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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. Design Randomization occurring within blocks
r2
re-express data
randomized block
prospective study
2. 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
subset
standardizing
r2
bar chart
3. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
statistic
placebo effect
variable
outlier
4. 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
cluster sample
pie chart
slope
control group
5. 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
principles of experimental design
mode
bias
convenience sample
6. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
voluntary response bias
independence
marginal distribution
histogram
7. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
tails
normal probability plot
level
regression to the mean
8. The parts of a distribution that typically trail off on either side; they can be characterized as long or short
bias
conditional distribution
tails
double-blind
9. Shows the relationship between two quantitative variables measured on the same cases
shifting
scatterplots
simple random sample
r2
10. A sample drawn by selecting individuals systematically from a sampling frame
categorical variable
systematic sample
center
changing center and spread
11. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
retrospective study
strength
bimodal
center
12. An equation of the form y-hat = b0 + b1x
undercoverage
context
multistage sample
linear model
13. Sampling schemes that combine several sampling methods
symmetric
median
variable
multistage sample
14. Bias introduced to a sample when a large fraction of those sampled fails to respond
skewed
nonresponse bias
lurking variable
bimodal
15. The specific values that the experimenter chooses for a factor
completely randomized design
level
convenience sample
shifting
16. The difference between the first and third quartiles
sample
influential point
interquartile range
extrapolation
17. A variable whose levels are controlled by the experimenter
comparing distributions
sampling frame
factor
matching
18. Extreme values that don't appear to belong with the rest of the data
outliers
changing center and spread
stem-and-leaf display
sampling frame
19. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
z-score
sample size
sample
normal model
20. When doing this - consider their shape - center - and spread
stratified random sample
comparing distributions
residuals
strength
21. Distributions with more than two modes
treatment
multimodal
experiment
sample size
22. The natural tendency of randomly drawn samples to differ
normal percentile
sampling variability
symmetric
normal probability plot
23. An event is this if we know what outcomes could happen - but not which particular values will happen
census
residuals
random
stratified random sample
24. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
ladder of powers
matching
control group
units
25. Graphs a dot for each case against a single axis
dotplot
experimental units
skewed
sample
26. A point that does not fit the overall pattern seen in the scatterplot
outlier
timeplot
voluntary response bias
matched
27. Anything in a survey design that influences response
completely randomized design
response bias
retrospective study
model
28. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
sample size
regression line
matching
case
29. An equation or formula that simplifies and represents reality
principles of experimental design
model
retrospective study
blinding
30. The most basic situation in a simulation in which something happens at random
simulation component
outlier
ladder of powers
comparing distributions
31. A distribution is this if the two halves on either side of the center look approximately like mirror images of each other
rescaling
standardized value
symmetric
matched
32. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
correlation
influential point
boxplot
parameter
33. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
completely randomized design
histogram
pie chart
center
34. The sequence of several components representing events that we are pretending will take place
outlier
predicted value
trial
simple random sample
35. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
interquartile range
bias
control group
outlier
36. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
placebo
lurking variable
residuals
ladder of powers
37. A sample that consists of the entire population
multimodal
single-blind
lurking variable
census
38. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
population parameter
data
matched
least squares
39. 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
bar chart
placebo effect
experimental units
subset
40. Found by summing all the data values and dividing by the count
correlation
simulation component
mean
single-blind
41. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
re-express data
shape
data
center
42. A numerical measure of the direction and strength of a linear association
simulation
block
center
correlation
43. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
matching
case
control group
simple random sample
44. Any attempt to force a sample to resemble specified attributes of the population
matching
conditional distribution
statistic
re-express data
45. A distribution that's roughly flat
regression line
5-number summary
uniform
form
46. The square root of the variance
re-express data
least squares
median
standard deviation
47. Although linear models provide an easy way to predict values of y for a given value of x - it is unsafe to predict for values of x far from the ones used to find the linear model equation; predictions should not be trusted
simulation component
extrapolation
outlier
spread
48. Found by substituting the x-value in the regression equation; they're the values on the fitted line
variance
uniform
predicted value
histogram
49. Uses adjacent bars to show the distribution of vales in a quantitative variable; each bar represents the frequency (or relative frequency) of values falling in an interval of values
double-blind
histogram
response bias
shifting
50. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant
confounded
linear model
direction
rescaling