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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. 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
stem-and-leaf display
units
undercoverage
simulation component
2. An observational study in which subjects are followed to observe future outcomes
prospective study
marginal distribution
simpson's paradox
skewed
3. Value calculated from data to summarize aspects of the data
statistic
5-number summary
normal percentile
comparing distributions
4. Shows quantitative data values in a way that sketches the distribution of the data
regression line
extrapolation
lurking variable
stem-and-leaf display
5. 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
model
case
marginal distribution
quartile
6. 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
distribution
regression line
contingency table
representative
7. Distributions with two modes
bimodal
response
direction
distribution
8. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
standard normal model
simple random sample
completely randomized design
subset
9. A variable whose levels are controlled by the experimenter
extrapolation
least squares
factor
outliers
10. An equation of the form y-hat = b0 + b1x
treatment
linear model
simpson's paradox
bar chart
11. Bias introduced to a sample when a large fraction of those sampled fails to respond
nonresponse bias
spread
completely randomized design
matched
12. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
experiment
intercept
prospective study
quartile
13. Value found by subtracting the mean and dividing by the standard deviation
leverage
standardized value
conditional distribution
block
14. 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
matched
bar chart
simulation component
extrapolation
15. Found by summing all the data values and dividing by the count
multistage sample
mean
systematic sample
regression to the mean
16. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
random numbers
conditional distribution
confounded
bar chart
17. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
form
distribution
regression to the mean
treatment
18. Places in order the effects that many re-expressions have on the data
ladder of powers
least squares
distribution
sample size
19. A sampling design in which entire groups are chosen at random
frequency table
normal model
cluster sample
linear model
20. The natural tendency of randomly drawn samples to differ
pie chart
subset
sampling variability
center
21. Data points whose x-values are far from the mean of x are said to exert ____ on a linear model; with high enough ____ - residuals can appear to be deceptively small
block
sample survey
leverage
response
22. A study based on data in which no manipulation of factors has been employed
shifting
spread
range
observational study
23. A point that does not fit the overall pattern seen in the scatterplot
outlier
standard normal model
linear model
convenience sample
24. 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
rescaling
experiment
case
leverage
25. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant
rescaling
blinding
data table
percentile
26. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
normal percentile
units
r2
strength
27. The ____ we care about most is straight
form
representative
marginal distribution
random numbers
28. 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
single-blind
shifting
response variable
influential point
29. 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
level
interquartile range
response
normal probability plot
30. The best defense against bias - in which each individual is given a fair - random chance of selection
confounded
linear model
randomization
5-number summary
31. An equation or formula that simplifies and represents reality
model
shifting
independence
histogram
32. Any attempt to force a sample to resemble specified attributes of the population
shifting
double-blind
matching
68-95-99.7 rule
33. 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
influential point
double-blind
intercept
direction
34. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
placebo effect
marginal distribution
multistage sample
retrospective study
35. When doing this - consider their shape - center - and spread
percentile
range
comparing distributions
lurking variable
36. In a statistical display - each data value should be represented by the same amount of area
variance
bias
area principle
random
37. Consists of the individuals who are conveniently available
case
completely randomized design
rescaling
convenience sample
38. 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
slope
predicted value
random assignment
39. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
level
standardizing
units
influential point
40. A variable in which the numbers act as numerical values; always has units
random
68-95-99.7 rule
retrospective study
quantitative variable
41. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
random numbers
placebo
rescaling
confounded
42. A numerical measure of the direction and strength of a linear association
placebo
correlation
marginal distribution
random
43. When averages are taken across different groups - they can appear to contradict the overall averages
44. The most basic situation in a simulation in which something happens at random
categorical variable
simulation component
random
r2
45. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
units
model
symmetric
slope
46. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
center
population
simpson's paradox
variance
47. The parts of a distribution that typically trail off on either side; they can be characterized as long or short
randomization
context
slope
tails
48. An individual result of a component of a simulation
normal model
data
voluntary response bias
outcome
49. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
multistage sample
outlier
treatment
strength
50. A normal model with a mean of 0 and a standard deviation of 1
population
bias
standard normal model
lurking variable