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Test your basic knowledge |
AP Statistics Vocab
Start Test
Study First
Subjects
:
statistics
,
ap
Instructions:
Answer 50 questions in 15 minutes.
If you are not ready to take this test, you can
study here
.
Match each statement with the correct term.
Don't refresh. All questions and answers are randomly picked and ordered every time you load a test.
This is a study tool. The 3 wrong answers for each question are randomly chosen from answers to other questions. So, you might find at times the answers obvious, but you will see it re-enforces your understanding as you take the test each time.
1. An equation or formula that simplifies and represents reality
bar chart
comparing distributions
model
marginal distribution
2. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
comparing distributions
distribution
re-express data
factor
3. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
predicted value
randomization
statistically significant
pie chart
4. Distributions with two modes
correlation
statistic
quantitative variable
bimodal
5. When an observed difference is too large for us to believe that is is likely to have occurred naturally
statistically significant
standardizing
tails
regression line
6. The square root of the variance
boxplot
standard deviation
predicted value
representative
7. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
comparing distributions
observational study
matching
lurking variable
8. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
voluntary response bias
uniform
sampling variability
symmetric
9. Individuals on whom an experiment is performed
extrapolation
lurking variable
predicted value
experimental units
10. When either those who could influence or evaluate the results is blinded
area principle
bimodal
single-blind
quantitative variable
11. Holds information about the same characteristic for many cases
variable
center
conditional distribution
sample survey
12. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
shape
response
census
stratified random sample
13. Consists of the individuals who are conveniently available
quartile
convenience sample
factor
units
14. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
undercoverage
factor
systematic sample
strength
15. Numerically valued attribute of a model
frequency table
placebo effect
parameter
nonresponse bias
16. The difference between the lowest and highest values in a data set
shape
pie chart
range
bias
17. Bias introduced to a sample when a large fraction of those sampled fails to respond
spread
nonresponse bias
marginal distribution
outlier
18. A treatment known to have no effect - administered so that all groups experience the same conditions
normal percentile
randomized block
placebo
z-score
19. The sequence of several components representing events that we are pretending will take place
leverage
uniform
experiment
trial
20. A distribution that's roughly flat
uniform
median
linear model
sample size
21. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
prospective study
matched
mean
random numbers
22. The square of the correlation between y and x; gives the fraction of the variability of y accounted for by the least squares linear regression on x; an overall measure of how successful the regression is in linearly relating y to x
r2
context
random assignment
undercoverage
23. An observational study in which subjects are followed to observe future outcomes
bar chart
spread
undercoverage
prospective study
24. A numerically valued attribute of a model for a population
population parameter
voluntary response bias
boxplot
leverage
25. Manipulates factor levels to create treatments - randomly assigns subjects to these treatment levels - and then compares the responses of the subject groups across treatment levels
experiment
random numbers
rescaling
representative
26. In a normal model - about 68% of values fall within 1 standard deviation of the mean - about 95% fall within 2 standard deviations of the mean - and about 99.7% fall within 3 standard deviations of the mean
68-95-99.7 rule
strength
distribution
convenience sample
27. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below
stem-and-leaf display
sample size
normal percentile
extrapolation
28. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
retrospective study
categorical variable
experimental units
voluntary response bias
29. If data consist of two or more groups that have been thrown together - it is usually best to fit different linear models to each group than to try to fit a single model to all of the data
subset
dotplot
shifting
z-score
30. The difference between the first and third quartiles
treatment
percentile
retrospective study
interquartile range
31. A numerical measure of the direction and strength of a linear association
correlation
regression line
principles of experimental design
census
32. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
random assignment
z-score
population
center
33. A list of individuals from whom the sample is drawn
sampling variability
sampling frame
z-score
stratified random sample
34. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
lurking variable
range
contingency table
trial
35. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
subset
simple random sample
mean
completely randomized design
36. The most basic situation in a simulation in which something happens at random
sample
bar chart
simulation component
experimental units
37. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
mode
direction
observational study
units
38. Distributions with more than two modes
random
convenience sample
data table
multimodal
39. The parts of a distribution that typically trail off on either side; they can be characterized as long or short
tails
distribution
outliers
strength
40. A variable whose values are compared across different treatments
response
quartile
representative
prospective study
41. A hump or local high point in the shape of the distribution of a variable; the apparent locations of these can change as the scale of a histogram is changed
context
mode
bimodal
stem-and-leaf display
42. A sampling design in which entire groups are chosen at random
distribution
cluster sample
shifting
standard normal model
43. A study based on data in which no manipulation of factors has been employed
observational study
mean
standardizing
independence
44. A sampling scheme that biases the sample in a way that gives a part of the population less representation than it has in the population
bar chart
undercoverage
census
outlier
45. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
nonresponse bias
regression to the mean
influential point
regression line
46. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
stratified random sample
population parameter
control group
simpson's paradox
47. Ideally tells who was measured - what was measured - how the data were collected - where the data were collected - and when and why the study was performed
median
multimodal
undercoverage
context
48. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
units
prospective study
simulation component
outlier
49. A sample that consists of the entire population
unimodal
lurking variable
census
convenience sample
50. An event is this if we know what outcomes could happen - but not which particular values will happen
random numbers
random
standardized value
regression to the mean