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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
experimental units
interquartile range
least squares
multistage sample
2. A study based on data in which no manipulation of factors has been employed
simpson's paradox
observational study
randomization
outliers
3. A variable whose values are compared across different treatments
shape
dotplot
response
linear model
4. The sequence of several components representing events that we are pretending will take place
context
trial
response variable
regression line
5. The parts of a distribution that typically trail off on either side; they can be characterized as long or short
tails
completely randomized design
68-95-99.7 rule
sample survey
6. When either those who could influence or evaluate the results is blinded
single-blind
placebo
marginal distribution
bimodal
7. Gives the possible values of the variable and the frequency or relative frequency of each value
median
trial
response
distribution
8. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
outlier
intercept
undercoverage
rescaling
9. The square root of the variance
population parameter
random assignment
simulation component
standard deviation
10. In a statistical display - each data value should be represented by the same amount of area
tails
area principle
regression line
leverage
11. 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
experimental units
normal probability plot
random
comparing distributions
12. Numerically valued attribute of a model
regression line
mode
response variable
parameter
13. Shows the relationship between two quantitative variables measured on the same cases
lurking variable
scatterplots
nonresponse bias
single-blind
14. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
data
sample survey
random numbers
conditional distribution
15. Bias introduced to a sample when a large fraction of those sampled fails to respond
randomized block
marginal distribution
nonresponse bias
response bias
16. Shows quantitative data values in a way that sketches the distribution of the data
stem-and-leaf display
distribution
control group
re-express data
17. 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
census
quartile
strength
random assignment
18. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
sampling frame
data
uniform
lurking variable
19. A variable that names categories (whether with words or numerals)
response variable
categorical variable
conditional distribution
quartile
20. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
unimodal
scatterplots
standardized value
marginal distribution
21. Extreme values that don't appear to belong with the rest of the data
blinding
outliers
uniform
prospective study
22. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
direction
distribution
blinding
sampling frame
23. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
placebo effect
simulation component
boxplot
re-express data
24. Shows a bar representing the count of each category in a categorical variable
randomized block
bar chart
multimodal
standard normal model
25. An event is this if we know what outcomes could happen - but not which particular values will happen
bar chart
standard normal model
regression line
random
26. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
center
parameter
marginal distribution
dotplot
27. The middle value with half of the data above and half below it
median
model
outliers
5-number summary
28. When an observed difference is too large for us to believe that is is likely to have occurred naturally
randomization
standardized value
response variable
statistically significant
29. A sample drawn by selecting individuals systematically from a sampling frame
unimodal
systematic sample
nonresponse bias
sampling frame
30. The distribution of a variable restricting the who to consider only a smaller group of individuals
undercoverage
conditional distribution
statistically significant
timeplot
31. A distribution that's roughly flat
z-score
matching
regression line
uniform
32. 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
residuals
strength
histogram
distribution
33. Summarized with the standard deviation - interquartile range - and range
census
distribution
spread
data table
34. 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
z-score
shifting
uniform
units
35. Summarized with the mean or the median
center
comparing distributions
context
z-score
36. Distributions with two modes
variable
completely randomized design
case
bimodal
37. The natural tendency of randomly drawn samples to differ
extrapolation
control group
sampling variability
median
38. An equation or formula that simplifies and represents reality
interquartile range
control group
re-express data
model
39. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
normal model
categorical variable
retrospective study
regression line
40. Places in order the effects that many re-expressions have on the data
block
ladder of powers
normal probability plot
standard normal model
41. 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
data
marginal distribution
correlation
matched
42. The entire group of individuals or instances about whom we hope to learn
standardizing
residuals
mean
population
43. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
bias
convenience sample
bar chart
rescaling
44. An observational study in which subjects are followed to observe future outcomes
multimodal
voluntary response bias
prospective study
slope
45. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters
representative
conditional distribution
response
standard normal model
46. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
least squares
factor
z-score
normal probability plot
47. Gives the possible values of the variable and the relative frequency of each value
slope
simple random sample
distribution
lurking variable
48. 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
skewed
undercoverage
block
trial
49. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
undercoverage
units
tails
outlier
50. An equation of the form y-hat = b0 + b1x
factor
median
conditional distribution
linear model