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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. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
blinding
5-number summary
response
simulation component
2. The distribution of a variable restricting the who to consider only a smaller group of individuals
normal model
center
conditional distribution
population parameter
3. The middle value with half of the data above and half below it
standard deviation
median
placebo effect
statistically significant
4. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
normal probability plot
single-blind
correlation
shape
5. The sum of squared deviations from the mean - divided by the count minus one
extrapolation
case
variance
model
6. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant
center
rescaling
random assignment
boxplot
7. Shows a bar representing the count of each category in a categorical variable
placebo effect
bar chart
variance
marginal distribution
8. Systematically recorded information - whether numbers or labels - together with its context
data
cluster sample
normal percentile
quartile
9. Places in order the effects that many re-expressions have on the data
independence
standard normal model
ladder of powers
random
10. 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
undercoverage
distribution
response bias
nonresponse bias
11. 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
histogram
outcome
influential point
parameter
12. 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
model
sample size
direction
categorical variable
13. A sampling design in which entire groups are chosen at random
predicted value
cluster sample
bimodal
census
14. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
correlation
regression to the mean
matching
simulation component
15. 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
spread
standard normal model
center
context
16. Doing this is equivalent to changing its units
changing center and spread
center
standard deviation
comparing distributions
17. 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
stem-and-leaf display
stratified random sample
variance
experiment
18. 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
normal probability plot
shifting
context
comparing distributions
19. When doing this - consider their shape - center - and spread
sample survey
standardizing
comparing distributions
context
20. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
bias
outlier
comparing distributions
mode
21. The difference between the lowest and highest values in a data set
data
range
normal model
multistage sample
22. An event is this if we know what outcomes could happen - but not which particular values will happen
area principle
leverage
correlation
random
23. An observational study in which subjects are followed to observe future outcomes
ladder of powers
systematic sample
control group
prospective study
24. Extreme values that don't appear to belong with the rest of the data
form
sample size
outliers
population
25. An equation or formula that simplifies and represents reality
retrospective study
model
shape
lurking variable
26. 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
regression line
experiment
parameter
r2
27. 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
simpson's paradox
subset
simulation component
form
28. 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
bar chart
simulation
standardized value
changing center and spread
29. A numerically valued attribute of a model for a population
population parameter
unimodal
68-95-99.7 rule
shape
30. All experimental units have an equal chance of receiving any treatment
bimodal
re-express data
multimodal
completely randomized design
31. The square root of the variance
retrospective study
standard deviation
simpson's paradox
skewed
32. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
r2
residuals
interquartile range
placebo effect
33. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
bias
lurking variable
quartile
strength
34. A sample that consists of the entire population
data
statistically significant
census
slope
35. A representative subset of a population - examined in hope of learning about the population
statistically significant
sample size
sample
frequency table
36. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
bias
leverage
stratified random sample
quartile
37. A display to help assess whether a distribution of data is approximately normal; if it is nearly straight - the data satisfy the nearly normal condition
response
multimodal
normal probability plot
treatment
38. The entire group of individuals or instances about whom we hope to learn
population
normal model
variance
random assignment
39. The difference between the first and third quartiles
interquartile range
convenience sample
statistic
direction
40. The specific values that the experimenter chooses for a factor
parameter
normal probability plot
level
experiment
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
spread
undercoverage
experimental units
42. When either those who could influence or evaluate the results is blinded
center
single-blind
statistically significant
marginal distribution
43. Holds information about the same characteristic for many cases
spread
variable
subset
shifting
44. Sampling schemes that combine several sampling methods
population
nonresponse bias
skewed
multistage sample
45. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
symmetric
voluntary response bias
randomization
multimodal
46. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
placebo effect
spread
form
sample size
47. A normal model with a mean of 0 and a standard deviation of 1
symmetric
standard normal model
subset
lurking variable
48. 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
systematic sample
intercept
68-95-99.7 rule
49. Distributions with more than two modes
multimodal
68-95-99.7 rule
shifting
cluster sample
50. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
68-95-99.7 rule
predicted value
center
lurking variable