case study - in depth observation of one person or a small group.

Hard to generalize from case studies

Goals of science:

describe

predict

explain

control

theory: idea or guide for organizing and explaining a phenomenon

hypothesis: an educated guess about the relationship between two or more variables.

variables: things that can vary (duh!)

categorical variables: values are different members of a category

Ex: Nationality

continuous variables: values vary in magnitude along some dimension

Ex: Income

Hypothesis:

When our housemate doesn't get enough sleep, she is grumpy.

Alternative hypothesis:

When our housemate isn't getting enough love, she is grumpy.

Predictor variable: variable that is hypothesized to produce a change in...

Outcome variable: variable hypothesized to who a difference when value of predictor is changed

manipulated variables - variables that the researcher controls and changes.

independent variable- variable the experimenter manipulates while holding all other starting conditions constant (varies INDEPENDENTLY of everything else).

dependent variable - variable whose value is hypothesized to vary according to value of independent variable (value DEPENDS on independent variable).

True experiment: Experimenter manipulates (controls and changes the value of) the independent variable; everything else is held constant.

subject variables - non-manipulated variables associated with qualities of the subjects in your study (e.g., IQ nationality, virgin/not virgin).

When we don't manipulate predictor variable, we are doing correlational research

Practice question!!

Which study is most likely to be a true experiment?

a. A study comparing reading comprehension in HIV-positive and HIV-negative 18 year-olds

b. A study that examines who can tell lies more convincingly, 8-year-olds or 13-year-olds.

c. A survey designed to find out if people from the southeastern U.S. are more polite than those from the northeast.

d. A test of performance to see if athletes perform better when their coaches are present or when their coaches are not present.

If we don't manipulate our predictor variable, we can't say for sure whether or not it CAUSES our outcome variable.

Correlational Research - research that examines the degree to which two variables are related, so that knowing the value of one allows us to predict the other

- but we don't know whether one causes the other.

correlation does not equal causality!!!

If 2 variables are correlated, when one changes, the other does too.

Correlation coefficient - measure of how closely the values of two variables are related to each other.

ranges from -1.0 to 1.0

positive correlation - when one number goes up, the other goes up

negative correlation - when one number goes up, the other goes down

perfect correlation - one variable can be EXACTLY predicted from the other (e.g., -1.0 or 1.0 correlation)

Possible causal realtionships between two correlated variables:

a causes b

b causes a

c causes a & b

Practice question!!

As the number of churches goes up in a town, so does the number of crimes committed. From this relationship, you can definitely conclude:

a. There is a negative correlation between number of churches and number of crimes.

b. Building more churches causes a higher crime rate.

c. An increase in population causes more crime and produces a greater need for churches

d. None of the above