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General Psychology Notes for all of Unit 1

by: Carolina Notetaker

General Psychology Notes for all of Unit 1 PSY 2012

Marketplace > Florida State University > Psychlogy > PSY 2012 > General Psychology Notes for all of Unit 1
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These notes cover everything in Unit 1 including chapters 1, 2 and 8. It can serve as a tool to complete any study guides you might have made on your own (or as a study guide itself).
General Psychology
Erica Wells
Class Notes
General Psychology, FSU psych, Erica Wells Psychology
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This 8 page Class Notes was uploaded by Carolina Notetaker on Sunday January 10, 2016. The Class Notes belongs to PSY 2012 at Florida State University taught by Erica Wells in Spring 2016. Since its upload, it has received 325 views. For similar materials see General Psychology in Psychlogy at Florida State University.


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Date Created: 01/10/16
Psychology Notes Chapter 1 What is psychology?   The study of the mind, brain and behavior (Most common  definition) Why is psychology more than just common sense?   Maybe what we think we know isn’t necessarily true. Example:  Some people might think that opposites attract, while others  might think that similars attract (“Common sense”)   Research gives us more information to find out which one of  these statements is true. (Similars attract)   There is always going to be an exception. Example: Even  though research shows that similars attract, there will always be that one couple that are nothing like each other/ opposites  (beauty & the beast, etc.)  Naive Realism: Belief that we see the world precisely as it is/ what  we see is what is true. In reality, we don’t always see the world as it  truly is.   common sense can lead us to false beliefs/ astray  (Superstitions)  But other times, common sense can actually be right: o Ex: Gut instincts about fear / something bad occurring  tend to be right most of the time o Can also generate a hypothesis which can then be tested  (ex: Frat guys tend to have higher drinking rates than non  frat guys)  Psychology as a science:  Science isn’t formulas like e=mc^2  Science is the process to get formulas / an approach to  evidence How do we know things like “Is cracking your knuckles bad for your  joints?” & “Do frat guys have higher drinking rates than non­ frat  guys?” ­> Scientific Method Pseudoscience: Claims that can be tested but have no evidence to  support them. Set of claims that seem scientific, but aren’t. (Testable  beliefs that are not supported by science).  Examples: Astrology, The Lunar Effect & Conspiracy theories. If these are all fake/ have no evidence to support them,  what’s the  harm?  A lot of harm can result from pseudoscience. Examples:   Conversion Therapy: treatment that aims to change sexual  orientation from homosexual to heterosexual.  Holocaust Denial: Belief that the Holocaust didn’t happen or  was greatly exaggerated   Scientific Racism: Belief that certain racial groups are inferior/  superior to others  Some warning signs of Pseudoscience:  1. Overreliance on anecdotes 2. Exaggerated claims 3. Absence of connection to other research  4. Lack of peer review 5. Failure to self correct when contrary evidence is presented 6. Uses fancy scientific language that doesn’t make sense  7. Talks about “proof” instead of “evidence”  Pseudoscience can be dangerous for 3 main reasons: 1. Opportunity cost: what you miss out on when you choose to do  something. Example: wasting time and money on something  like “crystal therapy”  2. Direct harm: Ex: Rebirthing therapy: “rebirthing” yourself to get  over “attachment issues”. Baby once died during this therapy  due to suffocation from trying to reenact birth. 3. Inability to think scientifically as citizens: We need to think  critically/ scientifically to move society forward. Example: during hitler’s reign, citizens actually started supporting / believing him  probably due to them not being able to think critically.  Scientific Skepticism: Doesn’t mean we should be close minded,  just means we should evaluate claims with an open mind but insist on persuasive evidence before accepting them. (Be willing to change  your mind). 6 Critical Thinking Principles:  1. Ruling out rival hypotheses 2. Correlation vs. Causation: Correlation DOES NOT MEAN  Causation. Can we be sure that A causes B? example: ice  cream sales went up, and so did murder rates, therefore an  increase in ice cream sales causes an increase in murder rates. But really, HEAT makes people more aggressive & also makes  people want to buy more ice cream. (just correlated) 3. Falsifiability: A theory that accounts for every possible outcome  explains nothing. Falsifiable doesn’t mean it’s false. Can the  claim be disproven? (can’t be too vague)  4. Replicability: Can the results be duplicated? 5. Extraordinary Claims: Require extraordinary evidence. Is the  evidence as convincing as the claim? 6. Occam’s razor: Keep it simple. Does a simpler explanation fit  the data just as well?  Bottom line: INSIST ON EVIDENCE  Scientific Theory: Explanation for a large number of findings in the  natural world.  Example: “High activity levels in kids with ADHD actually increases  their brain activity” Hypothesis: Specific, testable prediction derived from a scientific  theory. Example: “A kid will do better on a math test if he / she is  sitting on a bouncy chair vs. a non bouncy chair.”  Confirmation Theory: Tendency to seek out evidence that supports  our hypothesis and neglect evidence that contradicts our hypothesis.  Example: Belief that every woman is a bad driver. When you see a  bad driver that happens to be a woman, you point it out. But when  you see a bad male driver, you just disregard it.   To combat this, scientists need to design studies that disprove  their theories and look for evidence that falsifies those theories.  Belief Perseverance: Tendency to stick to our initial beliefs even  when evidence contradicts them. Example: Wearing lucky socks to  do well in a game. When you don’t do well (evidence that your theory  is wrong) you still continue to wear them.  Psychology has many levels of analysis: All the way from physical  (bottom of list) to social (top of the list). Can’t just examine one level.  Must examine ALL.  Heuristics: Mental shortcuts or rules of thumb that we use daily. They  reduce the cognitive energy required to solve problems BUT we  oversimplify reality.  Common heuristics: 1. Availability heuristic: estimating the likelihood of an  occurrence based on the ease with which it comes to our  minds. (shark attacks, airplane crashes, etc. Might assume  they are a bigger threat to us than they really are) 2. Representative Heuristic: “like goes with like”. Ignore how  common behaviors actually are and commit the base rate  fallacy. ( neglect to consider base rates). We might assume  a lot of people are psychopaths but statistics show less than  1% of the population is a psychopath.  Heuristics can serve us well (can help us make fairly accurate  judgments quickly)  Cognitive Biases: systematic errors in thinking that can lead to  confidence in false conclusions. Overconfidence Bias: Tendency to overestimate our ability to make  correct predictions.  Hindsight Bias: “I knew it all along” Why do we need research? To avoid speculation (example:  lobotomies) Scientific Method: toolbox of skills designed to counteract our  tendency to fool ourselves. Allows us to test specific hypotheses  derived from broader theories of how things work.  1. Naturalistic Observation: Observing/ describing behavior in  real world settings. (Example: People watching) Advantages: High external validity/ generalizability. Disadvantages: low  internal validity/ cause and effected inferences.  2. Case Study: Studying one person for an extended period of  time (depth instead of breadth) Common for rare types of  brain illnesses. Advantages: descriptions of phenomena,  providing disconfirming info of universally known info, and  ability to generate a hypothesis. Disadvantage: Develop  general principles, lead to cause and effect conclusions Evaluating Measures: to trust results, measures must have a. Reliability: Consistency of measurement b. Validity: Measure assesses what it claims to measure c. Can’t be unreliable AND valid at the same time.  Self­reporting measures and surveys­ Advantages: Easy to  administer & can provide subtle information. Disadvantages:  Respondents may not have the insight necessary and may not be  honest Validity vs. Reliability examples: ­ Channel, a second grader, got an A on each spelling test  throughout the year, which was counted as her reading score  for second grade. INVALID, RELIABLE.  ­ Jimmy knows he weighs 180 pounds. His scale says 300  pounds every time he steps on it. RELIABLE, INVALID. 3. Correlational Designs: Examine how 2 variables are related.  Correlations vary from ­1 to +1 and can be: ­ Positive: as one increases, so does the other. ­ Negative: as one increases, the other decreases ­ Zero: No relationship between the 2  Examples: Height and Weight: Positive, Studying and Grades:  Positive, Drinking and Social Awkwardness: Negative , Eye  color and IQ: Zero   Correlational methods cannot determine directionality or  causality. There could be a third variable involved.  How can we determine causation? An experimental design. The  only way to determine if one thing is causally related to another is via  an experimental design. This is because in an experiment, you  purposefully manipulate variables, rather than just measure already  existing difference. For example, smoking cigarettes and lung cancer  are correlational, not causational because we haven’t /can’t conduct  an experiment.  4. Experimental Designs: what makes a study an experiment? 1.  Random Assignment 2. Manipulation of Independent variable Pitfalls of experimental design:  ­ Placebo Effect: Improvement resulting from the mere  expectation of improvement. Subjects must be “blind”. Placebos show many of the same characteristics as real drugs. ­ Nocebo Effect: Placebo effect’s evil twin. Harm resulting from  the mere expectation of harm. ­ Demand characteristics: cues that participants pick up that  allow them to generate guesses regarding the researcher’s  hypothesis. (disguising the purpose of the study can help to  decrease these) Modern Ethical Guidelines for Human Research ­ informed consent ­ protection from harm and discomfort ­ justification of deception ­ debriefing Descriptive Statistics: Numerical characteristics of the nature of the  data set. Central Tendency: Measures of the central scores. Mean (average of  all scores), Median( Middle score), Mode( Most frequent score) Distribution Curves: A normal, bell shaped distribution  Variability: Measure of how loosely/ tightly bunched scores are Measures of Variability: Range­ Difference between the highest and  lowest scores. Standard Deviation: Takes into account how far each  data point is from the mean.  CHAPTER 8 Features of language: Highly practiced and automatic process. Four  levels of analysis that must coordinate with one another:  1. Phonemes (sounds) 2. Morphemes (meanings) 3. Syntax (Sentence structure) 4. Extra­linguistic information ( tone, body language, etc)  Language Development Stages: 1. Babbling Stage: spontaneously utter random sounds. Not  imitation(3­4 months)  2. One Word Stage: from age 1­2  3. Two Word Stage: Mostly age 2. AKA telegraphic speech   Current studies about critical period for language learning are  inconclusive.   There is no strict critical period for language development in  humans, but a sensitive period  Linguistic Determinism: View that all thought is represented and that,  as a result, our language defines our thinking (too severe of a view) Linguistic Relativity: View that characteristics of language shape our  thought processes. (More supported view) Thinking and Reasoning: Thinking is any mental activity or  processing of information. ­ Heuristics: (AKA mental shortcuts) shortcuts to increase our  thinking efficiency. Simplifies what we attend to. The efficiency  of our brain can serve us well, but can also lead to faulty  conclusions. ­ Top down processing: have the expectation and work our way  down to the details. Streamlines cognitive functioning by  utilizing preexisting knowledge.  Decision Making: ­ Framing: has an impact on decisions even when the underlying  information relevant to these decisions is identical.  Example: 5% chance of winning vs. 95% chance of losing. ­ Problem solving: Generating a cognitive strategy to accomplish  a specific goal. We often rely on algorithms to solve problems  (longer version of heuristic/ step by step process) 


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