Midterm 1 Flashcards
statistics
the science of collecting, analyzing, and interpreting data
statistic
a measure of some attribute of a sample (samples can be one element, or a large collection of elements)
descriptive statistics
statistics focus on a group of numerical observations about a population of interest
inferential statistics
interpretations about populations based on analyses of smaller set of information
variables
general characteristics, usually quantified, that VARY and can be used to compare or describe
variability
the fact that variables obtained often differ from one another
constructs
a hypothetical measure that is designed to generate variables that can be used to explain/measure an idea or concept
operational definition
a method of obtaining or measuring a variable
levels
a method of obtaining or measuring a variable
reliability
consistency in measurement
validity
accuracy of measurement with respect to intent
independent variables
variables that have at least 2 levels that we either manipulate or the observe in a group
dependent variables
variables that are believed to be caused by or changed by the independent variable
advantages to mean
LOWEST sampling variability
advantages to mode
Easy to calculate
advantages to median
Good for distributions that are skewed/have extreme outliers
disadvantages to mean
The only measure of central tendency that is sensitive to outliers
disadvantages to mode
Gives little info about the entire distribution.
disadvantages to median
Does not represent all of the scores in the distribution
outliers
Numbers that are much greater or much less than the other numbers in the set
measures of variability
Measures of variability allow us to talk about how close or far from the mean the scores in the distribution are.
random assignment
creating groups by giving each participant an equal chance of being in the experimental conditions/levels
stratified assignment
creating equivalent groups based on important characteristics
replication
duplication of a study with a different group, obtained in a different way, in order to verify the results
sample statistic
the measureable characteristic of the sample of the population that we’re interested in
sampling statistic
selecting a subset of the population to collect data from (statistics) in order to make inferences about the population (parameters)
subjective probability
probability based on an individual’s opinion of the likelihood that an event will occur, or that an event or relationship is due to more than chance
expected probability
a measure of the actual probability of an outcome if the outcomes were random and repeated many times
null hypothesis
a statement that implies no effects, differences, or similarities on or between variables within a population of interest
alternative hypothesis
a statement that implies that the null hypothesis is false (untrue)
4 types of studies
Case studies
case studies
an analysis of statistics of one element or a small sample of elements
non-experimental studies
analyses that compare or measure similarities/differences within a group that we do not manipulate
experimental studies
NAME?
construct validity
is it measuring what we’re interested in
predictive validity
does the measure predict related behavior/measures
concurrent validity
does it relate to other measures that are supposed to be measuring the same thing
continuous
variables that can assume an infinite number of values
discrete variables
variables that have a finite set of variables
categorical variables
variables that have no numerical meaning
quantitative variables
the levels of these variables that are represented as numbers
ordinal
variables that have that have a natural order, but the precise distance between values is not defined
interval
variables that have values where the distance between them is meaningful and consistent
ratio variables
interval variables where there is a true 0 and where ratios of values make sense
real limits
NAME?
midpoint
the precise center of a class interval
true random sampling
taking the entire population and selecting a sample randomly from that population
stratified sampling
identifying some major characteristics of interest in the population (e.g. gender, age, race, etc.) and generating a sample that is proportionally equivalent to the population
pseudo-random sampling
taking everyone that is accessible from a population of and selecting a sample randomly from that group
cluster sampling
random sampling of organized groups of individuals from the population
measurement error
variation due to the inability to measure something accurately
unreliability
variations due to differences in responses to the same situation
concepts that impact the scores
measurement error
convenience sampling
taking a select sample from the population that is easily accessible
volunteer sampling
sampling that is obtained through the willing participation
