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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 point that does not fit the overall pattern seen in the scatterplot
sample size
outliers
outlier
linear model
2. Any attempt to force a sample to resemble specified attributes of the population
matching
changing center and spread
response bias
lurking variable
3. A numerical measure of the direction and strength of a linear association
shifting
random
simulation component
correlation
4. A study based on data in which no manipulation of factors has been employed
completely randomized design
comparing distributions
representative
observational study
5. An event is this if we know what outcomes could happen - but not which particular values will happen
control group
random
quartile
distribution
6. In a statistical display - each data value should be represented by the same amount of area
area principle
sample survey
simulation component
quartile
7. A numerical summary of how tightly the values are clustered around the 'center'
quantitative variable
experimental units
boxplot
spread
8. To be valid - an experiment must assign experimental units to treatment groups at random
standard normal model
random assignment
data
predicted value
9. The best defense against bias - in which each individual is given a fair - random chance of selection
voluntary response bias
subset
rescaling
randomization
10. A distribution that's roughly flat
uniform
response
bias
range
11. Design Randomization occurring within blocks
response variable
randomized block
case
extrapolation
12. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
scatterplots
intercept
simulation component
normal probability plot
13. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
blinding
experimental units
units
data
14. Gives the possible values of the variable and the relative frequency of each value
confounded
bimodal
distribution
leverage
15. Extreme values that don't appear to belong with the rest of the data
independence
outliers
parameter
r2
16. A distribution is this if it's not symmetric and one tail stretches out farther than the other
simple random sample
tails
skewed
mode
17. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
response variable
shape
least squares
randomization
18. When both those who could influence and evaluate the results are blinded
units
double-blind
undercoverage
outcome
19. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
standardized value
quantitative variable
stem-and-leaf display
regression to the mean
20. The ____ we care about most is straight
experiment
bar chart
quantitative variable
form
21. A distribution is this if the two halves on either side of the center look approximately like mirror images of each other
multimodal
symmetric
normal model
variable
22. The difference between the first and third quartiles
units
interquartile range
68-95-99.7 rule
independence
23. A sample drawn by selecting individuals systematically from a sampling frame
5-number summary
retrospective study
systematic sample
residuals
24. A variable whose values are compared across different treatments
subset
quartile
response
sample
25. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
frequency table
retrospective study
mode
direction
26. A normal model with a mean of 0 and a standard deviation of 1
marginal distribution
normal percentile
placebo effect
standard normal model
27. Places in order the effects that many re-expressions have on the data
dotplot
data
ladder of powers
5-number summary
28. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
randomization
pie chart
interquartile range
re-express data
29. Displays data that change over time
stratified random sample
timeplot
response bias
single-blind
30. Value found by subtracting the mean and dividing by the standard deviation
68-95-99.7 rule
standardized value
normal percentile
shifting
31. Found by summing all the data values and dividing by the count
simulation
voluntary response bias
outlier
mean
32. All experimental units have an equal chance of receiving any treatment
simulation
sample
mode
completely randomized design
33. When an observed difference is too large for us to believe that is is likely to have occurred naturally
statistically significant
single-blind
matching
normal probability plot
34. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population
random numbers
histogram
sample survey
center
35. 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
trial
subset
response bias
units
36. 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
normal percentile
context
observational study
extrapolation
37. 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
stratified random sample
categorical variable
pie chart
38. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
confounded
random numbers
unimodal
treatment
39. The entire group of individuals or instances about whom we hope to learn
experiment
population
random
percentile
40. 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
data table
experiment
independence
confounded
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
factor
simulation
stratified random sample
sample survey
42. Shows quantitative data values in a way that sketches the distribution of the data
stem-and-leaf display
sample size
normal probability plot
skewed
43. When either those who could influence or evaluate the results is blinded
stem-and-leaf display
multimodal
simple random sample
single-blind
44. The most basic situation in a simulation in which something happens at random
range
blinding
uniform
simulation component
45. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters
representative
quantitative variable
center
lurking variable
46. Consists of the individuals who are conveniently available
convenience sample
dotplot
timeplot
pie chart
47. When averages are taken across different groups - they can appear to contradict the overall averages
48. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
distribution
r2
residuals
least squares
49. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
population parameter
outlier
independence
center
50. The ith ___ is the number that falls above i% of the data
ladder of powers
percentile
least squares
pie chart