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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. A distribution is this if the two halves on either side of the center look approximately like mirror images of each other
bar chart
comparing distributions
simpson's paradox
symmetric
2. The lower of this is the value with a quarter of the data below it; the upper of this has a quarter of the data above it
correlation
simulation
sampling frame
quartile
3. The natural tendency of randomly drawn samples to differ
population parameter
statistic
sampling variability
randomization
4. The most basic situation in a simulation in which something happens at random
comparing distributions
correlation
double-blind
simulation component
5. Displays counts and - sometimes - percentages of individuals falling into named categories on two or more variables; categorizes the individuals on all variables at once - to reveal possible patterns in one variable that may be contingent on the cate
block
marginal distribution
contingency table
matching
6. Gives the possible values of the variable and the relative frequency of each value
distribution
principles of experimental design
matched
quartile
7. An event is this if we know what outcomes could happen - but not which particular values will happen
normal percentile
skewed
undercoverage
random
8. The sum of squared deviations from the mean - divided by the count minus one
intercept
bias
variance
subset
9. Gives the possible values of the variable and the frequency or relative frequency of each value
sampling frame
standard normal model
frequency table
distribution
10. When omitting a point from the data results in a very different regression model - the point is an ____
standardized value
lurking variable
center
influential point
11. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
symmetric
completely randomized design
census
confounded
12. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
multimodal
comparing distributions
distribution
pie chart
13. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
regression to the mean
variance
population parameter
independence
14. Value found by subtracting the mean and dividing by the standard deviation
treatment
trial
response
standardized value
15. Bias introduced to a sample when a large fraction of those sampled fails to respond
marginal distribution
r2
mean
nonresponse bias
16. In a retrospective or prospective study Subjects who are similar in ways not under study may be ____ and then compared with each other on the variables of interest
voluntary response bias
matched
marginal distribution
outliers
17. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below
normal percentile
marginal distribution
shifting
sample survey
18. The square root of the variance
standard deviation
prospective study
normal percentile
contingency table
19. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
multimodal
changing center and spread
bias
census
20. Summarized with the mean or the median
center
scatterplots
random
z-score
21. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
stratified random sample
sampling variability
multistage sample
lurking variable
22. The best defense against bias - in which each individual is given a fair - random chance of selection
matching
randomization
random assignment
comparing distributions
23. A distribution is this if it's not symmetric and one tail stretches out farther than the other
extrapolation
skewed
randomized block
stratified random sample
24. When either those who could influence or evaluate the results is blinded
single-blind
histogram
sample survey
retrospective study
25. The ith ___ is the number that falls above i% of the data
placebo effect
prospective study
percentile
marginal distribution
26. Holds information about the same characteristic for many cases
nonresponse bias
marginal distribution
variable
sample survey
27. A normal model with a mean of 0 and a standard deviation of 1
randomization
standard normal model
stem-and-leaf display
center
28. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
random assignment
categorical variable
distribution
shape
29. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
least squares
multimodal
units
unimodal
30. 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
subset
strength
mode
lurking variable
31. A variable in which the numbers act as numerical values; always has units
statistic
quartile
quantitative variable
simulation
32. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
blinding
outcome
shifting
pie chart
33. The sequence of several components representing events that we are pretending will take place
level
boxplot
trial
data
34. Numerically valued attribute of a model
parameter
convenience sample
placebo effect
standardized value
35. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
sample size
systematic sample
treatment
residuals
36. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
standard normal model
bimodal
outlier
comparing distributions
37. When both those who could influence and evaluate the results are blinded
principles of experimental design
double-blind
outliers
bimodal
38. An arrangement of data in which each row represents a case and each column represents a variable
convenience sample
outliers
standardized value
data table
39. Distributions with more than two modes
boxplot
quartile
multimodal
bimodal
40. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters
sampling variability
factor
census
representative
41. A numerical summary of how tightly the values are clustered around the 'center'
spread
marginal distribution
distribution
stem-and-leaf display
42. All experimental units have an equal chance of receiving any treatment
tails
completely randomized design
sample survey
observational study
43. Summarized with the standard deviation - interquartile range - and range
sample survey
bimodal
spread
5-number summary
44. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
tails
sampling variability
intercept
correlation
45. The entire group of individuals or instances about whom we hope to learn
statistic
scatterplots
population
median
46. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
cluster sample
strength
model
sample
47. Anything in a survey design that influences response
pie chart
regression line
response bias
lurking variable
48. When an observed difference is too large for us to believe that is is likely to have occurred naturally
influential point
timeplot
statistically significant
trial
49. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
standardized value
quantitative variable
lurking variable
variable
50. A distribution that's roughly flat
case
uniform
random
subset