Last lectureOutlineLecturePSY 2301 1st Edition Lecture 1Last lectureSyllabusOutlineI. IntroductionII. Types of MethodsIII. Designs for Studying DevelopmentIV. Interpreting ResultsV. Selecting Measurement StrategiesLectureI. IntroductionA. Why do research?1. To avoid speculation2. To determine whether a particular technique is effective3. To extend and modify our theoriesB. Applied Research vs. Basic Research1. Applied Research has clear, practical applicationsa. YOU CAN USE IT!!!2. Basic Research explores questions that you may be curious about, but not intended to be immediately usedII. Types of MethodsA. Correlational Method1. Examines relationships between variables2. Frequently used during initial evaluation of variables These notes represent a detailed interpretation of the professor’s lecture. GradeBuddy is best used as a supplement to your own notes, not as a substitute.3. Typesa. Positive correlationi. The variable go in the same direction(both variables increase OR decrease together)- Ex. studying and grades hopefully has a positive correlationb. Negativei. The variables go in opposite directions (as one variable increases the other variable decreases)- Ex. heroin uses and grades probably has a negative correlation4. The Correlation Coefficient ( r ) a. A number that measures the strength of a relationshipb. Range is from -1.0 to +1.0c. The relationship gets stronger the closer you get the +/-1.0 and weaker the closer you get to zeroi. Which is a stronger correlation?- -.13 or +.38- -.72 or +.59- -.91 or +.045. Casual inferences cannot be made based on correlations (correlation =/= causation)a. Could be due to a third, unmeasured, unknown (confounding) variablei. Ex. as reading ability increases, the larger the shoe size- Age is the confounding/third variableb. How do researcher figure out what causes particular outcomesB. Experimental Design1. Experimental – a researcher manipulatesonevariable and measures the effect of the manipulation on anothera. Ex. does a cheering crowd result in a better performance by the Iowa Basketball Team?2. Hypotheses – testable prediction of what will happen under certain circumstancesa. What do you predict for the example on the last slide?i. Cheering crowd will result in a better performance3. Independent variable (IV) – is manipulateda. Cheering crowd vs. silent crowd4. Dependent variable (DV) is measureda. how many baskets are made5. Cause and effect relationships6. Systematically manipulate a variable7. Random assignmenta. Control groupb. Experimental/treatment group(s)8. Hold conditions constantC. Natural/Quasi- Experiment1. Naturally occurring events2. Watch participants in their natural environment3. No manipulation of variables/environment4. No random assignment5. Cannot truly show cause and effect6. Ex.a. The effect of war on children’s anxiety levelsD. Case Study1. A detailed portrait of a single individual; can also describe a small group of people2. Strengtha. In-depth examination of person and/or treatmentb. Can provide hypotheses, bridge gap between research and practice3. Limitationsa. Weak reliability and validity b. Weak generalizabilityc. Observer biasE. Survey/Self-Report Methodologies1. Most common type of study in psychology2. Can be done by (questionnaires) vs. in person (interviews)3. Questionnairesa. Cheap and fastb. Need a good random samplec. Low response rate4. Interviewsa. Unstructured or structured5. Limitationsa. Interpretation of questionsb. Use with children6. Strengths a. Efficient (large amounts of data, short amount of time)b. Confidentiality improves accuracyIII. Designs for Studying DevelopmentA. Cross-sectionala. Data collected at one point in timei. Ex. Math abilities in children in 3rd, 4th, and 5th gradeb. Strengthsi. Efficient (time & money), no practice effects or attrition- Practice effect – take a test over and over, one gets better- Attrition – dropping outc. Limitationi. Information on individual change is not availableii. Confounding age and cohort effectsB. Longitudinal 1. Same participants studied over time2. Strengthsa. Can assess stabilityb. Can identify trendsc. Can help understand individual differences3. Limitationsa. Costly and time-consumingb. Attritioni. Dropping outc. Practice effectsi. Getting better after repetitionIV. Interpreting resultsA. Statistical vs. Practical Significance1. Statistical significance – the observed group differences are not likely due to sampling errora. Can get statistical significance, even with very small group differences, if the sample size is large enough2. Practical significance – looks at whether the difference is large enough to be of value in a practical sensea. Is it an effect worth being concerned about – does it have any noticeable or worthwhile effects?V. Selecting Measurement StrategiesA. Reliability1. Consistency of the measuring tool2. Types of Reliabilitya. Interrateri. Degree of agreement between independent ratersb. Test-retesti. Re-administer test after time intervalii. Consistency of scores over timec. Internal consistencyi. Relatedness of itemsii. Coefficient alpha (or Cronbach’s alpha)B. Validity 1. Assessment measures what it is supposed to measure2. Content Validitya. Relevancei. Content is relevant to domainb. Comprehensivenessi. Covers all important aspects of domainc. Representativenessi. Items sample a domain