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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. 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
simple random sample
subset
z-score
retrospective study
2. The entire group of individuals or instances about whom we hope to learn
standard normal model
population
undercoverage
subset
3. A list of individuals from whom the sample is drawn
bimodal
rescaling
subset
sampling frame
4. 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
marginal distribution
case
linear model
lurking variable
5. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
trial
variance
placebo
5-number summary
6. A representative subset of a population - examined in hope of learning about the population
observational study
sample
variable
prospective study
7. Found by substituting the x-value in the regression equation; they're the values on the fitted line
predicted value
context
matching
center
8. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
model
range
standardizing
sampling frame
9. Summarized with the standard deviation - interquartile range - and range
scatterplots
representative
factor
spread
10. Shows a bar representing the count of each category in a categorical variable
simple random sample
bar chart
single-blind
simulation component
11. Found by summing all the data values and dividing by the count
tails
observational study
slope
mean
12. A point that does not fit the overall pattern seen in the scatterplot
outlier
dotplot
standard normal model
randomized block
13. An arrangement of data in which each row represents a case and each column represents a variable
rescaling
slope
data table
placebo
14. Displays data that change over time
timeplot
sample size
sample survey
spread
15. Summarized with the mean or the median
systematic sample
data
5-number summary
center
16. Extreme values that don't appear to belong with the rest of the data
completely randomized design
interquartile range
outliers
data table
17. Sampling schemes that combine several sampling methods
multistage sample
randomization
re-express data
outlier
18. 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
confounded
r2
extrapolation
sample survey
19. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
blinding
outcome
standardized value
form
20. The parts of a distribution that typically trail off on either side; they can be characterized as long or short
population
tails
frequency table
sample
21. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population
trial
simulation
sample survey
principles of experimental design
22. 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
prospective study
simpson's paradox
context
undercoverage
23. The sequence of several components representing events that we are pretending will take place
center
ladder of powers
trial
response bias
24. 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
outlier
ladder of powers
quartile
shape
25. The distribution of a variable restricting the who to consider only a smaller group of individuals
voluntary response bias
multistage sample
conditional distribution
matching
26. 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
percentile
confounded
placebo effect
mode
27. 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
outcome
experiment
variable
bar chart
28. All experimental units have an equal chance of receiving any treatment
matching
independence
completely randomized design
multistage sample
29. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
prospective study
interquartile range
unimodal
residuals
30. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
independence
unimodal
least squares
direction
31. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
matching
data
simulation component
simple random sample
32. When both those who could influence and evaluate the results are blinded
random assignment
dotplot
double-blind
direction
33. The best defense against bias - in which each individual is given a fair - random chance of selection
factor
randomization
standard normal model
independence
34. A sampling design in which entire groups are chosen at random
histogram
cluster sample
randomization
residuals
35. Data points whose x-values are far from the mean of x are said to exert ____ on a linear model; with high enough ____ - residuals can appear to be deceptively small
observational study
leverage
influential point
outlier
36. In a statistical display - each data value should be represented by the same amount of area
standard normal model
area principle
leverage
population parameter
37. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
multistage sample
confounded
boxplot
observational study
38. Systematically recorded information - whether numbers or labels - together with its context
normal percentile
completely randomized design
sampling variability
data
39. A distribution that's roughly flat
contingency table
experiment
retrospective study
uniform
40. A numerically valued attribute of a model for a population
z-score
population parameter
case
placebo
41. 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
observational study
predicted value
standardizing
42. The ____ we care about most is straight
voluntary response bias
factor
form
variance
43. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
simple random sample
level
voluntary response bias
stratified random sample
44. The difference between the first and third quartiles
residuals
interquartile range
sampling frame
census
45. When doing this - consider their shape - center - and spread
units
r2
comparing distributions
multistage sample
46. The square root of the variance
normal model
re-express data
standard deviation
linear model
47. The middle value with half of the data above and half below it
median
model
symmetric
pie chart
48. An event is this if we know what outcomes could happen - but not which particular values will happen
shifting
population
random
outliers
49. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
blinding
cluster sample
shape
completely randomized design
50. A variable whose levels are controlled by the experimenter
outlier
experimental units
factor
response