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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. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
uniform
representative
z-score
skewed
2. All experimental units have an equal chance of receiving any treatment
completely randomized design
contingency table
skewed
case
3. To be valid - an experiment must assign experimental units to treatment groups at random
random assignment
systematic sample
cluster sample
center
4. 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
case
shape
pie chart
5. Gives the possible values of the variable and the relative frequency of each value
predicted value
completely randomized design
dotplot
distribution
6. A variable whose values are compared across different treatments
response
prospective study
correlation
uniform
7. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
variance
least squares
distribution
percentile
8. A numerical summary of how tightly the values are clustered around the 'center'
normal probability plot
spread
stem-and-leaf display
matched
9. Shows the relationship between two quantitative variables measured on the same cases
lurking variable
representative
simulation
scatterplots
10. 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
spread
contingency table
quantitative variable
case
11. Lists the categories in a categorical variable and gives the count or percentage of observations for each category
confounded
frequency table
population
z-score
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
normal probability plot
least squares
tails
experiment
13. Shows quantitative data values in a way that sketches the distribution of the data
pie chart
distribution
stem-and-leaf display
units
14. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
block
categorical variable
response bias
units
15. The natural tendency of randomly drawn samples to differ
r2
standardized value
sampling variability
re-express data
16. Consists of the individuals who are conveniently available
convenience sample
intercept
random numbers
subset
17. An arrangement of data in which each row represents a case and each column represents a variable
data table
intercept
standardized value
scatterplots
18. 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
direction
area principle
slope
statistic
19. The parts of a distribution that typically trail off on either side; they can be characterized as long or short
standardizing
form
matching
tails
20. A study based on data in which no manipulation of factors has been employed
variance
observational study
histogram
dotplot
21. Places in order the effects that many re-expressions have on the data
categorical variable
ladder of powers
standard deviation
simulation component
22. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
5-number summary
matched
z-score
skewed
23. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
quantitative variable
placebo effect
regression line
matching
24. Doing this is equivalent to changing its units
interquartile range
changing center and spread
correlation
principles of experimental design
25. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
regression to the mean
lurking variable
placebo effect
random assignment
26. Design Randomization occurring within blocks
conditional distribution
form
randomized block
normal model
27. A sample drawn by selecting individuals systematically from a sampling frame
systematic sample
random numbers
single-blind
cluster sample
28. When both those who could influence and evaluate the results are blinded
randomized block
outcome
double-blind
influential point
29. Bias introduced to a sample when a large fraction of those sampled fails to respond
linear model
nonresponse bias
experiment
case
30. Although linear models provide an easy way to predict values of y for a given value of x - it is unsafe to predict for values of x far from the ones used to find the linear model equation; predictions should not be trusted
response
level
normal probability plot
extrapolation
31. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
parameter
bias
timeplot
trial
32. The square root of the variance
standard deviation
response bias
single-blind
sampling frame
33. Graphs a dot for each case against a single axis
categorical variable
median
matching
dotplot
34. The difference between the lowest and highest values in a data set
range
statistically significant
slope
changing center and spread
35. The best defense against bias - in which each individual is given a fair - random chance of selection
interquartile range
sampling frame
randomization
matching
36. A sampling design in which entire groups are chosen at random
retrospective study
cluster sample
normal probability plot
timeplot
37. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population
form
simple random sample
variance
sample survey
38. When omitting a point from the data results in a very different regression model - the point is an ____
data table
slope
re-express data
influential point
39. 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
mode
leverage
5-number summary
case
40. Summarized with the mean or the median
histogram
convenience sample
statistically significant
center
41. When either those who could influence or evaluate the results is blinded
subset
dotplot
single-blind
marginal distribution
42. Holds information about the same characteristic for many cases
random
form
variable
standard normal model
43. Anything in a survey design that influences response
sample size
response bias
variance
context
44. A distribution is this if it's not symmetric and one tail stretches out farther than the other
variance
blinding
skewed
scatterplots
45. The most basic situation in a simulation in which something happens at random
mean
timeplot
simulation component
marginal distribution
46. 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
nonresponse bias
trial
68-95-99.7 rule
census
47. 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
boxplot
linear model
observational study
marginal distribution
48. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
uniform
outlier
population
parameter
49. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
spread
normal probability plot
nonresponse bias
simple random sample
50. Extreme values that don't appear to belong with the rest of the data
outliers
model
slope
standardized value