Lecture 2 - Research Methods
Lecture 2 - Research Methods PSYC 2012
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This 5 page Class Notes was uploaded by Leslie Ogu on Thursday February 4, 2016. The Class Notes belongs to PSYC 2012 at George Washington University taught by Stock, M in Fall 2015. Since its upload, it has received 22 views. For similar materials see Social Psychology in Psychlogy at George Washington University.
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Date Created: 02/04/16
Leslie Ogu PSYC 2012 01/13/2016 Research Methods Correlational Research ★ Identifying the relationship between variables ○ Ex: What’s the relationship between smoking and lung cancer? ★ Variables are measured as they naturally occur ○ The researcher doesn’t interfere with them ○ Ex: Survey Methods Survey Methods ★ Usually given to groups of people, rather than individuals ○ Ex(s): seniors in high school, individuals who practice a certain religion ★ Strength(s): ○ Can collect information on many variables ○ Can have numerous participants ★ Weakness(es): ○ Question effects ○ The samples may not represent the population as whole ○ Responses may not be realistic due to things like social desirability (answering in ways that seem favorable to others) Question Effects ★ The way a question is asked or worded can influence a person’s response Representative Samples ★ Is your sample representative of the larger population? ○ all the cases in a group, from which samples can be drawn for a study ★ One solution Random Sampling/Selection so everyone in a particular population has an equal chance of being chosen for the sample ★ Problem difficulty ○ Usually rely on convenience samples ○ Ex: The College Sophomore Problem where most people a study is done on are college sophomores The Importance of Random Sampling ★ Ensures the sample reflects the population of interest Correlation Coefficient (r) ★ A statistical measure that shows the extent to which two factors vary together and thus how well either factor predicts the other ★ The sign ( or +) indicates the direction of the relationship: ○ Positive = both variables move in the SAME DIRECTION (as x ↑, y ↓) ■ r = .01 to 1 ○ Negative = both variables move in the OPPOSITE DIRECTION (as x ↓, y ↑) ■ r = .01 to 1 ○ r ranges from 1.00 (perfect negative relationship) to +1.00 (perfect positive relationship) Correlation Methods ★ Other explanations for correlation include some third variable that has some outside influence or effect, and reverse direction Experiments ★ Random Assignment ★ Manipulation of the Independent Variable ○ The manipulated variable ○ Has 2 levels minimum ○ Its effects are the ones being studied ★ Measure of the Outcome (Dependent Variable) ○ The measurable variable ○ Hypothesized to change when the IV is changed, whose outcome the experimenter wants to study ★ Control over the Research Environment ★ Potential to Assess Causation Experimental Research ★ Used to determine cause and effect relationships ★ Two key aspects of it are that the variables are manipulated by the experimenter, and extraneous variables are controlled random assignment ★ Establishing causality requires control over the environment ○ Control for factors that affect the DV, that aren’t the DV ○ Prevent other condition/factors from affecting the outcomes of the experiment (e.g., the number of hours slept before an experiment) ★ Everything except the IV is the same for different conditions Operationalization ★ To be able to measure the variables, we have to have operational definitions: specific procedures for manipulating or measuring a conceptual variable ○ E.g., Mood: ■ Manipulating things like music ■ Measuring things like mood rating scales ○ How will the variables be measured in “real life” terms ○ How you operationalize the variables will tell us if the study is valid and reliable Random Assignment ★ Participants have equal chance of being in any experimental condition ○ this will ensure that there are differences in participants’ personalities or backgrounds are distributed evenly across conditions ★ Why? Confounding Variables ○ Preexisting variables that could possibly affect the results of the experiment (Ex: intelligence, hunger, bias) ○ Minimizes differences between the people assigned to the different groups Experimenter Control ★ “Blind” Studies ○ Singleblind ■ participant doesn’t know which group they are in ○ Doubleblind ■ neither the participant nor experimenter knows which group the person is in (until after the DV is measured) ★ Experimenter Expectancy Effects ○ effects that are produced when an experimenter’s expectations about the results of an experiment affect his or her behavior toward a participant and will thereby influence the participant’s responses QuasiExperiments ★ Two or more groups are exposed to an IV and differences in a DV are examined ★ No or partial random assignment (usually selfselection) ★ Can’t make causal claims Statistical Significance ★ When we find that two or more groups differ from each other on our DV, we must figure out whether or not the difference is meaningful, or to have occurred by chance ★ An effect is “significantly signific” is an effect that would occur by chance < 5% of the time Design ★ BetweenSubjects Design ○ each person participates in only one group/treatment ○ results from each group are compared to each other to study the differences and effects of the IV ★ WithinSubjects Design ○ each person participates in more than one group/treatment Strengths & Limitations of Experimental Method ★ Strength(s): ○ Researcher has control ○ Can study causal relationships ★ Weakness(es): ○ Some variables can’t be manipulated ○ It is unethical to manipulate some variables ○ Controlled procedures may not be realistic Evaluating Experimental Research: Validity ★ Internal Validity: the extent to which we can draw conclusions about cause and effect ○ Good Design Random Assignment ○ Control for confounds ★ External Validity: the extent to which findings generalize to other people, settings, IVs, and DVs ○ Representative Sample ○ Replication ○ Field Experiments Random Sampling v. Random Assignment ★ Random Sampling ○ used when choosing people to be in the study ○ purpose: to be able to generalize to the population ○ importance: external validity ★ Random Assignment ○ used when assigning people to conditions ○ purpose: to avoid confounds by averaging out extraneous variables between conditions ○ importance: interval validity Some Guidelines for Evaluating Media Reports ★ Making causal statements w/ correlational data ★ Unrepresentative or small samples sizes ★ Nonrandom assignment or selection ★ Missing Comparison Groups ★ Lack of study details ★ Broad Implications ★ Poor Questionnaire Design
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