: an interview with closed ends o closeended questions & highly structured thought about questions and standardized closed ends so answers are standardized binary scale o usually only have 2 options o male/female; agree/disagree o good because we can code easily & then do stats easily or 1 o false dichotomy have to be careful about if it is really as straight forward as yes or no Likert scale o “feeling thermometer” numerical value of your feeling agree 0510 disagree in 2 styles let somebody be neutral o 110 make somebody answer o 19 Developing good questions: exhaustive V. (mutually) exclusive o want to be both o exhaustive – avoided false dichotomy by giving people all of their options EX: income A.) 30k60k B.) 60k90k C.) 90k + Problems: o You still might not be included which means you failed to be exhaustive o If you make exactly 90k you don’t know how to answer so you make sure categories don’t overlap Exclusive o Making sure you only offer 1 category for people to fall into Doublebarreled problem o Asking 2 questions but only giving one response for one of the questions EX: should gov. abolish death penalty and release all prisoners on death row? Short, quick, and clear (7 grader rule) o Avoiding attrition dropping out o Want questions to be on a 7 grade reading level o Do it partly so people can go through it pretty quickly Bias o Wording and halo effect o Halo effect is a fallacy of authority EX: many researchers think…what do you think? o Can be subtle or profound Administering surveys 3 styles o selfadministered; mail, email, in person o inperson – interview o telephone rapid and high response rate Observational Designs II Secondary analysis What is secondary data analysis? Primary vs. secondary o Primary: data that you collect directly o Secondary: data collected by someone else VALIDITY All about asking right questions Number of sources o Official gov’t stats EX: UCR o Nonpublic agency records EX: Court case load stats o Primary collection data Researchers reaching out to other researchers EX: crime and victimization Right time, right place Evaluation and the dark figure of crime o Figures that don’t get reported o Matching questions + measures Asking right question o Definitions, procedures, and responses EX: homicide in early 1900s o Keep track of unites EX: forming groups o Errors increase with volume The more data you collect, the more likely you are to encounter errors When do we use secondary data? Money, time, energy, information o Secondary data allows you to span all these things without ever having to take part in them Gives access to data you may not have had access to any other way o EX: UCR – SHR, court records Able to fill in the gaps by combining information. o EX: dates, locations Probability 1 Probability is important! Counterpart to randomness o Randomness is a subtle but incredibly powerful concept Any one particular even is unknown (the outcome is unknown), and yet the outcome of aggregates is very well known How do you know something is random? Because you don’t know what is going to happen ahead of time Humans have free will Our own measures contain errors Generally we conduct analysis on a sample Probability Independent random events grouped together, always produce order/patterns A measure of how likely an event is to occur o Ranges from 01 The higher the probability, the more likely a particular outcome is Definitions… Experiment: o Repeatable procedure for making an observation or measurement Outcome: o A possible result of an experiment Sample space: o The set of all possible outcomes of an experiment Event o Any subset of the sample space of an experiment Mutually exclusive events: Events = mutually exclusive if there is no overlap between the two events o Ex: in Venn Diagram, they do not share a common region Which means events can occur simultaneously EX: getting both a 1 and a 6 on a roll of a die Probability 2 Randomness: Probability helps describe randomness o Individual results v. aggregate calculations Law of Large numbers o Tells us that random events don’t care o Gamblers fallacy The coin doesn’t care about the outcome, but we do I feel like I’m due for a win, because I know I have a 50/50 shot, so I continue to bet Viewing some events that are actually equally likely as being more rare EX: rolling a die and getting a 2 Order arises from groups of random events! o Think about coin flipping example Implications for equal selection We converge on probabilities o I know I will get a little bit of everything if my sample is big enough Small events matter Rare events Must happen because of chance o Rare events happen through chance alone Winning the lottery even though you literally have no chance of winning So why does it matter? Lurking variables Controls for bias The Experimental Design, Part I Treatment: If you have a treatment you are running an experiment The thing in our control as a researcher that we get to introduce or take away o Looking for cause and effect relationship (True/Classical) Experimental Designs o Treatment A new way of doing research o The role of cause and effect Causation’s 3 parts and 2 conditions Hume 3 parts o Correlated o Time order o No outside factors 2 Conditions: o Necessary must be present o Sufficient – numerous ways to do something The goal is to get everything The use of control v. experimental groups o Comparison The only difference between control v. experimental group is the treatment If we see that the group that got the treatment experienced a different result than the group that did not receive the treatment, then we can conclude that the different result was due to the treatment The Savana Effect o Randomness – selection or assignment? – its about both! When we take a sufficiently large random sample we don’t have to worry about getting absolutely every different characteristic The large random sample ensures that we get the differences we need 4 step process: Assignment Pretest o Gives you a baseline Treatment Group Pretest x Posttest 1 X X X 2 x x Postte 3 x x st 4 x x Sever al common variations o The Solomon four–group design This gives you every possible combination You really know if what you think is happening is really happening Double v. Single Blind designs Blindness refers to what you understand about the study o Singleblind = participants don’t know what group they’re in o Doubleblind = participants AND researcher don’t know the groups The Classical Experiment, Part II Science in the “real” world “Ceteris paribus” – all things being equal – the model experiment o Controlling outside factors in the lab History Certain events cause people to act differently, such as being on high alert Maturation Peoples views, preferences, etc. begin to change Attrition, and others Process of gradually reducing the strength or effectiveness of someone or something through sustained attack or pressure o Controlling inside factors Pretest The Hawthorn effect Are we getting a socially desirable response Finding the perfect match: QuasiExperimental Designs o Experiment with a key difference Randomization o What about threats to internal validity 2 equal groups Someone can always find something that doesn’t quite match between two groups/subjects o Why use it? Ethical considerations EX: abused children turn into criminal adults? Or police officers coming in and out of the academy Nonequivalentgroups design o Matching on key factors o Matching on “types”/unites EX: classes at the academy Natural Experiments Experiment with a key difference o Treatment is “natural” (or unplanned) o Randomness is still the key but with a twist Threats to internal validity o Time or groups Why use it? o Unethical or impractical Think about scale EX: smoking ban and death penalty IRB’s, Ethics, Grants, and Funding Ethics: Professional code of conduct o Human (and animal) subjects Harm, risk, and rewards balancing act o Different from morality because morality is a person’s belief IRB: Internal Review Board o Maintaining and adhering to ethical standards o Gov’t and nongov’t organizations o Judge risk/reward AND safeguards to be used o Focus on Harm, risk, rewards EX: medical study o Internal to structure of institution o Review all studies that are coming through o Weigh out: Potential harms and benefits o Composed differently based on institution Research at one institution may get past an IRB while it wouldn’t at another institution Stanford Prison Experiment Remuneration: Incentivizing people (ex. Giving gift cards for participation) Paid for your work: (Research) Grants: o Monetary award Competitive; you make your proposal o Government, Nonprofit organizations Contributed to intellectual and social development o Major sources include NSF (National Science Foundation), NIJ (National Institute of Justice), NIH (National Institute of Health; Drug research) NIJ COPS office o Focused on departments nationwide that wanted to institute Community Oriented approach UA internal grant funding (seed funding; they give you a little money now with the hope that it will turn into a lot of money later) OSP and Pivot Giving a Presentation/Writing a paper The Hour Glass Paper formatting o Starting with large overarching idea o Bringing it in to more specific details o Coming back out to answer “so what?” or “why should I care?” Creating a conversation: You start with a question Use of “elaborative encoding” to bring them in Helpful tips: Rewards for progress Someone to check work Stop in the middle of line or section Skip around, let work come to you Pocket paper Although, nevertheless, because, thus o Many argue, and I agree…however o New evidence, old way o Old evidence, new way o Old evidence and old approach, new way Selfquiz Matching: A. Choosing to ignore or pay attention to specific aspects 1. Pathos _____ B. Dependability or consistency 2.Ethos _____ C. Groups of units one observes 3.Logos _____ D. Must be present E. Change Blindness; unable to observe 4. Deductive logic _____ results that are different than what one 5. Inductive logic _____ previously deduced F. Numerous ways to do something 6. Aggregate _____ G. Logic 7. Post Hoc Ergo Propter Hoc _____ H. An educated guess, taking a risk I. Attributing a behavior to something that 8. Inaccurate observation _____ doesn’t quite work 9. Selective Observation _____ J. From specific to general 10. Overgeneralization _____ K. Something we are constructing but you can’t see it directly 11. Attribution errors _____ L. Character 12. Necessary Conditions _____ M. “Am I measuring what I think I’m measuring?” 13. Sufficient Conditions _____ N. Anything that causes the true score and 14. Hypothesis _____ observed score to differ 15. Analysis _____ O. From general to specific P. Emotion 16. Theory _____ Q. Not a representative sample and can lead 17. Latent Construct _____ to bias R. After, therefore, because; because one 18. Error _____ thing follows another doesn’t mean that the 19. Sample _____ first thing caused the second S. Group you want to learn information 20. Population _____ about 21. Convenience Sampling _____ T. One experience defines your view on possible future experiences 22. SLOP (SelfSelective Opinion Poll)____ U. Get’s bigger as you go, gives you access 23. Purposive Quota _____ to hard to reach populations, not 24. Snowball Sampling _____ representative V. Created to explain something 25. Validity _____ W. First people you find that meet the 26. Reliability _____ characteristics you’re looking for X. Choosing to be in the sample as opposed to being randomly chosen to be in the sample Y. Subset of the population to be studied Z. Testing the hypothesis 1._____ Ceteris Paribus A. making sure you only offer one category for people to fall into 2._____ Likert Scale B. data collected by someone else C. “feeling thermometer”/ numerical value 3._____ exhaustive placed on feelings D. data collected directly 4._____ Exclusive E. using authority to direct a response F. the thing in our control as a researcher 5._____ Doublebarreled problem that we can induce or take away 6._____ Halo effect G. asking two questions but only giving a response to one question H. all things being equal 7._____ Primary data I. avoid false dichotomy by giving all 8._____ Secondary data possible options J. there is no overlap 9._____ Mutually exclusive 10._____ Treatment Selfquiz: Short answer/ Multiple Choice 1. Quantitative research focuses on _____________. A. Statistics B. Interviews C. Numerical Values D. Meaning individuals attach to things 2. What are the two styles of the Likert Scale? 3. Which of the following is not one of the benefits of using secondary data? A. Money, time, energy, information B. Access to data you may not have had access to otherwise C. Secondary data is not collected directly and therefore may not be correct D. Able to fill in gaps by combining information 4. What are Hume’s 3 parts of causation? 5. Research grants… A. Are a major source of funding for researchers B. Typically come from governmental or nonprofit organizations C. Are competitive D. All of the above
Are you sure you want to buy this material for
You're already Subscribed!
Looks like you've already subscribed to StudySoup, you won't need to purchase another subscription to get this material. To access this material simply click 'View Full Document'