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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. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
blinding
tails
distribution
completely randomized design
2. The natural tendency of randomly drawn samples to differ
cluster sample
sampling variability
matching
outlier
3. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
matched
stratified random sample
simple random sample
sampling variability
4. Shows a bar representing the count of each category in a categorical variable
bar chart
randomized block
population
distribution
5. Summarized with the standard deviation - interquartile range - and range
area principle
rescaling
uniform
spread
6. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
spread
spread
retrospective study
completely randomized design
7. To be valid - an experiment must assign experimental units to treatment groups at random
leverage
nonresponse bias
statistic
random assignment
8. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
shifting
randomized block
center
pie chart
9. A sampling design in which entire groups are chosen at random
cluster sample
ladder of powers
shape
lurking variable
10. The specific values that the experimenter chooses for a factor
center
level
dotplot
z-score
11. An equation or formula that simplifies and represents reality
mode
frequency table
marginal distribution
model
12. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
bar chart
nonresponse bias
intercept
center
13. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
simulation component
marginal distribution
symmetric
re-express data
14. Consists of the individuals who are conveniently available
convenience sample
cluster sample
simpson's paradox
shape
15. 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
percentile
data table
shifting
16. The difference between the first and third quartiles
interquartile range
least squares
leverage
random numbers
17. Numerically valued attribute of a model
direction
randomized block
parameter
double-blind
18. A numerically valued attribute of a model for a population
changing center and spread
symmetric
population parameter
sampling frame
19. A variable whose levels are controlled by the experimenter
factor
frequency table
uniform
prospective study
20. A numerical summary of how tightly the values are clustered around the 'center'
independence
spread
blinding
simulation
21. 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
mode
nonresponse bias
mean
interquartile range
22. When averages are taken across different groups - they can appear to contradict the overall averages
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23. 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
r2
variance
convenience sample
contingency table
24. 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
marginal distribution
dotplot
context
completely randomized design
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
symmetric
quantitative variable
intercept
68-95-99.7 rule
26. 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
placebo effect
subset
frequency table
standardizing
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
observational study
area principle
distribution
undercoverage
28. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
lurking variable
undercoverage
outcome
data table
29. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
center
control group
normal percentile
changing center and spread
30. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
conditional distribution
placebo effect
level
boxplot
31. The sequence of several components representing events that we are pretending will take place
representative
randomization
trial
sample survey
32. Control - randomize - replicate - block
principles of experimental design
model
conditional distribution
area principle
33. When doing this - consider their shape - center - and spread
lurking variable
comparing distributions
convenience sample
direction
34. 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
slope
multistage sample
histogram
response
35. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
strength
residuals
shape
center
36. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
standardizing
interquartile range
statistically significant
bimodal
37. Sampling schemes that combine several sampling methods
multistage sample
spread
68-95-99.7 rule
quantitative variable
38. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
tails
data table
normal probability plot
treatment
39. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population
sample
double-blind
sample survey
outliers
40. A numerical measure of the direction and strength of a linear association
simulation
correlation
standard normal model
standard deviation
41. A list of individuals from whom the sample is drawn
slope
sampling frame
single-blind
lurking variable
42. Holds information about the same characteristic for many cases
interquartile range
variance
mode
variable
43. 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
standard normal model
ladder of powers
principles of experimental design
44. In a statistical display - each data value should be represented by the same amount of area
simulation
area principle
intercept
placebo
45. A sample drawn by selecting individuals systematically from a sampling frame
systematic sample
case
symmetric
response
46. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
random numbers
outliers
units
range
47. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
scatterplots
shape
variance
lurking variable
48. Anything in a survey design that influences response
completely randomized design
marginal distribution
response bias
placebo effect
49. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
variance
spread
unimodal
level
50. 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
block
timeplot
simulation
population