ap statistics vocab Word Scramble

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Question	Answer
population	the entire group of individuals that we want information about
sample	a part of a population that we actually examine in order to gather information about the entire population
statistical inference	coming to a conclusion about an entire population based on sample
terms associated with sampling	involves studying a part to gain information about the whole (often very accurate)
sample design	the method used to choose the sample from the population (poor sample design can produce misleading conclusions)
voluntary response sampling	(often biased) people choose to be in a sample. This technique usually involves outgoing people with strong opinion, usually negative ones
convenience sampling	(often biased) chooses individuals that are easiest to reach
cluster sampling	when a population falls into naturally occuring subgroups, each having similar characteristics. 1) divide the population into groups/clusters 2)select ALL members of one or more clusters
systematic sampling	a sample in which each member of a population is assigned a number. Members of a population are ordered in same way. Sample members are selected at regular intervals from a starting number
confounding	variables are confounded when their effects on a response variable cannot be distinguished from each other
bias	the design of a study is biased if it systematically favors certain outcomes (does not have to be intentional for it to occur, however a good experimental designer must avoid it at all costs)
simple random sampling	choosing "n" individuals from a population in such a way that every set of "n" individuals has an equal chance of being in sample actually selected
census	a survery that attempts to contact every individual in an entire population
survey	a series of questions that attempts to gather information about a population or sample
table of random digits	a long string of the digits 0,1,2,3,4,5,6,7,8,9 where each entry is equally likely to be any of these ten digits and entires are independent of each other
probability sample	a sample chosen by chance. We must know what samples are possible and what chance or probability each possible sample has
stratified random sample	1)divide population into groups of similar individuals(strata) 2)then choose separate SRS in each stratum 3)combine the SRS from all strata to form the overall sample
multistage sample design	choose the sample in stages. 1)break population up into groups 2)randomly select a certain number of groups 3)from those groups selected, then randomly pick sample from each
undercoverage	occurs when some groups in the population are left out of the process of choosing a sample
nonresponse	occurs when an individual chosen for the sample can't be contacted or does not cooperate
response bias	respondents lying, usually about illegal or unpopular behavior
wording of questions	confusing or leading questions can introduce bias
sampling size	usually large samples are more accurate than smaller samples (relatively speaking)
sampling frame	a list of all individuals from a population from which a sample is chosen. This should be ENTIRE population, but in practice, this is difficult
observational study	observes individuals and measures variables, but does not attempt to influence the responses (usually poor way to find EFFECT of one variable on another)
experiment	imposes a treatment on individuals to observe their responses. 1)randomization 2)control group 3)impose a treatment 4)replication
experimental units	the individuals on which an experiment is done. They are "subjects". A specific experimental condition applied to the units is called a treatment.
treatment	the specific experiment condition applied to the unit
factor	the explanatory variable in an experiment. At times there can be many factors
level	the specific value of the each factor
placebo effect	a placebo is a dummy treatment. Most subjects respond favorably to ANY treatment, even a "fake" one. The response to the dummy treatment is known as the placebo effect.
control group	the group of subjects that receive the fake treatment (placebo). The control group helps to alleviate confounding effects of the placebo effect
matching	trying to ensure that the experimental group and control group are matched (have the same type of subjects)
completely randomized design	when all experimental units are allocated at random among all treatments. This helps average out the effects of chance in sample that are large enough
statistical significance	an observed effect too large to attribute to just chance (did change occur because of the actual treatment imposed or was it just chance?)
replication	repeating each treatment on a large enough number of experimental units or subjects
principals of experimental design	1)control: the effects of confounding variables on the response variable 2)randomize: use impersonal chance to assign experimental units to treatments 3)replication: each treatmenton many units to reduce chance variation in results
hidden bias	taking care that all experimental units or subjects are treated in exactly the same way. If not hidden bias could occur
blind experiment	the subjects do not know what treatment they receive
double blind experiment	not only does the patient not know what treatment they are receiving, but the person administering the treatment and/or the person recording the results does not know which treatment is being administered
block design	a block is a group of subjects that are simliar in ways that are expected to affect the response to treatments
matched pairs design	design that compares two treatments. -each block consists of two units or subjects closely mathced -subject: are assigned randomly to treatments and results are compared

Created by: lauraprz12