Understanding the Foundations of Psychology: History, Schools of Thought, and Career Opportunities

1. Unit 1 The History and Science of Psychology

2. Why study Psychology? • Investigate scientific explanations of age-old questions: • Is “out of sight, out of mind” really true? • When you change your answers on a test, are you more likely to pick the right answer? • How much is your personality like your parents’? • What triggers good moods? Bad moods?

3. Defining Psychology • Role of philosophy • Aristotle and “thinking about thinking” • Influence of biology • Importance of outward behavior • Psychology is defined asthe scientific study of behavior and mental processes.

4. The Birth…and Afterbirth of Psychology • Classical origins • Wilhelm Wundt • First psychology lab, 1879 at the University of Leipzig • Examined introspection, or the analysis of one’s conscious experiences

5. Schools of Thought: “Old Skool” Holla! • Structuralism • E.B. Titchener • Introspection • Break down immediate sensation, past memories, feelings • Functionalism • William James • Darwin’s influence • Conscious experience is adaptive • Stream of consciousness Break it down! No! Why is it ADAPTIVE? Titchener James

6. Schools of Thought:Old Skool • Early contributions of women • Limitations on access to education • Restrictions on awarding advanced degrees • Exclusion from psychological societies • Mary Whiton Calkins – Harvard: “No Ph.D. for you!” • Margaret Floy Washburn – 2nd Female President of APA • Rosalie Rayner • Today, women earn the majority of Ph.D.s in psychology and hold nearly half of the leadership roles in psychological societies

7. Schools of Thought:Classics I torture babies! • Psychoanalysis • Sigmund Freud • Role of the unconscious • Sex and aggression • Early childhood events • Evolved into psychodynamic school • Behaviorist School • John Watson, Ivan Pavlov, B.F. Skinner • Observable, measurable behavior Und zen zie child becomes neurotic! Sigmund Freud Behaviorist John B. Watson

8. Schools of Thought:Classics • Gestalt • Max Wertheimer, Fritz Perls • Human tendency to perceive patterns • “the whole is greater than the sum of its parts” • Useful in understanding process of perception Black spots, or a dalmatian?

9. Schools of Thought:Classics • Humanistic School • Carl Rogers, Abraham Maslow • Human potential for growth • Free will • Here and now • Need for acceptance and love • Cognitive School • Jean Piaget, Albert Ellis, Aaron Beck • Importance of thoughts and thought processes • Perception, thinking, memory, language Cognitive psychologist Jean Piaget

10. Once again… • Psychology is the scientific study of behavior and mental processes (cognition) • It is the hybrid of both observable behavior and inferred internal processes

11. Schools of Thought:New Directions • Today, contemporary schools of thought have expanded to also include the following: • Neuroscience • Evolutionary Psychology • Behavioral Genetics • Social-Cultural

12. Schools of Thought:The Biopsychosocial Approach • Regardless of the particular school of thought, contemporary psychology has come to embrace the biopsychosocial approach • Biological influences • Psychological influences • Social-Cultural influences OBEY.

13. Schools of Thought:The Biopsychosocial Approach • Each particular school of thought may emphasize one area more than another • Which area/s do you think each school would emphasize?

14. Enduring Issues in Psychology • Psychologists representing all schools of thought debate what shapes behavior • Some on-going debates include the following: • Nature vs. Nurture • Person vs. Situation • Mind vs. Body • Stability vs. Change • Diversity • The failure to resolve the debates suggests both sides are valid and shed light on behavior • An eclectic approach may be most appropriate

15. Psychology Careers:Education • The Degrees • BA – 4 year study • MA – 2-3 Years beyond BA • Ph.D./Psy.D./Ed.D. – 6-7 years beyond BA • M.D. – Psychiatrists (prescribe medication) – medical school • Increased career opportunities for advanced degrees • Admission is competitive! • Strong GPA and GRE scores • Related work or volunteer experience • Close relationships with professors • Publish if possible!

16. Psychology Careers:Fields of Study • Research vs. Applied Psychology? • The majority of psychology professionals work as therapists in some capacity • Clinical Psychologists • Counselors • Psychiatrists • Psychology’s Diverse Subfields • Cognitive • Community • Developmental • Educational • Experimental • Forensic • Industrial/Organizational • Neuropsychologists • School • Social

17. Conducting Research • Goals of Psychology • Describe • Explain • Predict • Control • Pitfalls of intuition and “common sense” explanations • Hindsight bias • Overconfidence • Remember psychology’s definition: “The scientific study of behavior and mental processes”

18. Conducting Research • The Scientific Attitude: Rely on Empiricism! • Curiosity: passion to explore and understand • Skepticism: questioning results; retesting • Humility: understanding humans’ limitations and the possibility for error • Ultimately, psychologists must be critical thinkers • Do not accept “truths” without first testing them • Look at evidence, question assumptions, filter out bias

19. The Scientific Method • Generate a question • Formulate a theory • Develop a hypothesis • Test hypothesis • Operational definitions • Clear and concise • Replication of results

20. Descriptive Research Methods • Case Study • In-depth Research • Can we generalize? • Survey • Lots of information – FAST! • Population • Random sample • Stratified Sample • Wording • Naturalistic Observation • Hawthorne Effect minimized • Observer bias • Interobserver reliability • Control?

21. Correlational Methods • What is the relationship between two factors? • Allows prediction, but NOT cause and effect! • Correlation vs. causation • A positive or negative relationship does not establish the direction of the relationship • It does not PROVE the if-then • Measuring the Strength of Relationship • Correlation Coefficient • Between -1 and 1 • Stronger relationships are closer to -1 or to 1, closeness to 0 indicates weak or no relationship • Positive correlation vs. negative correlation • Scatterplots

22. Reading Scatter Plots:Match the Correlation Coefficient with the Graph! A. .86 B. -1.0 C. 0 D. .99

23. Correlational Studies:Pitfalls • Illusory Correlations • We can be influenced to see correlations when we believe they exist • Fueled by confirmation bias, or the tendency to only remember examples that support what we already believe is true • E.g. “Old people are cheap!”

24. Experimental Method • Researcher deliberately manipulates selected variables and then measures the effects of these manipulations • Because the researcher has this level of control, the experiment can establish causation • However, the level of control can be somewhat artificial, and results may not generalize to the real world outside the lab • Also, it may be unethical to manipulate certain variables

25. The Experiment: An Example • Situation: New insomnia drug called DROW-Z’s…does it work? • Want to establish a cause and effect relationship or if-then, SO we must do an… • EXPERIMENT!

26. Personnel - Who is involved? • Experimenter • Runs and/or designs the experiment • Subjects/Participants • Those being tested • Sample - group that represents the larger group we are generalizing about (i.e. insomniacs) • Random Selection - everyone has an equal chance of being chosen! • Confederates • People who help the experimenter administer the experiment

27. Variables - What is happening? • Independent Variable • The variable being TESTED • Experimenter can manipulate it • E.g. exposure to DROW-Z’s • Dependent Variable • The RESULT • What happens as a result of exposure to the independent variable • E.g. do subjects on DROW-Z’s SLEEP better? • Confounding Variable • Throws off results • Unwanted!

28. Experimental vs. Control Groups • Experimental Group • The group exposed to manipulation of the independent variable • E.g. receives the DROW-Z’s • Control Group • Group NOT exposed to manipulation of the independent variable • E.g. does NOT receive DROW-Z’s • May instead receive a PLACEBO • Random assignment to groups • All subjects have an equal chance of being in either the control group or experimental group!

29. Operational Definitions, Etc. • Operational Definitions • What are we measuring and how? • Allows experiment to be replicated by others • E.g. what is a “better” night’s sleep? • Sample Size: the bigger the better! • What is the difference between groups? • Replication?

30. Avoiding Pitfalls • Double- and Single-blind procedures • Single - subject doesn’t know who is in control group and who is in experimental group • Double - subject and confederate don’t know who is in which group • Placebo • Reduces confounding variable • Reduces demand characteristics (subject bias)

31. Analyzing Results:Statistical Analysis • Statistics Defined • A branch of mathematics used to organize and analyze data • Necessary to use statistics to understand what results actually MEAN – if they mean anything at all… • Be skeptical of sweeping generalizations • E.g. “Males are better at math and science than females” • How was this measured?

32. Statistical Analysis: Scales of Measurement • Nominal Scale • Set of categories for classifying • E.g. types of cars in the student lot • Ordinal Scale • Scale that indicates relative position; ranks data • E.g. class rank • Interval Scale • Scale with equal distance between values, but without a true zero • E.g. temperature • Ratio Scale • Scale with equal distance between values, but WITH a true zero • E.g. Inches of rain

33. Statistical Analysis:Descriptive Statistics • Frequency Distribution • A count of the number of scores that fall within each series of intervals • Frequency histogram and Frequency polygraph

34. This is a single score that represents a set of scores Mode Most frequently occurring score Mean Average Median The midpoint – half the scores fall below, and half are above Sample Data Set: 1, 1, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 5, 5 Mode = ? Mean = ? Median = ? This is a NORMAL CURVE, where all measures of central tendency are equal! Descriptive Statistics:Measures of Central Tendency

35. Descriptive Statistics:The Skewed Distribution • Frequency distribution is asymmetrical • http://www.youtube.com/watch?v=gzSbAkZE8jw • Mean, median and mode are different values • Negative (left) – just a few very low scores • Positive (right) – just a few very high scores • **Relationship between Median and Mean

36. Descriptive Statistics:The Bimodal Distribution • As the name implies, a bimodal distribution has TWO modes

37. Descriptive Statistics:Measures of Variation • Range – the difference between the highest and lowest score in a distribution • What does it tell you? • What DOESN’T it tell you? • Standard Deviation – how much do scores vary from the mean in a distribution? (see table 1.4 in packet p. 36) • Calculate mean • Subtract each score from the mean • Square that difference • Add the sum of the squares • Divide by the number of scores in the distribution • Take square root of this • The number is equal to the value of ONE standard deviation

38. Descriptive Statistics:Measures of Variation • So what? • In a normal curve, this number reveals the percentage of scores that falls within a particular range • 68% fall within one standard deviation from the mean • 95% fall within two standard deviations from the mean • 99% fall within three standard deviations from the mean What must the standard deviation be for this distribution of IQ scores?

39. Inferential Statistics:Statistical Significance • Significant Difference • What is the difference between the experiences of the control and the experimental groups? • What is the chance that the difference happened due to chance? • .05 value generally accepted (1 in 20 due to chance) • If it IS a significant difference, how important is that difference (e.g. difference between IQ scores of first- and later-born children is significant, but due to its very small value, it is not important. • WITHIN vs. BETWEEN group variation? • If the Between Group Variation is significantly greater than the Within Group Variation, then it is likely that there is a statistically significant difference between the groups.

40. Example • Left side of classroom- Calculate SD of the following data set: • 5, 10, 15, 20, 25, 30, 35, 40, 45 • Right side of classroom- Calculate SD of following data set: • 21, 22, 23, 24, 25, 26, 27, 28, 29 • What do the differences in SD tell us about our data?

41. Real life example: • The average shoe size of a male is 9 with a standard deviation of 1.5 • This means 68% of males wear between a size 7.5 and 10.5 • 95% of males wear between a size 6 and 12 • 99% of males wear between a size 4.5 and 13.5

42. Inferential Statistics:Reliability • When can we generalize about a population based on the results from our sample? • Sample is a representative sample • The less variation in the data, the more reliable (if variability is high in a distribution, the mean becomes less meaningful) • The more examples the better! (ask 2 friends how they like the class vs. asking 25)

43. Research and Ethics • Setting Standards • APA (American Psychological Association) • PsyETA (Psychologists for the Ethical Treatment of Animals) • Human Subjects Review Board/Ethics Committee • Must Haves: • Informed Consent • Confidentiality • Justified use of deception • Protection from harm/discomfort • Debriefing • How did Milgram, Landis, Watson, and Zimbardo challenge ethical standards? • http://www.youtube.com/watch?v=Z0jYx8nwjFQ