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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. The difference between the first and third quartiles
confounded
outlier
interquartile range
factor
2. The square root of the variance
data
center
normal percentile
standard deviation
3. Extreme values that don't appear to belong with the rest of the data
5-number summary
blinding
dotplot
outliers
4. A numerical summary of how tightly the values are clustered around the 'center'
spread
normal probability plot
level
randomized block
5. When averages are taken across different groups - they can appear to contradict the overall averages
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6. A list of individuals from whom the sample is drawn
confounded
sampling variability
sampling frame
normal model
7. 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
ladder of powers
simulation
representative
context
8. 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
interquartile range
shifting
unimodal
9. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population
sample survey
random assignment
multistage sample
changing center and spread
10. Individuals on whom an experiment is performed
experimental units
regression to the mean
treatment
convenience sample
11. Gives the possible values of the variable and the frequency or relative frequency of each value
distribution
leverage
changing center and spread
block
12. A numerically valued attribute of a model for a population
lurking variable
cluster sample
population parameter
convenience sample
13. A treatment known to have no effect - administered so that all groups experience the same conditions
placebo
least squares
cluster sample
categorical variable
14. A variable in which the numbers act as numerical values; always has units
skewed
independence
quantitative variable
range
15. Sampling schemes that combine several sampling methods
completely randomized design
percentile
multistage sample
68-95-99.7 rule
16. Any attempt to force a sample to resemble specified attributes of the population
tails
matching
shifting
area principle
17. 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
model
statistic
normal probability plot
18. Design Randomization occurring within blocks
regression line
randomized block
data
random assignment
19. The middle value with half of the data above and half below it
representative
mode
lurking variable
median
20. Value calculated from data to summarize aspects of the data
experimental units
principles of experimental design
statistic
regression line
21. A sample that consists of the entire population
mean
census
retrospective study
random
22. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
block
shape
timeplot
population
23. Gives the possible values of the variable and the relative frequency of each value
outlier
residuals
distribution
case
24. The natural tendency of randomly drawn samples to differ
standard deviation
strength
comparing distributions
sampling variability
25. 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
timeplot
mean
context
contingency table
26. Places in order the effects that many re-expressions have on the data
outlier
ladder of powers
direction
randomization
27. 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
convenience sample
pie chart
undercoverage
standard normal model
28. The distribution of a variable restricting the who to consider only a smaller group of individuals
matching
marginal distribution
conditional distribution
matched
29. An event is this if we know what outcomes could happen - but not which particular values will happen
block
parameter
predicted value
random
30. The ____ we care about most is straight
stratified random sample
symmetric
form
case
31. Holds information about the same characteristic for many cases
pie chart
experimental units
variable
observational study
32. All experimental units have an equal chance of receiving any treatment
completely randomized design
spread
spread
parameter
33. Uses adjacent bars to show the distribution of vales in a quantitative variable; each bar represents the frequency (or relative frequency) of values falling in an interval of values
distribution
histogram
interquartile range
subset
34. Found by summing all the data values and dividing by the count
sample
contingency table
spread
mean
35. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
simple random sample
re-express data
extrapolation
response bias
36. Found by substituting the x-value in the regression equation; they're the values on the fitted line
comparing distributions
predicted value
level
data table
37. When omitting a point from the data results in a very different regression model - the point is an ____
unimodal
influential point
strength
convenience sample
38. A variable whose values are compared across different treatments
bimodal
regression line
response
influential point
39. A point that does not fit the overall pattern seen in the scatterplot
cluster sample
uniform
marginal distribution
outlier
40. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
conditional distribution
predicted value
68-95-99.7 rule
outlier
41. Control - randomize - replicate - block
skewed
distribution
principles of experimental design
undercoverage
42. Although linear models provide an easy way to predict values of y for a given value of x - it is unsafe to predict for values of x far from the ones used to find the linear model equation; predictions should not be trusted
simulation component
extrapolation
matching
center
43. Gives a value in 'y-units per x-unit'; changes of one unit in x are associated with changes of b1 units in predicted values of y
distribution
bimodal
slope
multistage sample
44. An individual result of a component of a simulation
random assignment
outcome
normal probability plot
conditional distribution
45. The most basic situation in a simulation in which something happens at random
principles of experimental design
simulation component
double-blind
marginal distribution
46. 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
outlier
68-95-99.7 rule
leverage
ladder of powers
47. 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
range
r2
systematic sample
statistically significant
48. Useful family of models for unimodal - symmetric distributions
influential point
normal model
area principle
multistage sample
49. When either those who could influence or evaluate the results is blinded
regression line
representative
single-blind
simulation
50. A variable that names categories (whether with words or numerals)
least squares
categorical variable
lurking variable
observational study