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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. A distribution that's roughly flat
uniform
standardizing
residuals
randomized block
2. A numerically valued attribute of a model for a population
systematic sample
population parameter
interquartile range
trial
3. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
symmetric
blinding
mode
normal model
4. Bias introduced to a sample when a large fraction of those sampled fails to respond
center
representative
sample
nonresponse bias
5. All experimental units have an equal chance of receiving any treatment
random assignment
completely randomized design
correlation
linear model
6. An individual about whom or which we have data
prospective study
placebo effect
standard normal model
case
7. The middle value with half of the data above and half below it
sampling variability
variance
median
convenience sample
8. Design Randomization occurring within blocks
randomized block
random numbers
matching
predicted value
9. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
re-express data
outlier
units
completely randomized design
10. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
level
strength
bias
subset
11. Extreme values that don't appear to belong with the rest of the data
variable
outliers
dotplot
multimodal
12. Found by summing all the data values and dividing by the count
principles of experimental design
systematic sample
mean
sample
13. 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
quantitative variable
standardized value
re-express data
14. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
standard normal model
case
normal probability plot
center
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
quartile
population parameter
spread
distribution
16. A positive ____ or association means that - in general - as one variable increases - so does the other; when increases in one variable generally correspond to decreases in the other - the association is negative
standard deviation
double-blind
mean
direction
17. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
trial
shape
intercept
strength
18. A numerical summary of how tightly the values are clustered around the 'center'
spread
residuals
quantitative variable
systematic sample
19. Systematically recorded information - whether numbers or labels - together with its context
cluster sample
variable
stem-and-leaf display
data
20. Control - randomize - replicate - block
principles of experimental design
shifting
level
response bias
21. 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
regression line
multimodal
mode
22. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population
mean
sample survey
z-score
population parameter
23. 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
undercoverage
census
re-express data
rescaling
24. The sum of squared deviations from the mean - divided by the count minus one
correlation
sampling variability
variance
contingency table
25. Gives the possible values of the variable and the frequency or relative frequency of each value
predicted value
multistage sample
distribution
experiment
26. Shows a bar representing the count of each category in a categorical variable
bar chart
data table
random assignment
blinding
27. The difference between the first and third quartiles
outlier
random assignment
interquartile range
least squares
28. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
sample size
strength
distribution
retrospective study
29. The natural tendency of randomly drawn samples to differ
sampling variability
leverage
statistic
blinding
30. A variable in which the numbers act as numerical values; always has units
quantitative variable
bias
z-score
principles of experimental design
31. Shows the relationship between two quantitative variables measured on the same cases
scatterplots
simulation
context
bimodal
32. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
least squares
sample size
form
model
33. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
symmetric
normal percentile
statistic
simple random sample
34. 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
r2
sample
matched
histogram
35. Sampling schemes that combine several sampling methods
multistage sample
stem-and-leaf display
mean
undercoverage
36. Summarized with the mean or the median
lurking variable
double-blind
center
68-95-99.7 rule
37. A distribution is this if it's not symmetric and one tail stretches out farther than the other
skewed
completely randomized design
experimental units
timeplot
38. A numerical measure of the direction and strength of a linear association
correlation
normal probability plot
block
tails
39. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters
parameter
standardizing
random numbers
representative
40. 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
rescaling
principles of experimental design
variance
simulation
41. A sample that consists of the entire population
census
random numbers
stratified random sample
comparing distributions
42. An arrangement of data in which each row represents a case and each column represents a variable
simple random sample
data table
z-score
random
43. Individuals on whom an experiment is performed
timeplot
regression line
experimental units
variance
44. The specific values that the experimenter chooses for a factor
outliers
level
lurking variable
units
45. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
lurking variable
intercept
outliers
matched
46. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
units
slope
unimodal
re-express data
47. A normal model with a mean of 0 and a standard deviation of 1
block
case
standard normal model
unimodal
48. 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
mode
multimodal
blinding
standard normal model
49. Holds information about the same characteristic for many cases
rescaling
regression line
r2
variable
50. When doing this - consider their shape - center - and spread
voluntary response bias
comparing distributions
units
sample survey