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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. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
regression line
statistic
experiment
confounded
2. The best defense against bias - in which each individual is given a fair - random chance of selection
sampling variability
changing center and spread
randomization
form
3. 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
outcome
quantitative variable
dotplot
r2
4. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
strength
lurking variable
ladder of powers
double-blind
5. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
leverage
matching
sample
random numbers
6. Individuals on whom an experiment is performed
placebo
convenience sample
experimental units
stem-and-leaf display
7. A normal model with a mean of 0 and a standard deviation of 1
randomization
percentile
standard normal model
sample
8. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
normal model
tails
block
strength
9. Gives the possible values of the variable and the frequency or relative frequency of each value
lurking variable
quartile
standardizing
distribution
10. A study based on data in which no manipulation of factors has been employed
extrapolation
rescaling
observational study
shifting
11. Systematically recorded information - whether numbers or labels - together with its context
data
parameter
statistic
control group
12. A numerical measure of the direction and strength of a linear association
correlation
sample
uniform
shape
13. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
factor
median
placebo
stratified random sample
14. Shows the relationship between two quantitative variables measured on the same cases
level
undercoverage
scatterplots
leverage
15. 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
tails
context
center
quartile
16. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
ladder of powers
r2
independence
68-95-99.7 rule
17. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
lurking variable
contingency table
skewed
standardizing
18. Values of this record the results of each trial with respect to what we were interested in
simulation component
response variable
independence
r2
19. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
response bias
treatment
outlier
uniform
20. A variable whose levels are controlled by the experimenter
population
linear model
factor
regression to the mean
21. A distribution is this if the two halves on either side of the center look approximately like mirror images of each other
symmetric
distribution
double-blind
r2
22. A representative subset of a population - examined in hope of learning about the population
convenience sample
sample
outlier
boxplot
23. 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
standardized value
normal probability plot
histogram
boxplot
24. A variable that names categories (whether with words or numerals)
categorical variable
randomized block
sample
unimodal
25. 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
5-number summary
mode
standardizing
response bias
26. An arrangement of data in which each row represents a case and each column represents a variable
distribution
strength
data table
frequency table
27. Doing this is equivalent to changing its units
multistage sample
independence
changing center and spread
outlier
28. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters
quartile
representative
multimodal
cluster sample
29. Extreme values that don't appear to belong with the rest of the data
outliers
frequency table
sample
representative
30. Displays data that change over time
standard deviation
timeplot
placebo
census
31. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
z-score
spread
control group
random
32. 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
lurking variable
extrapolation
randomization
skewed
33. Found by substituting the x-value in the regression equation; they're the values on the fitted line
response
predicted value
standardized value
observational study
34. Control - randomize - replicate - block
principles of experimental design
timeplot
observational study
stratified random sample
35. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
confounded
census
boxplot
retrospective study
36. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
treatment
spread
trial
cluster sample
37. Value found by subtracting the mean and dividing by the standard deviation
linear model
independence
histogram
standardized value
38. An event is this if we know what outcomes could happen - but not which particular values will happen
simple random sample
random
random assignment
response bias
39. A point that does not fit the overall pattern seen in the scatterplot
blinding
outlier
principles of experimental design
prospective study
40. The square root of the variance
census
subset
standard deviation
changing center and spread
41. A variable in which the numbers act as numerical values; always has units
intercept
changing center and spread
quantitative variable
level
42. 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
re-express data
data table
matched
quartile
43. 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
census
multimodal
experiment
trial
44. When groups of experimental units are similar - it is a good idea to gather them together into these
categorical variable
mode
block
scatterplots
45. The sequence of several components representing events that we are pretending will take place
outlier
rescaling
randomization
trial
46. Useful family of models for unimodal - symmetric distributions
statistic
blinding
normal model
completely randomized design
47. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
re-express data
percentile
statistically significant
random assignment
48. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
r2
shape
statistically significant
population parameter
49. 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
slope
rescaling
population parameter
statistic
50. Models random events by using random numbers to specify event outcomes with relative frequencies that correspond to the true real-world relative frequencies we are trying to model
prospective study
population
variance
simulation