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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 most basic situation in a simulation in which something happens at random
simulation component
normal model
bias
r2
2. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
block
bar chart
independence
confounded
3. Summarized with the standard deviation - interquartile range - and range
frequency table
boxplot
residuals
spread
4. All experimental units have an equal chance of receiving any treatment
completely randomized design
form
sample
extrapolation
5. Control - randomize - replicate - block
response bias
principles of experimental design
uniform
random numbers
6. A variable whose values are compared across different treatments
response
sampling frame
statistic
shape
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
factor
normal probability plot
context
distribution
8. 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
outliers
placebo
bar chart
9. Extreme values that don't appear to belong with the rest of the data
linear model
bias
confounded
outliers
10. 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
data table
quartile
stratified random sample
variance
11. Value calculated from data to summarize aspects of the data
bias
response bias
statistic
control group
12. Systematically recorded information - whether numbers or labels - together with its context
experimental units
data
statistically significant
standardized value
13. A sample that consists of the entire population
census
68-95-99.7 rule
changing center and spread
prospective study
14. 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
strength
mode
interquartile range
15. Found by summing all the data values and dividing by the count
units
simulation
histogram
mean
16. The best defense against bias - in which each individual is given a fair - random chance of selection
randomization
rescaling
distribution
range
17. 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
r2
spread
matched
case
18. When doing this - consider their shape - center - and spread
center
placebo
bimodal
comparing distributions
19. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
mode
population parameter
experimental units
standardizing
20. A sample drawn by selecting individuals systematically from a sampling frame
r2
outlier
completely randomized design
systematic sample
21. A numerically valued attribute of a model for a population
population parameter
lurking variable
prospective study
confounded
22. The square root of the variance
principles of experimental design
population parameter
standard deviation
variance
23. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
lurking variable
control group
multimodal
block
24. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
response variable
level
standard normal model
blinding
25. Bias introduced to a sample when a large fraction of those sampled fails to respond
center
bar chart
matched
nonresponse bias
26. Anything in a survey design that influences response
bar chart
variance
independence
response bias
27. The natural tendency of randomly drawn samples to differ
sampling variability
changing center and spread
model
unimodal
28. To be valid - an experiment must assign experimental units to treatment groups at random
nonresponse bias
random assignment
simpson's paradox
quantitative variable
29. Summarized with the mean or the median
principles of experimental design
center
contingency table
completely randomized design
30. Distributions with more than two modes
systematic sample
strength
statistic
multimodal
31. 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
68-95-99.7 rule
sampling frame
least squares
shifting
32. When an observed difference is too large for us to believe that is is likely to have occurred naturally
boxplot
sample
census
statistically significant
33. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
multimodal
double-blind
population
residuals
34. Doing this is equivalent to changing its units
randomized block
nonresponse bias
statistically significant
changing center and spread
35. 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
5-number summary
marginal distribution
uniform
slope
36. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
population parameter
case
unimodal
quartile
37. 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
placebo effect
variance
predicted value
undercoverage
38. The ____ we care about most is straight
variance
spread
form
center
39. 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
case
subset
slope
unimodal
40. A normal model with a mean of 0 and a standard deviation of 1
standard normal model
single-blind
experiment
sampling variability
41. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
z-score
outliers
center
residuals
42. A numerical summary of how tightly the values are clustered around the 'center'
spread
data table
outlier
multistage sample
43. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
response variable
lurking variable
spread
least squares
44. The parts of a distribution that typically trail off on either side; they can be characterized as long or short
principles of experimental design
independence
parameter
tails
45. 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
normal model
distribution
placebo effect
46. When groups of experimental units are similar - it is a good idea to gather them together into these
block
intercept
5-number summary
double-blind
47. An equation or formula that simplifies and represents reality
sampling frame
shape
residuals
model
48. A distribution is this if the two halves on either side of the center look approximately like mirror images of each other
matching
symmetric
stem-and-leaf display
sample survey
49. An arrangement of data in which each row represents a case and each column represents a variable
random
68-95-99.7 rule
data table
randomized block
50. A numerical measure of the direction and strength of a linear association
correlation
mode
prospective study
direction