Lecture 2 and 3 – 1/16/15 and 1/21/15 – and Chapter 2 Notes- Scientific Method: how you develop an experiment first through hypothesis and then through the actual experimento Hypothesis: prediction about what will happen under particular circumstanceso Theory: body of related propositions intended to describe some aspect of the world- Research Methodso Correlational Study: the degree to which two variables have a relationship Positive Correlation: as one variable increases, the other also increases (+1.0) Negative Correlation: as one variable increases, the other decreases (-1.0)- Correlation DOES NOT determine causation, only describes relationso Causation: whether or not one variable actually causes another- Illusory Correlation: illusion that has no actual relationship and no causation Surveys: series of questions written down and asked to subject group- Results can change on the way the questions are asked, whether or not the responses are voluntary or there is an incentive, and whether or not the topicapplies to the specific person- Population: the group you wish to know abouto Sample: smaller group of the population Ex: 50 people instead of 500 peopleo Random Sample: small group of the population that is unbiased in the choosing so that everyone has a chance of being chosen Ex: Assigning random numbers to each person of the population and then using a random number generator to choose who to includeo Representative Sample: accurately represents the population’s demographics  Ex: No exclusions based on race, religion, or other defining aspectso Convenience Sample: sub group in the population that is more convenient to sample, not necessarily representative Ex: rather than random college students across the nation, you only look at CU Boulder college studentso Descriptive Research: observe and describe behaviors over time and document phenomenon Observational Study: only observing the subjects without interfering- Can happen in laboratories and in nature (naturalistic observation)o Lab Study: good for controlling variables, but subjects might act differently because they know they are being watched (humans specifically) High on Internal Validity (valid in experimental settings but not necessarily in real life)o Naturalistic Study: good for observing real life behavior, but high occurrence of confounding variables Confounding variables: something that was never consideredinterfering with your experiments and resultso Participant Observation: observing at close range, usually for learningsomething, can still only guess on many things howevero Archival Research: looking at descriptions made by others to gain insight about a particular groupo Validity: how accurately your research and results reflect situations Internal validity: valid in experimental situations but not in real life External Validity: very generalizable to average actions that occur in real life but cannot define exact reasons - Case Studies: following a single person or a small group of people to better understand a phenomenon- Longitudinal Study: following a single person or a small group for a long period of time to see how the aspect being studied affects their liveso Experimental Research: research done to discover causation and effects of variables through the scientific method Independent Variable: the variable that you can control in an experiment Dependent Variable: output that depends on the controlled variable Control Group: Group that is not affected by the independent variable and rather given a placebo or nothing Random Assignment: assigning participants to groups randomly so there is less bias Bell Curve: the curve showing that a majority of trials should show up within 1 or 2 deviations from the mean- Too outlying results are not representative of the population- P Values: whether or not the results are significant (less than 0.5 is significant)o Statistical Significance: measure of the probability that the result could have occurredby chanceo Measurement Validity: correlation between some measure and some outcome that the measure is supposed to predict Reverse Causation: when X is assumed to cause Y, yet the opposite might be the real cause Third Variable: some other variable that exerts a casual influence on both X and Y Self Selection: participants that personally vary how they act and affect the level of each variable rather than the experimenter being in