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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. 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
simulation
regression to the mean
randomized block
sampling variability
2. A variable whose levels are controlled by the experimenter
factor
linear model
statistic
population parameter
3. Useful family of models for unimodal - symmetric distributions
form
timeplot
normal model
distribution
4. An observational study in which subjects are followed to observe future outcomes
blinding
prospective study
strength
trial
5. A sample drawn by selecting individuals systematically from a sampling frame
systematic sample
spread
randomized block
normal percentile
6. Found by summing all the data values and dividing by the count
block
center
mean
normal model
7. An individual result of a component of a simulation
simpson's paradox
range
outcome
5-number summary
8. Numerically valued attribute of a model
lurking variable
parameter
placebo
outliers
9. A normal model with a mean of 0 and a standard deviation of 1
placebo
standard normal model
nonresponse bias
spread
10. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
control group
strength
trial
influential point
11. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
outlier
systematic sample
nonresponse bias
bimodal
12. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
outcome
lurking variable
randomization
random
13. 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
extrapolation
frequency table
context
sample survey
14. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
units
block
model
68-95-99.7 rule
15. The square root of the variance
standard deviation
timeplot
units
multimodal
16. Adding a constant to each data value adds the same constant to the mean - the median - and the quartiles - but does not change the standard deviation or IQR
shifting
confounded
normal percentile
random assignment
17. Extreme values that don't appear to belong with the rest of the data
standard normal model
voluntary response bias
randomized block
outliers
18. 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
mean
sampling variability
variance
19. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
boxplot
scatterplots
statistic
normal probability plot
20. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters
representative
spread
standard deviation
area principle
21. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
direction
changing center and spread
least squares
outlier
22. A sampling design in which entire groups are chosen at random
contingency table
symmetric
cluster sample
quantitative variable
23. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
experimental units
randomization
unimodal
voluntary response bias
24. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
double-blind
strength
interquartile range
confounded
25. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
random numbers
experimental units
marginal distribution
case
26. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
blinding
predicted value
matching
standardized value
27. Control - randomize - replicate - block
dotplot
independence
principles of experimental design
mode
28. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
experiment
control group
5-number summary
simpson's paradox
29. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
r2
shape
response variable
double-blind
30. Value calculated from data to summarize aspects of the data
linear model
statistic
block
population
31. The parts of a distribution that typically trail off on either side; they can be characterized as long or short
timeplot
data table
randomized block
tails
32. A study based on data in which no manipulation of factors has been employed
shape
rescaling
observational study
sampling variability
33. The specific values that the experimenter chooses for a factor
level
shifting
simpson's paradox
bias
34. A numerical summary of how tightly the values are clustered around the 'center'
histogram
block
dotplot
spread
35. A numerical measure of the direction and strength of a linear association
normal model
spread
conditional distribution
correlation
36. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
retrospective study
quantitative variable
rescaling
intercept
37. The distribution of either variable alone in a contingency table; the counts or percentages are the totals found in the margins (last row or column) of the table
case
normal probability plot
leverage
marginal distribution
38. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
stratified random sample
confounded
bar chart
unimodal
39. An event is this if we know what outcomes could happen - but not which particular values will happen
response bias
predicted value
independence
random
40. In a statistical display - each data value should be represented by the same amount of area
area principle
histogram
statistic
parameter
41. A treatment known to have no effect - administered so that all groups experience the same conditions
regression to the mean
random assignment
placebo
marginal distribution
42. A display to help assess whether a distribution of data is approximately normal; if it is nearly straight - the data satisfy the nearly normal condition
bimodal
census
leverage
normal probability plot
43. Consists of the individuals who are conveniently available
convenience sample
block
observational study
median
44. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
random numbers
random
re-express data
outliers
45. 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
units
simpson's paradox
experimental units
subset
46. When groups of experimental units are similar - it is a good idea to gather them together into these
block
least squares
random numbers
model
47. An arrangement of data in which each row represents a case and each column represents a variable
data table
5-number summary
outlier
correlation
48. An equation of the form y-hat = b0 + b1x
linear model
case
distribution
level
49. Doing this is equivalent to changing its units
changing center and spread
bar chart
percentile
5-number summary
50. The entire group of individuals or instances about whom we hope to learn
sampling frame
population
histogram
case