CJ 280-002 Exam 1 Study Guide
CJ 280-002 Exam 1 Study Guide CJ 280
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This 10 page Study Guide was uploaded by Jennifer Gintovt on Monday February 8, 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 146 views. For similar materials see Research Methods in Criminal Justice at University of Alabama - Tuscaloosa.
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Date Created: 02/08/16
CJ 280002 Exam 1 Study Guide 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 Description – the story of scope and process Explanation – why, exactly? Application – evaluation v. problem analysis 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 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 Finding Stasis What matters more? o Agree to disagree Things need to be agreed upon upfront before you can really delve into the argument Ex. References, common language, and evidence Stalled out…when an argument isn’t actually occurring then you talk past each other 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 Probability o EX. Women watch more TV than men Null hypothesis would be: there’s no difference between the amount of TV men and women watch When you test this hypothesis and find something different, then you can reject the null hypothesis Research Hypothesis Your statement 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 Want to make a good hypothesis Be clear o Make a clear stand from abstraction State the expected relationship o “This will effect that” Reflect theory and/or literature o Why do you think that? Test it! Not prove it… To the point o Distraction hurts later interpretation EX. Mr. Jones birth control Testable o Can always go back to the theory later Control Variables Strain them out Ceteris Paribus o “With other things being the same” 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 ben 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 Probability and sample o Key to fallacies and exceptions Work with hypothesis Make the call 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 Measuring ideas o Shouldn’t have to rely on great minds to solve something that we should all be able to solve o P.W. Bridgman (1927) Looking to get at a latent construct Something we are constructing but you cant see it directly o EX. You can see people smiling and laughing, but you can’t see happiness 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 EX. Serial killers, child pornographists – interview one person, begin to access network of acquaintances known by interviewees Not representative Matching: A. Choosing to ignore or pay attention to 1. Pathos _____ specific aspects 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 previously deduced 5. Inductive logic _____ 6. Aggregate _____ F. Numerous ways to do something G. Logic 7. Post Hoc Ergo Propter Hoc _____ H. An educated guess, taking a risk 8. Inaccurate observation _____ I. Attributing a behavior to something that doesn’t quite work 9. Selective Observation _____ J. From specific to general K. Something we are constructing but you 10. Overgeneralization _____ 11. Attribution errors _____ can’t see it directly L. Character 12. Necessary Conditions _____ M. “Am I measuring what I think I’m 13. Sufficient Conditions _____ measuring?” N. Anything that causes the true score and 14. Hypothesis _____ observed score to differ O. From general to specific 15. Analysis _____ 16. Theory _____ P. Emotion 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 22. SLOP (Self Selective Opinion Poll)____ possible future experiences 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 Y. Subset of the population to be studied to being randomly chosen to be in the Z. Testing the hypothesis sample
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