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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. The number of individuals in a sample
sample size
percentile
population parameter
conditional distribution
2. An individual about whom or which we have data
data table
case
regression to the mean
independence
3. Extreme values that don't appear to belong with the rest of the data
contingency table
parameter
outliers
outcome
4. An observational study in which subjects are followed to observe future outcomes
completely randomized design
prospective study
dotplot
lurking variable
5. Summarized with the mean or the median
center
cluster sample
strength
range
6. A treatment known to have no effect - administered so that all groups experience the same conditions
blinding
sample size
multimodal
placebo
7. 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
normal probability plot
comparing distributions
5-number summary
scatterplots
8. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
intercept
correlation
shifting
retrospective study
9. Anything in a survey design that influences response
model
response bias
single-blind
unimodal
10. 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
leverage
marginal distribution
scatterplots
representative
11. The ____ we care about most is straight
form
subset
sampling frame
conditional distribution
12. 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
experiment
intercept
normal probability plot
simulation
13. An arrangement of data in which each row represents a case and each column represents a variable
data table
population parameter
5-number summary
intercept
14. The difference between the lowest and highest values in a data set
subset
standardized value
range
bias
15. Places in order the effects that many re-expressions have on the data
strength
ladder of powers
context
area principle
16. Individuals on whom an experiment is performed
contingency table
lurking variable
experimental units
interquartile range
17. 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
simple random sample
sampling variability
form
histogram
18. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
lurking variable
context
5-number summary
boxplot
19. Graphs a dot for each case against a single axis
re-express data
histogram
dotplot
experimental units
20. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
subset
voluntary response bias
population
stratified random sample
21. A variable whose values are compared across different treatments
simpson's paradox
response
normal model
data
22. Systematically recorded information - whether numbers or labels - together with its context
direction
range
data
histogram
23. A numerical summary of how tightly the values are clustered around the 'center'
outcome
systematic sample
sample size
spread
24. 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
subset
random numbers
dotplot
units
25. In a normal model - about 68% of values fall within 1 standard deviation of the mean - about 95% fall within 2 standard deviations of the mean - and about 99.7% fall within 3 standard deviations of the mean
confounded
68-95-99.7 rule
shape
lurking variable
26. The sequence of several components representing events that we are pretending will take place
principles of experimental design
predicted value
quartile
trial
27. 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
conditional distribution
timeplot
mode
frequency table
28. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
representative
normal percentile
center
shape
29. A distribution is this if it's not symmetric and one tail stretches out farther than the other
5-number summary
confounded
simulation component
skewed
30. 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
sample size
tails
mode
simulation
31. The specific values that the experimenter chooses for a factor
block
extrapolation
percentile
level
32. A normal model with a mean of 0 and a standard deviation of 1
stratified random sample
standard normal model
intercept
tails
33. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
intercept
prospective study
voluntary response bias
bias
34. Bias introduced to a sample when a large fraction of those sampled fails to respond
double-blind
nonresponse bias
contingency table
frequency table
35. The most basic situation in a simulation in which something happens at random
parameter
standard deviation
interquartile range
simulation component
36. Values of this record the results of each trial with respect to what we were interested in
area principle
residuals
response variable
factor
37. Found by summing all the data values and dividing by the count
strength
mean
simpson's paradox
uniform
38. When both those who could influence and evaluate the results are blinded
symmetric
regression line
double-blind
trial
39. A sampling design in which entire groups are chosen at random
cluster sample
center
leverage
experimental units
40. 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
contingency table
shape
direction
standard normal model
41. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
z-score
matching
slope
lurking variable
42. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
intercept
placebo effect
units
quartile
43. An equation or formula that simplifies and represents reality
population parameter
conditional distribution
random numbers
model
44. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below
standardized value
direction
single-blind
normal percentile
45. Doing this is equivalent to changing its units
randomization
distribution
changing center and spread
case
46. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
convenience sample
pie chart
form
strength
47. A representative subset of a population - examined in hope of learning about the population
sample
data
rescaling
randomization
48. 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
quartile
simulation component
range
49. In a statistical display - each data value should be represented by the same amount of area
area principle
units
single-blind
population parameter
50. Any attempt to force a sample to resemble specified attributes of the population
experimental units
matching
multimodal
outlier