Methods and Research

1. Methods and Research

2. Hindsight bias • “Knew it all along phenomenon” • Paul Slovic & Baruch Fischoff • The tendency to believe, after learning the outcome, that one would have foreseen it.

3. Overconfidence • Thinking that we know more than we do • More confident than correct • WREAT=WATER • ETRYN=ENTRY

4. Point to Remember… • Hindsight bias and overconfidence often lead us to overestimate our intuition. Through scientific inquiry we can sift through what is reality and what is illusion.

5. Scientific Attitude • Requires one to ask two questions: • 1.)What do you mean? • 2.) How do you know? • Requires humility • May have to reject your own ideas • Being skeptical but not cynical, open but not gullible • Use critical thinking • Examines assumptions, discerns hidden values, evaluates evidence, and assess conclusions

6. Case Study • One individual (or small group) studied over an extended period of time in depth • Sometimes over generalizes • Must answer questions with other methods

7. Survey • Looking at many cases in less depth • Wording effects can give you different results • “aide to the needy” vs. “welfare” • “free and reduced lunch” vs. “economically disadvantaged” • Questionnaire or interview • Random sampling • A sample that fairly represents a population because each member has an equal chance to be included.

8. Naturalistic Observation • Observing and recording behavior in naturally occurring situations without trying to manipulate and control the situation. • Behaviors may be overlooked or if the one being observed notices that they are being watched, behaviors may change

9. Point to Remember.. • A case study, survey, or naturalistic observation does not explain behaviors, it just describes it!

10. Correlation • One trait or behavior accompanies another • One predicts the other • Scatterplots • Positive • Negative (one score goes up and the other goes down) • No Relationship

11. Illusory Correlations • A perceived nonexistent correlation between two things • Help explain superstitious beliefs • Being outside in the cold and wet causes one to get sick (not true)

12. Causation • One variable may or may not lead to an outcome • Low self-esteem could cause Depression • Depression could cause low self-esteem

13. Point to Remember… • Correlation indicates the possibility of a cause and effect relationship but it does not prove causation.

14. Double-Blind Procedure • Both the researchers and participants do not know if they have received the actual treatment or the placebo • Reduce bias behaviors

15. Placebo Effect • Placebo: Latin meaning “I shall please” • Just believing you are receiving treatment can cause your mind to boost your spirits, relax your body, or relieve your symptoms • Pill with no medical ingredients

16. Experimental Condition vs. Control Condition • Experimental: • Exposed to the treatment • Control: • Without the treatment • Used as the comparison

17. Independent vs. Dependent Variables • Independent(cause): • The factor that is manipulated • Variable whose effect is being studied • Breast milk(experimental)/ Formula (control) • Dependent(effect): • Outcome factor • The one that is being changed due to the manipulations of the independent variable • Intelligence score

18. Describing Data • Mean • Average • Preferred measure of tendency but very sensitive to extremes • Median • Middle • Less sensitive but doesn’t take into account all the information in the data points • Mode • Most frequently occurring • Least common, but quick if data is not in order • Range • Difference between high and low • Standard Deviation • Determines if scores are packed together or dispersed

19. Statistical Significance • When sample averages are reliable and the difference between them is relatively large • The difference we observe is probably not due to chance variation between the samples

20. Experiment Design • Hypothesis: Prediction of how two or more factors are related • “If (IV)…then (DV)…” statement • Cofounding variables: Differences between the experimental and control group other than those resulting from the independent variable • Limit confidence in research conclusions • Operational definition: A description of the specific procedure used to determine the presence of a variable.

21. Eliminating Confounding Variables • Experimental bias/experimenter expectancy effect: When a researcher’s expectations/preferences about the outcome of a study influence the results gathered • Simple smile, nodding, treating the experimental group differently • Demand characteristics: Clues participants discover about the purpose of the study • Single-blind procedure used

22. Within-subjects Design • Each participant is used as his/her own control • Before treatment and after treatment is compared • Counterbalancing is used to reduce an effect if two treatments are being tested • ½ of the group is assigned one treatment first and vise a versa

23. Quasi-Experimental Research • Participants are not randomly assigned • males vs. females • young vs. old • Caucasians vs. Latinos • Do not establish cause and effect relationships due to cofounding variables

24. Test Method Reliability Validity • Consistency • Repeatability • Same scores/results each time • The extent to which an instrument measures/predicts what it is supposed to • Example: solving algebra problems would not measure your understanding of Psychology

25. Statistics:A field that involves the analysis of numerical data about representative samples of populations • Nominal Scale: Numbers used to simply name something and can be used to count the number of cases • Girls=1, boys=2…no meaning • Ordinal Scale: Used for ranking and numbers cannot be averaged • Highest score= 1, second highest=2. etc. • Interval Scale: Meaningful differences between each of the numbers • Difference between 32 and 42 is 10 • Ratio Scale: Meaningful ratio can be made with two numbers • * Ratio scale have a absolute zero point (weight, volume, and distance, zero has meaning)

26. Descriptive Statistics:Numbers that summarize a set of research data obtained from a sample • Describe sets of interval or ratio data • Frequency Distribution: Orderly arrangement of scores indicating the frequency of each score/group of scores. • Histogram (bar graph) • Frequency Polygon: Line graph that replaces the bars with single points and then the points are connected with lines (Bell curve)

27. Measures of Central Tendency • Describe the average or most typical scores for a set of data (mean, median, mode) • Bimodal: two scores appear most frequently • Multimodal: 3+ scores appear more than once • Normal Distribution: Mirror images, symmetrical, bell curve • Skewed: Data is squeezed into one end • Negatively skewed: to the left • Positively skewed: to the right

28. Measures of Variability • Describes the spread/dispersion of scores (range, variance, standard deviation) • Variance computation: • Difference between each value and the mean, squaring the difference between each value and the mean (eliminates negatives), summing the squared differences and then taking the average of the sum of squared differences • Standard Deviation Computation: • The square root of the variance • Must fall between 0 and half the value of the range • *Wont be required to find actual calculations of variance or SD 

29. Inferential Statistics • Used to interpret data and draw conclusions • Allows researches to either generalize the chosen sample to the entire population or not as long as the sample represents the population. • Statistical Significance (p) is used • Results are statistically significant when: • Large difference between means of the two frequency distributions • SD are small • Samples are large • Statistically Significant if: • 1 in 20 probability p < .05 • less than 1 in 100 probability p < .01 • The lower the p value the less likely the results were due to chance