1.Exceptionally broadTopics studied include:•Biochemistry•Physiology•Sociology/AnthropologyMultilayered : To overcome "over-determination of events"2.Topics studied:Functions/Nature of causality in human relationships •Single events have multiple causes; our explanations must therefore be multi-layered. In other words, complex behaviors inherently have multiple causes, including biological, psychological/environmental. •Nomothetic versus Idiographic3.Nomothetic laws : General laws and are thought to apply to all people, at all times, and in all situations. e.g. If a person does something and are given a positive reinforcement soon after (e.g. rewards), they are more likely to do that in the future. This is true independent of sex, race, geographical location etc. In general, we are motivated to maximize (duration and intensity of) pleasure and minimize pain. Other examples: principles of learning, principles of perception.•Such laws explain how we are all the same. •Idiographic laws: laws that are used to explain our uniqueness e.g. individual personalities•Psychologically aspires to be simultaneously nomothetic and ideographic. e.g. All of us are motivated to maximize pleasure and minimize pain (nomothetic), but the way each individual tries to maximize pleasure and minimize pain will be different (idiographic).•Correlational Methods:Scatterplots vs. Coefficients1.0 = no relationship2.+ = direct relationship3.- = inverse relationship4.Causal inference5.Strength-Weakness relationships between variables•Advantages of correlational relationships:Very useful in identifying phenomena that we want to understand better.i.e.g.1. People who were abused as children, are more likely to abuse children over a long period of time, compared to people who were not abused as children. This does not mean that if a given individual was abused as a child, they will definitely abuse a child in the future. •In other words, there is a correlation between growing up in an abusive home (as a victim) and becoming abusive to children in the future.e.g.2. There is a correlation between sex and aggression. This does not mean that every man is more aggressive than every woman. •They can be done on a very large scale. ii.e.g. Correlational studies with large sample sizes (30-1000's)•They are relatively cheap to conduct.iii.e.g. Can be done on the internetThey can be used to investigate a much wider range of questions than other research methods in experimental psychology.iv.Disadvantages of correlational relationships:They provide a very weak way of testing any given theory. Correlation does not imply causation.Methods of doing correlational analysis:Scatterplots are a pictorial representation of the relationship between two variables.•Coefficients are a numerical representation of the relationship between two variables.•Week 3.5 Psych 100: The distinct features of PsychologyThursday, September 12, 20131:59 PM Week 3.5 Psych 100 Page 1Coefficients are a numerical representation of the relationship between two variables.•Questions examined by correlational analysis:Are two variables related or not?i.How are the two variables related?ii.How strongly are the two variables related? As values on one variable go up (or down) do values on the other variable go up (or down)?iii.Is the relationship between two variables the same or different in different groups of people?iv.Correlational Coefficients:Correlational coefficients can only take on values between -1.00 and 1.00 (including 0). -1.00 0 1.00When the correlational co-efficient is 0.0:e.g. relationship between shoe size and IQ.the two variables are not related i.e. if you know something about one variable, you know absolutely nothing about the nature of the other variable. •on the scatterplot, there is so much variance, that there is no line of best fit that could describe the relationship between the two variables (R= regression coefficient tends to 0).•When the correlational co-efficient is > 0.0:e.g. relationship between income and IQon the scatterplot, there is a line of best fit that could describe the relationship between the two variables (R= regression coefficient is > 0).•Note 1: You cannot precisely predict the value of one variable, given the value of the other, but you can estimate the range of values a variable can take, given information on the other. Note 2: A greater correlation will have a greater cluster of points closer to the line of best fit; e.g. the spread of observed values will be less for a correlation co-efficient of 0.8 (r= 0.8) compared to the observed distribution of values for a correlation co-efficient of 0.5 (r =0.5)Note 3: There is an upward slope in the scatterplot.The two variables are related;i)There is a positive/direct relationship b/w the variables: As values on one variable go up, values on the other variable also go up.ii)r= 0.5 (say) iii)When the correlational co-efficient is < 0.0:e.g. 1. relationship between age and no. of fantasies.e.g. 2. income and no. of bounced checks on the scatterplot, there is a line of best fit that could describe the relationship between the two variables (R= regression coefficient is < 0).Note 1: You cannot precisely predict the value of one variable, given the value of the other, but you can estimate the range of values a variable can take, given information on the other. Note 2: A greater correlation will have a greater cluster of points closer to the line of best fit; e.g. the spread of observed values will be less for a correlation co-efficient of -0.8 (r= -0.8) compared to the observed distribution of values for a correlation co-efficient of -0.5 (r =-0.5)Note 3: There is a downward slope in the scatterplot.i.The two variables are related;ii.There is an inverse relationship between the two variables. As values on one variable go up, values on the other variable go down.Theoretically, r = 1.00 or r = -1.00 generates a single line of best fit, where all points neatly fall on the line. This does not happen in real world situation. Week 3.5 Psych 100 Page