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42 Cards in this Set

  • Front
  • Back
data
observations that have been collected.
statistics
collection of methods for planning studies and experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpeting, and drawing conclusions based on data.
population
complete collection of all elements to be studied.
census
collection of data from every member of the population.
sample
subcollection of members selected from a population.
parameter
numerical measurement describing some characteristic of a population.
statistic
numerical measurement describing some characteristic of a sample.
Quantitative Data
Consist of numbers representing counts or measurements.
Qualitative Data
Can be separated into different categories that are distinguished by some nonmuneric characteristic.
Discrete Data
Type of quantitative data; must always be a whole number (no decimals)
Continuous Data
type of quantitative data; result in measurments, can be decimals.
Nominal level of measurment
characterized by data that consist of names, labels, or categories only. The data cannot be arranged in order.
Ordinal level of measurement
characterized by data that can be arranged in some order, but the differences between data values cannot be determined or are meaningless.
interval level of measurement
characterized by data that can be arranged in some order, and the difference between any two data values is meaningful. However, data at this level do not have a natural zero starting point.
Ratio level of measurement
like the interval level, but has a natural zero starting point (where none of the quantity is present). Differences and ratios are both meaningful at this level.
Voluntary response sample (self-selected sample)
a sample which the respondents themselves decide whether to be included (biased)
Loaded Questions
Questions intentionally worded to elicit a desired response.
Nonresponse
when someone rufuses to respond to a survey question or is unavailable.
Correlation Does Not Imply Causality
just because there is a statistical association between two variables, you cannot conclude that one of the variables is the cause of (or directly affects) the other variable.
Self-Interest Study
sponsored by someone who has something to gain from the results.
Prescise Numbers
very large quantities are difficult to compute. It is likely an emimate and should not be considered accurate.
Deliberate Distortions
when results are falsified
Observational study
we observe and measure specific characteristics, but we don't attempt to modify the subjects being studied.
Experiment
apply some treatment and then proceed to observe its effects on the subjects.
cross-sectional study
data are observed, measured, and collected at one point in time.
retrospective study
data are collected in the future from groups sharing common factors (cohorts)
Confounding
occurs in an experiment when you are not able to distinguish amoung the effects of different factors.
Blinding
occurs when the patient doesn't know if they are getting the drug or the placebo
Double-blind
if patients and doctors don't know who is getting a drug or the placebo
Randomized block design
1) form blocks (or groups) of subjects with similar characteristics; and 2) randomly assign treatments to the subjects within each block. You would do this when groups are different in ways that are likely to affect the responses to treatments.
Completely randomized experimental design
subjects are assigned to different treatment groups through a process of random selection.
Rigorously Controlled Design
subjects are carefully chosen so that those given each treatment are similar in ways that are important to the experiment.
Random sample
members from the population are selected in such a way that each individual member has an equal chance of being selected.
simple random sample
n subjects is selected in such a way that every possible sample of size n has the same chance of being chosen.
probability sample
involves selecting members from a population in such a way that each member has a known (but not necessarily the same) chance of being selected.
systematic sampling
we select some starting point and then select every kth element in the population.
convenience sampling
we simply use results that are very easy to get.
stratified sampling
we subdivide the population into at least two different subgroups (or strata) so that subjects within the same subgroup share the same characteristics, then we draw a sample from each subgroup (or stratum).
cluster sampling
we first divide the population area into sections (or clusters), then randomly select some of those clusters, and then choose all the members from those selected clusters.
Multistage Sampling
involves the selection of a sample in different stages that might use different methods of sampling.
sampling error
the difference between a sample result and the true population result; such an error results from chance fluctuations
nonsampling error
occurs when the sample data are incorrectly collected, recorded, or analyzed (such as selecting a biased sample, using a defective measuring instrument, or copying the data incorrectly.