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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 numerical measure of the direction and strength of a linear association
systematic sample
residuals
intercept
correlation
2. The most basic situation in a simulation in which something happens at random
simulation component
mean
dotplot
variance
3. In a statistical display - each data value should be represented by the same amount of area
rescaling
area principle
block
simpson's paradox
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
scatterplots
frequency table
normal probability plot
marginal distribution
5. 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
bimodal
quantitative variable
sample survey
undercoverage
6. The sum of squared deviations from the mean - divided by the count minus one
slope
interquartile range
stratified random sample
variance
7. When averages are taken across different groups - they can appear to contradict the overall averages
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8. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
correlation
simpson's paradox
5-number summary
placebo
9. Design Randomization occurring within blocks
random numbers
bias
single-blind
randomized block
10. All experimental units have an equal chance of receiving any treatment
lurking variable
completely randomized design
mean
normal model
11. 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
outlier
context
normal percentile
confounded
12. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
unimodal
percentile
systematic sample
boxplot
13. Any attempt to force a sample to resemble specified attributes of the population
standardized value
matching
median
outcome
14. A variable that names categories (whether with words or numerals)
sample size
categorical variable
dotplot
random assignment
15. 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
simulation
sample
quantitative variable
16. Consists of the individuals who are conveniently available
control group
convenience sample
distribution
matched
17. Gives the possible values of the variable and the relative frequency of each value
tails
trial
distribution
observational study
18. 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
treatment
mode
center
correlation
19. Systematically recorded information - whether numbers or labels - together with its context
placebo
normal probability plot
block
data
20. A variable in which the numbers act as numerical values; always has units
standard deviation
tails
lurking variable
quantitative variable
21. Anything in a survey design that influences response
response bias
regression to the mean
changing center and spread
statistically significant
22. A representative subset of a population - examined in hope of learning about the population
single-blind
area principle
shifting
sample
23. The sequence of several components representing events that we are pretending will take place
data
undercoverage
confounded
trial
24. 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
changing center and spread
68-95-99.7 rule
standardized value
direction
25. Graphs a dot for each case against a single axis
retrospective study
independence
dotplot
rescaling
26. An event is this if we know what outcomes could happen - but not which particular values will happen
sample survey
random
mode
stem-and-leaf display
27. A point that does not fit the overall pattern seen in the scatterplot
outlier
blinding
rescaling
percentile
28. The entire group of individuals or instances about whom we hope to learn
timeplot
skewed
population
sample
29. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
lurking variable
median
confounded
parameter
30. Summarized with the standard deviation - interquartile range - and range
comparing distributions
spread
normal model
double-blind
31. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
regression to the mean
subset
shape
simulation
32. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population
random
nonresponse bias
sample survey
unimodal
33. 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
subset
placebo
sampling frame
tails
34. When groups of experimental units are similar - it is a good idea to gather them together into these
block
changing center and spread
boxplot
confounded
35. An observational study in which subjects are followed to observe future outcomes
sample size
histogram
prospective study
center
36. 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
predicted value
experiment
r2
matching
37. The difference between the lowest and highest values in a data set
population
marginal distribution
range
voluntary response bias
38. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
randomized block
treatment
parameter
voluntary response bias
39. Found by summing all the data values and dividing by the count
mean
bias
treatment
random assignment
40. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
regression to the mean
simulation
range
marginal distribution
41. An individual about whom or which we have data
case
random assignment
mode
r2
42. Sampling schemes that combine several sampling methods
multistage sample
context
distribution
population parameter
43. 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
extrapolation
pie chart
predicted value
44. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
normal percentile
z-score
simple random sample
outliers
45. An equation or formula that simplifies and represents reality
sample survey
model
mean
context
46. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
context
control group
factor
units
47. When either those who could influence or evaluate the results is blinded
single-blind
block
representative
normal probability plot
48. A distribution is this if the two halves on either side of the center look approximately like mirror images of each other
sampling variability
lurking variable
symmetric
convenience sample
49. Distributions with two modes
bimodal
categorical variable
distribution
case
50. Displays data that change over time
timeplot
normal percentile
mean
placebo effect