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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. 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
standardized value
leverage
shifting
double-blind
2. 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
68-95-99.7 rule
quartile
retrospective study
randomization
3. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
outlier
leverage
double-blind
experimental units
4. The difference between the lowest and highest values in a data set
variable
leverage
range
observational study
5. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
strength
outlier
intercept
data table
6. Numerically valued attribute of a model
parameter
trial
independence
placebo effect
7. Summarized with the standard deviation - interquartile range - and range
r2
spread
conditional distribution
center
8. Displays data that change over time
shape
timeplot
simulation
r2
9. In a retrospective or prospective study Subjects who are similar in ways not under study may be ____ and then compared with each other on the variables of interest
extrapolation
regression to the mean
linear model
matched
10. The ____ we care about most is straight
multistage sample
correlation
form
response
11. The entire group of individuals or instances about whom we hope to learn
double-blind
population
standardized value
simulation component
12. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
retrospective study
median
random numbers
statistic
13. A representative subset of a population - examined in hope of learning about the population
interquartile range
sampling variability
least squares
sample
14. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
context
standardized value
regression line
trial
15. Doing this is equivalent to changing its units
variance
changing center and spread
predicted value
direction
16. When doing this - consider their shape - center - and spread
sample size
multimodal
comparing distributions
experimental units
17. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
factor
block
standardized value
control group
18. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
simple random sample
completely randomized design
experiment
experimental units
19. An event is this if we know what outcomes could happen - but not which particular values will happen
random
intercept
simulation component
outlier
20. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below
normal percentile
systematic sample
68-95-99.7 rule
random
21. A variable whose levels are controlled by the experimenter
level
block
factor
regression line
22. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
conditional distribution
voluntary response bias
experimental units
placebo effect
23. The square root of the variance
double-blind
multimodal
scatterplots
standard deviation
24. 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
random
r2
multistage sample
shape
25. Summarized with the mean or the median
data table
center
parameter
standard normal model
26. Bias introduced to a sample when a large fraction of those sampled fails to respond
subset
center
changing center and spread
nonresponse bias
27. 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
sampling frame
contingency table
undercoverage
histogram
28. Design Randomization occurring within blocks
extrapolation
placebo
standardizing
randomized block
29. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population
population parameter
sample survey
sample
matching
30. A point that does not fit the overall pattern seen in the scatterplot
least squares
strength
uniform
outlier
31. The sum of squared deviations from the mean - divided by the count minus one
sample size
standard normal model
data
variance
32. Systematically recorded information - whether numbers or labels - together with its context
data
random assignment
simulation component
comparing distributions
33. A sampling design in which entire groups are chosen at random
undercoverage
cluster sample
distribution
dotplot
34. A study based on data in which no manipulation of factors has been employed
sampling frame
5-number summary
observational study
quantitative variable
35. 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
sampling frame
sample size
trial
marginal distribution
36. Found by substituting the x-value in the regression equation; they're the values on the fitted line
percentile
representative
randomized block
predicted value
37. 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
data table
conditional distribution
voluntary response bias
subset
38. A sample drawn by selecting individuals systematically from a sampling frame
context
systematic sample
boxplot
outcome
39. A variable that names categories (whether with words or numerals)
symmetric
categorical variable
spread
placebo effect
40. An individual result of a component of a simulation
simulation component
parameter
randomized block
outcome
41. Found by summing all the data values and dividing by the count
mean
direction
independence
completely randomized design
42. When an observed difference is too large for us to believe that is is likely to have occurred naturally
statistically significant
data
systematic sample
random
43. 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
model
slope
normal percentile
single-blind
44. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
z-score
placebo effect
placebo
form
45. 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
completely randomized design
shape
stratified random sample
histogram
46. A numerical summary of how tightly the values are clustered around the 'center'
spread
statistic
boxplot
changing center and spread
47. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
z-score
variable
random
outcome
48. Extreme values that don't appear to belong with the rest of the data
outliers
mean
marginal distribution
quartile
49. Shows the relationship between two quantitative variables measured on the same cases
distribution
scatterplots
leverage
intercept
50. An observational study in which subjects are followed to observe future outcomes
prospective study
outliers
correlation
regression to the mean