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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. 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
confounded
context
experiment
matched
2. 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
scatterplots
sampling variability
sample
3. Gives a value in 'y-units per x-unit'; changes of one unit in x are associated with changes of b1 units in predicted values of y
confounded
slope
marginal distribution
leverage
4. Values of this record the results of each trial with respect to what we were interested in
placebo
leverage
response variable
nonresponse bias
5. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
least squares
area principle
boxplot
rescaling
6. When either those who could influence or evaluate the results is blinded
strength
single-blind
experiment
systematic sample
7. 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
bar chart
quartile
experiment
regression to the mean
8. Doing this is equivalent to changing its units
multistage sample
changing center and spread
observational study
mean
9. A sample drawn by selecting individuals systematically from a sampling frame
block
quartile
systematic sample
matching
10. A distribution that's roughly flat
independence
uniform
marginal distribution
control group
11. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
sample survey
census
undercoverage
confounded
12. Anything in a survey design that influences response
r2
conditional distribution
sample size
response bias
13. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
regression line
unimodal
parameter
skewed
14. An equation of the form y-hat = b0 + b1x
block
linear model
mean
independence
15. Numerically valued attribute of a model
parameter
voluntary response bias
bimodal
sample size
16. An event is this if we know what outcomes could happen - but not which particular values will happen
context
simple random sample
random
pie chart
17. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
independence
regression to the mean
systematic sample
standardized value
18. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
mode
stratified random sample
intercept
quantitative variable
19. The number of individuals in a sample
multistage sample
range
sample size
cluster sample
20. A distribution is this if it's not symmetric and one tail stretches out farther than the other
bimodal
skewed
control group
prospective study
21. Extreme values that don't appear to belong with the rest of the data
center
shifting
outliers
systematic sample
22. Graphs a dot for each case against a single axis
categorical variable
dotplot
mean
observational study
23. 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
least squares
mode
quartile
systematic sample
24. Summarized with the mean or the median
extrapolation
statistically significant
experiment
center
25. When an observed difference is too large for us to believe that is is likely to have occurred naturally
bias
statistically significant
simulation component
randomized block
26. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
standard normal model
outliers
variance
voluntary response bias
27. When groups of experimental units are similar - it is a good idea to gather them together into these
cluster sample
undercoverage
lurking variable
block
28. 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
parameter
quantitative variable
data table
29. An observational study in which subjects are followed to observe future outcomes
statistic
unimodal
response variable
prospective study
30. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
independence
outlier
strength
quantitative variable
31. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
timeplot
mode
random numbers
outlier
32. Individuals on whom an experiment is performed
outcome
experimental units
statistically significant
sample
33. The distribution of a variable restricting the who to consider only a smaller group of individuals
conditional distribution
trial
median
histogram
34. Gives the possible values of the variable and the relative frequency of each value
representative
distribution
multistage sample
normal probability plot
35. Found by substituting the x-value in the regression equation; they're the values on the fitted line
outliers
predicted value
normal percentile
nonresponse bias
36. A numerical measure of the direction and strength of a linear association
direction
double-blind
correlation
census
37. Summarized with the standard deviation - interquartile range - and range
quantitative variable
spread
control group
center
38. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
strength
block
bias
slope
39. Control - randomize - replicate - block
placebo effect
principles of experimental design
control group
variance
40. When averages are taken across different groups - they can appear to contradict the overall averages
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41. Displays data that change over time
block
timeplot
nonresponse bias
skewed
42. A point that does not fit the overall pattern seen in the scatterplot
linear model
multimodal
outlier
form
43. Sampling schemes that combine several sampling methods
contingency table
random numbers
confounded
multistage sample
44. Shows quantitative data values in a way that sketches the distribution of the data
stem-and-leaf display
case
timeplot
voluntary response bias
45. Shows a bar representing the count of each category in a categorical variable
bar chart
influential point
context
mean
46. 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
r2
subset
principles of experimental design
matching
47. Design Randomization occurring within blocks
representative
experiment
outliers
randomized block
48. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
units
shape
variance
lurking variable
49. Shows the relationship between two quantitative variables measured on the same cases
variance
scatterplots
units
matched
50. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
ladder of powers
pie chart
quartile
sample size