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77 terms

MAT 100 -- Exam #2 Vocabulary

a set of individuals about which we want to know something
what we do to count a population
a complete head count of the population; measures everyone in the population
an analysis of a (representative) subset of the population to estimate values of the whole
something that allows you to estimate a value or count indirectly
a (representative) subset of the population
the act of selecting a sample
the value of a variable of interest measured from a sample
the value of a variable of interest concerning the population (estimated by a statistic)
one-sample estimation
using a single sample of a population to estimate parameter values
two-sample estimation/capture-recapture
using a two-sample method to estimate the size of the population by determining the proportion of the population that was captured in the first sample and recaptured in the second using proportion
measurement problem
the issues associated with estimating the value of a population parameter
typically a survey that 1) chooses a sample which is representative, 2) measures the individuals in the sample, 3) makes inferences about the population
sampling proportion
the ration n/N: the number of people with a particular answer divided by the number of people in the sample
sampling bias
using a sample that is not representative of the population in some relevant way
selection bias
a sample has a built-in tendency to over-include or under-include a particular group in the population
target population
the population about which the results of a poll applies
sampling frame
is the (usually a) list of the population from which a sample is drawn
convenience sample
a sample drawn not because its representative, but because it is convenient for the researcher(s)
response rate
the percentage of people selected for a sample that actually respond to the survey
non-response bias
a bias in a data set because some people selected for the study chose not to respond
quota sampling
a systematic effort to force the sample to be representative of relevant subjects of a population through the use of quotas (similar to probability sampling)
(simple) random sampling
everyone in the population has an equal chance of being selected
stratified sampling
divides the population into relevant groups, and then a random sample is selected from within each group.
the groups (or layers) within a stratified sample
measures the relationship between the values of a pair of variables
one event causes another
clinical study
an experimental study used to determine if a treatment causes a particular result
confounding variables
a variable that may also effect the result of a study
controlled study
an experimental study where one of the treatment groups uses a placebo to help control for confounding variables
randomized controlled study
an experimental design that uses controls and randomly assigns subjects to treatment groups
placebo effect
the benefits achieving through believing that one is being treated even if the "treatment" is inert
an inert substance that has no effect on a response variable
blind study
the subjects of a study do not know what treatment they are receiving by researchers do
double-blind study
the subjects of study do not know what treatment they are receiving and neither do any of the researchers interacting directly with the subjects
data set
a collection of values for one or more variables
data point (datum)
each value in a data set
discrete variable
a variable with numerical outcomes that can only take on integer values
continuous variable
a variable with numerical outcomes that can take on any value within a range (including fractions and decimals)
bar graph
line graph
frequency table
a table used to organize data into the counts (frequencies) in each category or class
pie graph/pie chart
P% is below the given value
the middle value (50% above, 50% below)
first quartile
the value where 1/4 (25%) of the data is below that value, and 3/4 (75%) is above
third quartile
the value where 3/4 (75%) of the data is below that value and 1/4 (25%) is above
5-number summary
minimum, first quartile, median, third quartile, maximum
box plot
the difference between the minimum and maximum values
standard deviation
a measure of spread of a distribution (average deviation from the mean)
the standard deviation squared
interquartile range
the difference between the third quartile and the first quartile
random experiment
an activity or process whose outcome cannot be predicted ahead of time
sample space
the set of all possible outcomes of a random experiment
a subset of a sample space
simple event
a single element in a sample space
compound event
a set of elements in a sample space
impossible event
an event that cannot occur, and even not in the sample space
certain event
an event that must occur
the process of determining the number of elements in a set
a list of ordered events where repetition is not allowed//the count of such events
a list of unordered events where repetition is not allowed//the count of such events
probability assignment
a function that assigns valid probabilities (between 0 and 1) to a set of events
equiprobable space
a probability assignment where all events are equally likely
complementary events
a pair of events that divide the sample space into two sets: those in event A, and all others not in A
independent events
the outcome of event A does not influence the probability of event B
odds for (an event)
the proportion of elements in event A divided by the proportion of elements not in event A
odds against (an event)
the proportion of elements not in event A divided by the proportion of elements in event A
weighted average//expected value
a mean calculated by considering the frequency of events at each value
fair game
a game where the expected value is 0 for all players
explanatory variable
the variable in an experiment that is being manipulated to (maybe) cause the result
response variable
the variable that is measured at the end of an experiment that is thought to be caused by the explanatory variable
block design
a study design where participants are broken up into groups (typically demographic groups like race, gender, or some other behavior), and then where each group is divided into treatment and placebo groups for the experiment. This is done to help control for possible confounding variables.