PSYC 1000 Notes - Chapter 1
PSYC 1000 Notes - Chapter 1 PSYC 1000
Popular in Introductory Psychology
Popular in Psychology (PSYC)
This 4 page Class Notes was uploaded by William Maloney on Monday September 19, 2016. The Class Notes belongs to PSYC 1000 at Tulane University taught by Melinda Fabian in Fall 2016. Since its upload, it has received 7 views. For similar materials see Introductory Psychology in Psychology (PSYC) at Tulane University.
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Date Created: 09/19/16
Thinking Critically with Psychological Science Overview How do we gather psychological information in a scientific way? Think critically with psychological science Critical thinking is carefully forming/evaluating knowledge rather than simply using intuition In addition to the scientific method, critical thinking gives us effective ways of finding out how people work what makes people do, think, and feel certain things. The human mind is good at meeting basic needs and relationships the bigger picture, but it fails at the details we make critical thinking errors. When our natural thinking style fails Hindsight bias After learning the result of some psychological research, you believe you could have predicted that very outcome. Overconfidence error We are too certain in our judgment We overestimate our performance, rate of work, skills, and self control We overestimate the accuracy of our knowledge people are more certain than they are accurate. Problematic in eyewitness testimony Can be a problem on tests if you feel confident in your knowledge, try to explain it to someone else Perceiving order in random events We have the wrong idea about what randomness looks like We are always trying to make sense of something How to go about being scientific Be systematic Be objective Be a critical thinker Examine assumptions Look for hidden bias Put aside your own assumptions and biases How was the information collected? Other possible explanations? The Scientific method Set up situations to test our idea Make careful, organized observations Analyze if the data fits out ideas Make conclusions see if data supports our original idea Steps/the basics A theory is a principle that explains a phenomenon and predicts future behavior A hypothesis is a testable prediction consistent with our theory Operational Definitions How research variables are defined Ex. For measuring ADHD decisions, we measure impulsivity by number of times a student calls out without raising his or her hand. Replications Uses same operational definitions and procedures Validates results when tested on other people Research goals and types Descriptive research is a systematic, objective observation of people Goal is to provide an accurate picture of people’s behaviors, thoughts, and attributes Just descriptions; doesn’t give a lot of depth Case study i s examining one individual in great depth The danger is that it can be unrepresentative Naturalistic Observation Just watching and not trying to change anything observing “natural” behavior. Survey Gathering information through self report Many cases, less depth Cheap Random Sampling A technique for making sure every member of a population has an equal chance of being chosen. Correlational Research Correlation: When two traits/attributes are related Scientific definition: A measure of how closely two factors vary together Finding correlations: scatterplots Positive correlation Variables increase/decrease together Negative correlation Variables vary in opposite direction Correlation Coefficient (r) Indicates direction and strength of relationship Range is from 1 to +1 0 is no relationship If we find a correlation, what conclusion can we draw? Not much: there may be a hidden variable Can’t determine causality Experimentation Manipulating one factor in a situation to determine its effect while other factors are kept under c ontrol Only way to determine cause/effect One of the hardest, most invasive types of research Experimental and control groups Random assignment o f participants to control/experimental groups Placebo Effect: Experimental effects caused by expecations Placebo is the fake treatment in place of the experimental treatment Ideally, the control group is blind to whether they’re getting the fake treatment or not Many studies are d oubleblind: N either participants nor staff know who’s in what group Variables Independent Variable (IV) Dependent Variable ( DV) Confounding variables m ay have an effect on dependent variables From data to insight: statistics Once we’ve gathered data, we use statistics to: Present an accurate picture of data Help us reach valid conclusions Tools for describing data Most data representations can be manipulated even if the data is correct, it can be represented in a biased way Measures of central tendency Mode Mean Median Skewed distributions are those in which a few data points greatly raise the mean Range: Difference between highest and lowest scores Standard Deviation: Average distance of scores from mean Normal Curve: A symmetrical, bell shaped curve that describes the distribution of many types of data (normal distribution). Most scores fall near the mean. Drawing conclusions from data: are the results useful? After finding a pattern in the data that shows a d ifference etween one group and another, we can ask more questions. Is the difference r eliabl Can it predict future behavior? Achieved via: Unbiased sampling Consistency Many data points Is the difference significant? Could it have been the result of variation? When is this true? When your data is reliable When the difference between the groups is large
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