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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. Shows a bar representing the count of each category in a categorical variable
range
randomized block
bar chart
linear model
2. An individual result of a component of a simulation
outcome
placebo effect
standard deviation
response
3. Found by summing all the data values and dividing by the count
block
interquartile range
distribution
mean
4. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
standardized value
strength
68-95-99.7 rule
stratified random sample
5. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
case
percentile
independence
simulation
6. The most basic situation in a simulation in which something happens at random
sample size
simulation
regression to the mean
simulation component
7. Summarized with the mean or the median
changing center and spread
randomized block
double-blind
center
8. 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
simulation
shape
convenience sample
correlation
9. The best defense against bias - in which each individual is given a fair - random chance of selection
blinding
categorical variable
spread
randomization
10. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
distribution
spread
random numbers
strength
11. Shows the relationship between two quantitative variables measured on the same cases
influential point
residuals
scatterplots
matching
12. When both those who could influence and evaluate the results are blinded
experiment
strength
double-blind
simulation
13. An event is this if we know what outcomes could happen - but not which particular values will happen
random
population parameter
unimodal
sampling frame
14. 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
normal model
standard normal model
undercoverage
least squares
15. Distributions with two modes
unimodal
bimodal
parameter
treatment
16. The ith ___ is the number that falls above i% of the data
quantitative variable
population
5-number summary
percentile
17. The square root of the variance
prospective study
standard deviation
experiment
multistage sample
18. 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
random numbers
bias
lurking variable
19. The entire group of individuals or instances about whom we hope to learn
simpson's paradox
conditional distribution
population
block
20. A representative subset of a population - examined in hope of learning about the population
sample
tails
sample survey
simulation
21. Useful family of models for unimodal - symmetric distributions
boxplot
dotplot
data
normal model
22. Displays counts and - sometimes - percentages of individuals falling into named categories on two or more variables; categorizes the individuals on all variables at once - to reveal possible patterns in one variable that may be contingent on the cate
contingency table
spread
residuals
standardized value
23. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
placebo effect
voluntary response bias
outlier
influential point
24. The distribution of a variable restricting the who to consider only a smaller group of individuals
trial
conditional distribution
placebo
standardized value
25. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
units
normal percentile
predicted value
marginal distribution
26. Shows quantitative data values in a way that sketches the distribution of the data
statistically significant
lurking variable
stem-and-leaf display
data table
27. 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
context
percentile
categorical variable
data table
28. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
response
bimodal
control group
treatment
29. Gives the possible values of the variable and the frequency or relative frequency of each value
center
bar chart
tails
distribution
30. A sample drawn by selecting individuals systematically from a sampling frame
outliers
factor
systematic sample
variance
31. Extreme values that don't appear to belong with the rest of the data
standard normal model
outliers
direction
response
32. When either those who could influence or evaluate the results is blinded
comparing distributions
quantitative variable
variable
single-blind
33. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
normal percentile
unimodal
outlier
random numbers
34. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
treatment
simple random sample
cluster sample
placebo
35. The number of individuals in a sample
blinding
linear model
trial
sample size
36. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
contingency table
rescaling
conditional distribution
center
37. The natural tendency of randomly drawn samples to differ
least squares
simulation
standardizing
sampling variability
38. The sum of squared deviations from the mean - divided by the count minus one
independence
systematic sample
variance
distribution
39. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
double-blind
pie chart
context
shape
40. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
5-number summary
re-express data
ladder of powers
variable
41. An arrangement of data in which each row represents a case and each column represents a variable
data table
matched
mean
level
42. An equation of the form y-hat = b0 + b1x
population
random numbers
control group
linear model
43. A normal model with a mean of 0 and a standard deviation of 1
predicted value
comparing distributions
standard normal model
influential point
44. When groups of experimental units are similar - it is a good idea to gather them together into these
matching
outlier
single-blind
block
45. Numerically valued attribute of a model
intercept
randomized block
nonresponse bias
parameter
46. 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
ladder of powers
multistage sample
slope
variance
47. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
standard deviation
predicted value
stratified random sample
standardizing
48. Any attempt to force a sample to resemble specified attributes of the population
matching
undercoverage
intercept
scatterplots
49. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population
rescaling
outcome
boxplot
sample survey
50. A variable that names categories (whether with words or numerals)
sample survey
categorical variable
slope
spread