Chapter 1 Flashcards
science of collecting, organizing, summarizing, and analyzing data to draw conclusions or answer questions + provide a measure of confidence in conclusions
statistics
a fact or proposition used to draw a conclusion or make a decision - information that varies
data
the entire group to be studied
population
person/object that is a member of the population being studied
individual
statistic that describes the results of a sample without making any generalizations about population
descriptive statistic
a numerical summary of a sample
statistic
statistic that extends the results of a sample to the population and measures the reliability of the result (level of confidence)
inferential statistic
a numerical summary of a population
parameter
classified based on an attribute or characteristic of the individual (ex. gender, zip code)
qualitative variable
provide numerical measures of individuals that can be added or subtracted in meaningful ways (ex. temperature, number of days studied)
quantitative variable
quantitative variable with a finite number of possible values (countable)
discrete variable
quantitative variable with an infinite number of possible values (measured not counted)
continuous variable
first level of measurement - values of the variable name, label, or categorize (qualitative)
nominal level
second level of measurement - values of the variable can be arranged in a ranked or specific order (qualitative)
ordinal level
third level of measurement - differences in values of the variable have meaning, addition/subtraction can be done, 0 doesn’t mean absence of quantity (quantitative)
interval level
fourth level of measurement - ratios of the values of the variable have meaning, multiplication/division can be done, 0 means absence of quantity (quantitative)
ratio level
study that measures value of the response variable without attempting to influence the response or explanatory variable - collecting data by simply watching
observational study
study in which the researcher intentionally manipulates the explanatory variable and controls other variables at fixed values, recording the response for each - required in order to determine causality
designed experiment
when the effects of two or more explanatory variables are not separated - any relation between explanatory and response variable may be due to some other variable not accounted for
confounding
explanatory variable that was not considered in a study, but that affects the value of the response variable
lurking variable
explanatory variable that was considered in the study, whose effect cannot be distinguished from a second explanatory variable in the study
confounding variable
observational study that collects information about individuals at a specific point in time / a very short period
cross-sectional study
observational studies that are retrospective, looking back in time at existing records
case-control study
observational studies that observe a specific group of individuals over a period of time, collecting data as they go (prospective)
cohort study
collecting data based on looking back in time at existing records
retrospective
collecting data over a period of time going forward
prospective
list of individuals in a population along with certain characteristics of each individual (AKA frame)
census
using chance to select individuals indiscriminately from a population to be included in a sample
random sampling
every possible random sample has an equal chance of occurring
simple random sampling
sample obtained by dividing population into non-overlapping groups (strata) and obtaining a simple random sample from each - individuals within each strata are similar to each other
stratified sample
sampling method that doesn’t require a frame - selecting every (k)th individual from the population
systematic sample
sample obtained by selecting all individuals within a randomly selected collection or group of individuals
cluster sample
sample in which the individuals are easily obtained and not based on randomness - flawed method of sampling
convenience sample
the results of the sample are not representative of the population
bias
form of bias when the technique used to obtain sample’s individuals tends to favor one part of the population over another
sampling bias
when the proportion of one segment of the population is lower in a sample than it is in the population - a cause of sampling bias
undercoverage
form of bias when the individuals selected to be in the sample who do not respond to the survey have different opinions from those who do
nonresponse bias
form of bias when the answers given on a survey do not reflect the true feelings of the respondent
response bias
question that allows the respondent to provide his or her own response
open question
question that requires the respondent to choose from a list of predetermined responses
closed question
controlled study conducted to determine the effect of varying one or more explanatory variables (factors) on a response variable
experiment
any combination of the values of the explanatory variables (factors) in an experiment
treatment
person, object, or other well-defined item upon which a treatment is applied in an experiment (AKA subject)
experimental unit
baseline treatment that is used to compare to other treatments in an experiment
control group
innocuous medication with no effect that looks, tastes, and smells like the experimental medication - used to prove efficacy of experimental medication
placebo
non-disclosure of the treatment an experimental unit (subject) is receiving
blinding
the experimental unit (subject) is unaware of which treatment they are receiving, but the researcher knows
single-blind experiment
neither the experimental unit (subject) nor the researcher knows which treatment the experimental unit is receiving
double-blind experiment
experimental design in which experimental units are paired up based on some way they’re related / similar - one receives one treatment, the other receives another
matched-pairs design
