Science the systematic method of observation and experimentation to answer questions about our reality Objectivity basing conclusions on facts instead of being swayed by personal belief emotion or bias Critical Thinking What questions should you be asking yourself if you re a critical thinker Is there any evidence 1 What am I being asked to believe accept 2 3 Are there other interpretations of the evidence 4 What extra evidence do I need 5 What is a reasonable conclusion Theory Facts and relationships that can explain and predict observed phenomena something that is basically accepted as fact until disproved Example s Newton s theory of gravity Hypothesis An educated guess as to why a certain event occurs Usually framed as If a then b You cant prove a hypothesis true just support an idea Hypothesis vs Theory a hypothesis is possible but not yet tested A theory is a well supported and documented reason for the phenomenon Peer Review sharing research with other experts before submitting it for publication Replication if the finding is very surprising or unexpected other scientists will attempt to replicate the experiment in the same way to double check its accuracy Scientific Method Review 1 objective observations 2 systematic observations testing a common occurrence not a fluke 3 hypothesis thats descriptive and predictive 4 peer review and replication of research Descriptive Methods ensure systematic as opposed to biased observation of real world issues 1 Case Studies observation of a small group in depth Example s removal and study of hippocampus of epilepsy surgery Phineas Gage Keonigs et all studied a damaged brain cortex and whether or not people with the damage made moral or utilitarian decisions Pros Cons Pros ability to analyze rare events like HM ability to look at naturally occurring disorders without having to cause one Cons May not generalize Difficult to find willing subjects 2 Naturalistic Observation Observing events in their natural setting Example s Jane Goodall s first hand observation of behavior and interaction of gorillas Stores observing customer shopping patterns to determine future advertisements people s buying patterns etc Pros Cons Pros ability to observe how people actually behave in the real world easy and inexpensive to acquire data Cons researcher s presence could alter the behavior of people how do you interpret your observations objectively and in an interpretive way 3 Surveys the questioning of an appropriate sample of a subset of the population Example s Survey to parents asking if they would vaccinate their children Pros Cons Pros large sample size inexpensive requires little time Cons people may not answer truthfully people may not answer correctly researcher may not get enough people to respond Correlation The direction and strength of a relationship between two variables Variable values that can vary within or across individuals Types of Correlations 1 No Correlation no relationship characterized by a random spattering of data 2 Negative Correlation as one variable increases the other decreases 3 Positive Correlation as one variable increases the other increases with it CORRELATION IS NOT CAUSATION ONE VARIABLE DOES NOT CAUSE THE OTHER Measure Perfect Positive Correlation 1 High Positive Correlation 8 Low Positive Correlation 3 Low Negative Correlation 3 High Negative Correlation 8 Perfect Negative Correlation 1 Third Variable contributes to the other correlating factors Uses of Correlations also think about what correlations CANNOT tell us Experiments research method allowing for controlled observations to test a hypothesis and make a claim Independent vs Dependent Variable Independent If I do this what is being manipulated Dependent Then this will happen the outcome of the manipulation Operationalization defining abstract independent and dependent variables into measurable units Control vs Experimental Group Control Group Undergoes all of the same conditions as the experimental group without the manipulation of an independent variable Experimental Group The group being tested on the group in which an independent variable is being tested Random Sampling Randomly selecting participants from the population Generalizability Being able to generalize results from the sample to the larger population Random Assignment this means that everyone has an equal chance of being in the experimental group or the control group to avoid bias achieve objectivity Double Blind Where the participants do not know whether they are in the control group or the experimental group Also the person distributing the dosage does not know which group they re in either Placebo An inactive substance that cannot be distinguished from the real subject Placebo Effect when the subject experiences a certain treatment because they believe they have taken the substance Example s Stereotype Threat gender difference people were told women were bad at math no gender difference people told there was no stereotype The women in the gender difference condition did worse than men but in the no gender condition men and women did the same Confounding Variable irrelevant variables that can alter the conclusion of research Pros Cons Certain people just like over the other People read into the search task in the control group Pros causality highly controlled easily replicated Cons artificial difficulty controlling all confounding variables operationalization Meta analysis analysis of many previous studies of a topic Experiments require an independent and dependent variable Experiments typically have a control group and an experimental group Control vs Experimental used to prevent confounding variables How do we study the effects of time 1 Cross Sectional Study comparing people from several age groups at once on a variable of interest Faster and less dropout 2 Cohort Effects specific type of confound when comparing across age groups one age group is drastically different from the experiences of the other 3 Longitudinal Study Data is collected from the same individuals over a number of years Take a lot of time and have huge dropout rate but prohibit cohort 4 Mixed Longitudinal Design Participants from several age ranges are selected and followed for a short time approx 5 years Conclusions from Data Reliable vs Valid Reliability subject tends to score the same no matter how many trials Validity test measures exactly what its supposed to measure Example s scale measuring weight anything thats