stats for behavioral science 1

Population vs. Sample

• Population is the parameters

• Sample is the stantistics

How do we measure variables?

Scales of measurement:

• Nominal: categorical or qualitative (ex. political party, religious affiliation)

• Ordinal: able to be ranked but does not give intervals (ex. class rankings)

• Interval: ranked and shows the intervals (ex. temperature in degrees and age)

• Ratio: everything but could have infinite amount of variables between the intervals (ex. weight, height, time)

Continuous vs. Discrete Variables

• Continuous meaning they can continue going on forever, or an infinite amount of variation in between intervals (ex. time, weight, height)

• Discrete meaning you know there is no decimal between the intervals (ex. number of children, pages in a book)

Don’t confuse the variable with how it’s measured

Parametric vs. nonparametric statistics

Depending on level of measurement and underlying assumptions about data

Experimental vs. observational research

Correlation does not mean causation, experimental research means randomly selecting people, while observational is with groups that already do the activity and the researcher just observes.

Pygmalion effect

The phenomenon whereby one person’s expectation for another person’s behavior comes to serve as a self-fulfilling prophecy

Independent vs. dependent variables

Independent variables are the cause or factor you change in an experiment and dependent variables are the effect or factor you are measuring