Exam 1 Study Guide
Exam 1 Study Guide Psyc 200
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This 10 page Study Guide was uploaded by Hannah on Sunday October 9, 2016. The Study Guide belongs to Psyc 200 at University of Wisconsin - Stevens Point taught by Dr. Mark Ferguson in Fall 2016. Since its upload, it has received 42 views. For similar materials see Research Methods in Psychology in Psychology at University of Wisconsin - Stevens Point.
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Date Created: 10/09/16
Research Methods Psyc 200 Section 6 Introduction ● Sources of knowledge and how different institutions prioritize the sources. ○ Sources: ■ Authority: expertise or status in a particular domain ■ Intuition: implicit understanding outside of specialized training ■ Logic: formalized rules of correct and incorrect reasoning ■ Observation: using measurements to understand a phenomenon ○ Priority Religion Government Philosophy Science 1 Authority Authority Logic Observation 2 Intuition Intuition Observation Logic 3 Logic Logic Intuition Intuition 4 Observation Observation Authority Authority ■ Notice that Religion and Government are the same and that the only thing different about Philosophy and Science is that observation and logic are switched. This should help with remembering. ● Reasons that misunderstandings between religion and government are unnecessary ○ Religion and Science address different questions ■ Non-observables vs observables ■ Morals/ethics vs consequences ○ Religion and Science often point to same conclusions ■ Ex: Buddhism and meditation. Buddhism supports the idea that meditation focuses the mind and there is research that proves this. ● The core beliefs of science and the five phases of research ○ Core Beliefs: ■ Determinism: a belief that nature is orderly which means events have a systematic cause ■ Verificationism: belief that events should be testable or falsifiable with research tools ■ Empiricism: belief that nature can be understood through the collection of observations or data ■ Parsimony: belief that simpler explanations are preferable to complex ones ○ Five Phases: ■ Idea Phase: involves generating ideas and developing them into testable predictions(research boils down to questions that people want to answer) ■ Design Phase: involves organizing studies to test these predictions(different types of research for different types of questions) ■ Measurement Phase: involves collecting observations to evaluate your predictions(generally involves assigning numbers to properties or events) ■ Analysis Phase: involves looking for patterns in observations to evaluate your predictions(generally involves computer generated statistical analyses) ■ Communication phase: involves sharing your finds with others(presentations and publications with scientists, policy makers, citizens, etc) ● The five phases are not always linear. During research scientists move back and forth between the phases until the study is complete. ● Types of research questions and designs(including form and causal information) ○ Four Types of Designs ■ Descriptive: examines variation in one or more factors (ex: case studies) ■ Correlational: examines relations between two or more factors(ex: survey research) ■ Quasi-experimental: examines causal relations between two or more factors in the real world (ex: applied research) ■ Experimental: examines causal relations between two or more factors in a controlled setting (ex: lab experiments) ■ Type Form VariabilityCovariation Direction Control -ality Description Does Y Yes No No No Vary? Prediction Does X Yes Yes No No vary with Y? Application What Yes Yes Yes No causes variatio n in Y? Explanatio Does X Yes Yes Yes Yes n cause variatio n in Y? Hypotheses ● Induction vs Deduction and inductive vs deductive sources of ideas ○ Induction: reasoning from specific instances to general principle ■ Data driven research ○ Deduction: reasoning from general principles to specific instances ■ Theory driven research ○ Inductive sources(bottom-up): ■ Personal Intuition/experience ■ causal/expert observations ■ happenstance/serendipity(happy accidents) ■ paradoxical/unusual events ○ Deductive Sources: ■ Functional/adaptive reasoning(self efficacy) ■ Reasoning by analogy/metaphor ■ Classic or present theories/research ■ Conflicting findings/exceptions ● Questions to ask about potential research ideas ○ What makes this idea interesting or important? What is its contribution? ○ Have any supportive or unsupportive perspectives been overlooked? ○ How could the idea be improved? (uncover hidden assumptions) ○ If it works, what would this knowledge teach us about psychology or how could it be used to improve people’s lives? ● Constructs vs Operation and Independent Variables vs Dependent Variables ○ Construct: abstract, theoretical concepts in the world ■ “Conceptual definitions” (dictionary definition) ■ Ex: emotion, memory, thought ○ Operation: manipulations or measure meant to represent constructs in a study ■ “Operational definitions” ● Ex: We determine how hungry someone is by how many fries they eat ○ Independent Variables: refers to a variable manipulated in a study(“cause”) ■ Construct affected by operation ○ Dependent Variables: refers to a variable measured in a study(“effect”) ■ Construct assessed by operation ● Theories vs Hypotheses; theory vs hypothesis stage of idea development ○ Theories: one of more general statements about constructs and the relationship between them ■ Ex: hunger makes people eat ○ Hypothesis: a specific prediction about operations and the relationship between them ○ Theory Stage of Idea Development: articulate questions, identify constructs and predict the relationship between constructs ■ What happens in the world ○ Hypothesis Stage of Idea Development: choose design, identify operations and predict the relationship between operations ■ What happens in the study ● Primary vs Secondary Sources ○ Primary Sources: reports of original research, generally found in journal articles and edited books ○ Secondary sources: summaries and commentaries on original research, generally found in review journals and encyclopedias ● Steps for finding research literature; bottom up vs top down searches ○ Bottom up ■ Start with a broad idea and move through research to help you find what you are looking for. You use the expanding words from the chart below and slowly narrow it down once you know what you are looking for. Usually you find observations, find a pattern and then make a theory. ○ Top Down ■ Usually done by finding an existing theory, making a hypothesis, testing it and then confirming or rejecting the theory. When you start your search you use narrowing words from the chart below and find a specific idea and move back down to the observations. ● Ways to expand or narrow your search; literature chains; search records ○ Expand or narrow ■ Expand Narrow Remove words Add words Boolean “or” Boolean “and” or “not” Wildcards (ex: congit*) Limiter boxes (on left) Databases in other relevant fieldsDrop-down menu (on right) Literature(reference) chains Quotation marks around phrases Google Scholar Thesaurus Function Talk to professor or librarian Advanced Search ■ Literature chains: Finding an article and looking through/reading the references and related articles ■ Search Records: it is important to keep a search record so you know what articles you have already seen so you do not waste time looking through the same articles over and over again. This also helps you keep track of your various sources. ○ How to read and understand sources materials; characteristics of good references ■ How to read/understand: ● Set aside time to read resources in a distraction free place ● Treat reading session like treasure hunts---read in a strategic instead of linear way only looking for what you need and nothing more ■ Characteristics of good references: ● Check methods and results if either are weird or seem messed up trash the paper; it will not be good. Things to look for is if the cause/effect is backwards(ex: results say A cause B but really B cause A) ○ How and why to take notes on source materials ■ How: ● Take notes in your own words ● Keep notes brief ● Paraphrase what you need ● Avoid direct quotations otherwise you might accidentally plagiarize ■ Why: ● Taking notes is important because this allows you to have easy access to the main(important) parts of the article in a quick way instead of rereading the article. This also helps you rewrite things in your own words so when you write papers you lessen the chance of plagiarism. ○ Construct Validity; convergent vs discriminant validity ■ Construct Validity: refers to the degree of correspondence between construct and operation in a study. (degree of overlap) ■ Approaches to construct validity ● Convergent validity: similar operation do correspond ● Discriminant validity: different operations do not correspond ○ Responsibility to protect participants from harm ■ Laws and professional groups now hold researchers responsible for protecting participants from physical/mental harm(ex: stress, self doubts, anxieties) ■ When harms could be intense or long-lasting we need to find other ways of testing our predictions. ■ In class, we talked about the Tuskegee 1932 study where the researchers knowingly infected 399 African American people with syphilis to see how the disease progressed without telling the participants. ○ Institutional Review Boards; expedited vs full board reviews; cost-benefit analysis ■ Institutional Review Boards: a panel of reviewers that evaluate ethical concerns in studies and offer suggestions for improvement ● Panel is made up of professors, academic staff, and community members ■ Expedited vs Full Board Reviews ● Expedited(one or two people) review that study if it doesn’t cross the minimal harm line(doesn’t cause more harm than everyday life) ● Full Board reviews for extensive damage, challenging topics, etc ■ Cost-benefit analysis ● Is the harm worth the information we will learn from the study? Descriptive and Correlational ● Descriptive vs Correlational Designs ○ Descriptive: organizing studies to characterize one or more constructs ■ Focus on describing variation ○ Correlational: organizing studies to identify relations between two or more constructs ■ Focus on predicting variation ■ Must have at least two constructs ● Why choose descriptive or correlational designs over experimental designs? ○ These two designs may have greater external validity over experimental ● Linear vs curvilinear relationships and interpreting correlational coefficients ○ ○ Linear means that there is a positive or negative correlation. So, as X increases so does Y or as X decreases so does Y. ○ For curvilinear Professor Ferguson gave the example of exercise. In the beginning your happiness(x) is low and so is your amount of exercise(y) but as your amount of exercise increases so does your happiness. Then, you might be achy so your amount of exercise decreases again and your happiness also decreases again and this causes the curve. You can have more than one curve in a study as you remove and introduce variables. ○ Correlational Coefficients: this is the number to match the correlation. If it is a positive number than the correlation is positive and then the opposite is true; if it is a negative number than the correlation is negative. ● Three explanations for correlations(preferred, reverse causation, spurious causation) ○ Preferred: ○ Reverse Causation: rather than x causes Y; Y actually causes X ■ Directionality problem, without direction you don’t know which came first ○ Spurious Causation: rather than X causes Y; Z actually causes X and Y ■ Third variable problem (confounds) ● Ex: amount of people going to church increases with the amount of alcohol consumption in 40 largest cities. They are not correlated; large city means more people which causes an increase in numbers. ● Four methods of data collection in descriptive and correlational studies(including their strength and weaknesses) ○ Archival Methods: a systematic examination of one or more variables by using existing documents ■ Ex: census data, court records, personal letters ■ Strength: helpful for studying historical change, generating novel hypotheses, and data already collected ■ Weaknesses: records are not always available or accurate ○ Case Methods: systematic examination of one or more variables related to particular individuals, groups or events ■ Ex: Phineas Gage and neuroscience, Ifaluk people and emotions ■ Strength: informative about rare issues and suggest testable hypotheses ■ Weaknesses: rare sample and lack of comparison sample ○ Observational Methods: systematic examination of one or more variables as they occur in the natural environment ■ Researchers need to think whether to be participants or observers(acknowledged or unacknowledged) ■ Researchers need to design a coding(measure) system to determine what they are measuring. (assigning numbers to things) ■ Strengths: done anywhere, inexpensive, suggest testable hypotheses ■ Weaknesses: Reactivity, ethical questions, reliability of coding ○ Survey Methods: systematic examination of one or more variables using a series of self report measures ■ Surveys given via interviews or questionnaires ■ Ex: census, political poll, demographic or epidemiological studies, marketing research ■ Strengths: easy to conduct, efficiently collect a lot of information ■ Weaknesses: sampling matters, poor response rates, reactivity Quasi-experimental ● Quasi-experimental designs and how they differ from experimental ○ Quasi-experimental designs take place in the real world rather than the lab ○ They are not quite experiments because they lack one or more of these three traits ■ Random Assignment ■ Independent Variable manipulation ■ Control or comparison groups ● Threats to internal validity and how it relates to causal inferences/confounds ○ Internal Validity is how accurate the conclusions are about the effects of the independent variable ○ Quasi-experiments have a lot of issues with confounds(other independent variables that may be responsible for the response) because in the real world researchers lack control. Causal inferences is where other possibilities have been ruled out and the correct independent variable has been chosen as the cause. ● Why choose Quasi-Experiments rather than experiments? ○ True experiments are not always possible or desirable ■ Ex: you may want to study the effectiveness of seat belt laws on decreasing the amount of fatalities. You can’t assign people to not use their seat belt and suffer possible fatal injuries. ○ There may be no ideal research design for the question ○ A desire to maximize both internal and external validity ● Nonequivalent Groups Design and the two discussed in class ○ Involves two or more groups with at least one exposed to a treatment that might not be manipulated ○ Random assignment might not be possible so groups can differ from each other at the start of the study ○ Researchers might need to identify reasonable control or comparison groups ■ Nonequivalent groups posttest-only design ● X O1 -------------- O 1 ● X=treatment O=outcome ● Professor Ferguson used the example of Three Mile Island(TMI) ■ Nonequivalent Groups Pretest-posttest design ● O1 X O2 ---------------------------------- O1 O2 ● Ex: Does a depression medication work? We test the depression levels first and then we give one group a treatment and after that test the scores again ○ Time Series Designs and the two discussed in class and how it differs from within subjects designs ■ A measure is administered to the same group at multiple points in time like within-subjects designs ● Time series are different that within-subjects because time series have a broader time frame and lack control over subjects experiences between administrations of the outcome measure ■ Interrupted Time-Series Design ● O1 O2 O3 X O4 O5 O6 ■ Interrupted time series with nonequivalent control group design ● O1 O2 O3 X O4 O5 O6 O1 O2 O3 O4 O5 O6 ○ Patching(the process and its relation to confounds) ■ Patching is the process of including additional treatments, comparison groups, or outcomes to reduce the plausibility of relevant confounds ● Process is inelegant but helps reduce the likelihood that different confounds are responsible for the results researchers find ○ Applied Research and program evaluation(including access and characteristics) ■ Applied research focuses on developing solutions to societal problems, rather than creating knowledge ■ This gets researchers out of the lab and into the field--community and organizational settings, issues that are important to others, and often with a more focused timeline(they need to meet deadlines for the agency they work for) ■ Gaining access to field settings ● Explain the practical or clinical importance of your project ● Be sensitive to the feelings of the organization and its clientele ● Remain open to collaboration with the organization on your project ● Discuss how the project will help you(explain why you are there, what you want to learn so that they don’t think you are trying to hurt their company) ● Talk about your clear and minimally-disruptive project plan ■ Program evaluation ● The application of research methods to the assessment of social programs and interventions ● Unique characteristics ○ More explicit, political context ○ Separation of design and implementation roles ○ Confusion about outcome versus process related priorities ○ Five functions of program assessment(including the goal of program diffusion) ■ Needs assessment: determines whether there is a need for a social program and the steps required to meet that need ● stakeholders(people who are connected to the issue) help determine what is needed ■ Program theory and design assessment: evaluates the raionale for why a program has been, or will be, designed in a particular way ● Feeding all the hungry people(where will this food come from, who is paying for it, what happens when it runs out) or just a small amount of people(is it worth it and does it make a difference) ■ Precess evaluation: determines whether a program is being implemented as intended ■ Outcome evaluation: assesses a program’s effectiveness ■ Efficiency assessment: weighs the program’s benefits and effectiveness in relation to costs, to determine whether it is an efficient method for addressing the program ■ Program diffusion: using the same program in a different city. If a program is efficient and effective then it might be implemented in other settings or with other groups
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