Chapter 1- Intro to Statistics: Lecture Material Flashcards
variables
characteristic that can change or take on different values, must be able to vary
- most research begins with a general question about the relationship between two variables for a specific group
Population
An entire group of individuals
Sample
- Samples are selected to represent the population, because normally populations are too large to examine the entire group
- The goal is to use results from the sample to answer questions about the population
inferential statistics
use sample data to draw general conclusions (inferences) about populations
defining and measuring sampling error is a large part of inferential statistics
descriptive statistics
- methods for organizing and summarizing data
- Tables or graphs used to organize data
- Descriptive values used to summarize data
parameter
- descriptive value for a population
statistic
descriptive value for a sample
sample statistics are not perfect representatives of pop parameters
Sampling error
the discrepancy between a sample statistic and its population parameter
data
- goal of statistics is to help researches organize and interpret data
- measurements obtained in research are called data
discrete variables
- consist of indivisible categories
ex. dice roll, football game points
continuous variables
are infinitely divisible into any unit the researcher chooses
nominal scale
- unordered set of categories identified by name only
- only determination you can make is whether two individuals are the same or different on that variable
ordinal scale
- ordered set of categories
- can tell the direction of difference between two individuals
ex. class rank, placing in a race
interval scale
- an ordered series of equal sized categories
- can identify the direction and magnitude of differences
- zero point is arbitrary
ex. temperature in degrees F or degrees C
ratio scale
- interval scale where a value of zero indicates none of the thing
- identifies direction and magnitude of difference
ex. temperature in Kelvin
correlation
- goal is to determine strength and direction of the relationship between two variables
- uses observation of two variables as they exist naturally
- correlation does not equal causation
experiments
- examine the relationship between 2 or more variables by changing one variable and observing the effects on the other variable
can only switch one variable at a time, ideally all other variables are controlled to prevent them from influencing the results
nonexperimental studies
- nonexperimental studies are similar to experiments because they also compare groups of scores
- they do not use a manipulated variable to differentiate between groups
- the independent variable is a pre-existing participant variable (male/female, before/after)
- no manipulations= no casual determinations (you cannot control for competing explanations of findings)
ex. relationship quality in couples making the transition into parenthoo
PEMDAS
summation w sigma notation comes before other addition and subtraction