PSY201: Intro Flashcards
Statistics
describe data - summarize, organize, interpret findings: relationship, effect of manipulation, how big that effect is
without stats, data + findings meaningless
provide ‘universal’ language (rules) to communicate results
population
entire group of individuals
Rarely have opportunity to study entire category/group of interest
parameters
Pop characteristics
Sample
represent pop in research study
goal is to use results obtained from sample to help answer questions about pop
statistics
Sample characteristics
Variables
characteristic/condition that can change/take on different values
Discrete variables
consist of indivisible categories (class size)
continuous variables
infinitely divisible into whatever units researcher may choose (time/weight)
Real Limits
boundaries located exactly half-way betw adjacent categories
Independent Variable (IV)
manipulated; the manipulation is called a treatment
DependentVariable
observed + measured to determine effect of treatment
measuring variables
To establish relationships betw variables, researchers must observe variables + record observations
scale of measurement
set of categories
nominal scale
unordered set of categories identified only by name
measurements only permit you to determine whether 2 individuals same/different
ordinal scale
ordered set of categories in terms of size
measurements tell you direction of diff betw two individuals.
interval scale
ordered series of equal-sized categories
measurements identify direction + magnitude of difference zero point is located arbitrarily on an interval scale
ratio scale
interval scale where value of zero indicates none of variable measurements identify direction + magnitude of difference + allow ratio comparisons of measurements
Experiments
to demonstrate cause + effect relationship betw 2 variables show that changing value of 1 variable causes changes in a 2nd variable
Experiments
one variable is manipulated to create treatment conditions. A second variable is observed and measured to obtain scores for a group of individuals in each of the treatment conditions.
Experiments
measurements compared to see if there are diff betw treatment conditions
All other variables controlled to prevent them from influencing results
Correlational Studies
to determine whether there is relationship betw 2 variables + to describe relationship
simply observes 2 variables as they exist naturally
Non-experimental or quasi-experimental
don’t use manipulated variable to differentiate groups
variable that differentiates groups usually pre-existing participant variable (male/female)/time variable (before/after)
Non-experimental or quasi-experimental
cannot demonstrate cause + effect relationships
similar to correlational research because they simply demonstrate + describe relationships
Data
measurements obtained in research study
goal of statistics is to help researchers organize and interpret the data
Descriptive statistics
Numbers used to simplify, summarize + describe data
Do not involve generalizing beyond description
descriptive value for pop = parameter
descriptive value for sample = statistic
Descriptive statistics
avg scores used to summarize data
Tables/graphs used to organize data
Inferential statistics
methods for using sample data to make general conclusions (inferences) about pops
sample data provide only limited info about pop
sample statistics generally imperfect representatives of corresponding pop parameters
Sampling Error
discrepancy betw sample statistic + its pop parameter
Defining + measuring sampling error large part of inferential statistics
Notation
X (X + Y if multiple scores): individual measurements/scores obtained for participant # of scores in data set identified by N for pop/n for sample
Notation
Summing set of values common in stats
Greek letter sigma, Σ: sum of
ΣX identifies the sum of the scores
Order of Operations
- All calculations within parentheses
- Squaring/raising to other exponents
- Multiplying + dividing
- Addition (summation) with Σ notation
- Subtraction
