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CJ 280-002 Exam 1 Study Guide

by: Jennifer Gintovt

CJ 280-002 Exam 1 Study Guide CJ 280

Jennifer Gintovt
GPA 3.361

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Here is my personal study guide that I have created for our first CJ 280 exam. Here you will find all important information that could/will be covered on the exam. I have also included a section wh...
Research Methods
Matthew Dolliver
Study Guide
CJ 280-002, Criminal Justice, CJ 280, Exam 1, Study Guide, research methods
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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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