Use LEFT and RIGHT arrow keys to navigate between flashcards;
Use UP and DOWN arrow keys to flip the card;
H to show hint;
A reads text to speech;
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.
|