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Test your basic knowledge |
AP Statistics Vocab
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Subjects
:
statistics
,
ap
Instructions:
Answer 50 questions in 15 minutes.
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.
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. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below
5-number summary
normal percentile
conditional distribution
center
2. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
units
area principle
intercept
conditional distribution
3. 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
observational study
strength
population
leverage
4. The ith ___ is the number that falls above i% of the data
percentile
response variable
bimodal
placebo
5. 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
voluntary response bias
direction
simple random sample
area principle
6. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population
representative
subset
sample survey
placebo
7. When an observed difference is too large for us to believe that is is likely to have occurred naturally
statistically significant
spread
uniform
area principle
8. The square of the correlation between y and x; gives the fraction of the variability of y accounted for by the least squares linear regression on x; an overall measure of how successful the regression is in linearly relating y to x
timeplot
least squares
marginal distribution
r2
9. Any attempt to force a sample to resemble specified attributes of the population
matching
outlier
least squares
simulation component
10. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
z-score
lurking variable
re-express data
median
11. The specific values that the experimenter chooses for a factor
sample
outliers
level
categorical variable
12. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
bias
extrapolation
standardizing
context
13. Places in order the effects that many re-expressions have on the data
normal probability plot
extrapolation
data table
ladder of powers
14. 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
mean
simulation
normal probability plot
systematic sample
15. 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
unimodal
distribution
multistage sample
16. An individual result of a component of a simulation
outcome
stem-and-leaf display
lurking variable
factor
17. Useful family of models for unimodal - symmetric distributions
normal probability plot
predicted value
tails
normal model
18. All experimental units have an equal chance of receiving any treatment
completely randomized design
random assignment
regression to the mean
standardized value
19. Value calculated from data to summarize aspects of the data
lurking variable
statistic
leverage
form
20. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters
retrospective study
representative
blinding
correlation
21. A variable whose levels are controlled by the experimenter
stratified random sample
factor
conditional distribution
nonresponse bias
22. Distributions with more than two modes
multimodal
experiment
completely randomized design
quantitative variable
23. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
confounded
shape
response bias
subset
24. A numerical measure of the direction and strength of a linear association
correlation
extrapolation
context
sampling frame
25. An event is this if we know what outcomes could happen - but not which particular values will happen
response bias
leverage
range
random
26. A variable whose values are compared across different treatments
simpson's paradox
regression to the mean
response
contingency table
27. To be valid - an experiment must assign experimental units to treatment groups at random
census
dotplot
slope
random assignment
28. Lists the categories in a categorical variable and gives the count or percentage of observations for each category
frequency table
mode
form
confounded
29. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
least squares
standard normal model
placebo effect
systematic sample
30. Displays data that change over time
statistically significant
timeplot
random assignment
model
31. When doing this - consider their shape - center - and spread
normal model
multistage sample
spread
comparing distributions
32. A sample drawn by selecting individuals systematically from a sampling frame
scatterplots
linear model
simpson's paradox
systematic sample
33. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
marginal distribution
random assignment
center
changing center and spread
34. The difference between the first and third quartiles
interquartile range
bar chart
trial
variable
35. 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
simulation
re-express data
distribution
36. The best defense against bias - in which each individual is given a fair - random chance of selection
regression line
experiment
timeplot
randomization
37. Graphs a dot for each case against a single axis
bar chart
quantitative variable
dotplot
sample
38. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
residuals
voluntary response bias
slope
leverage
39. Numerically valued attribute of a model
boxplot
re-express data
distribution
parameter
40. 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
outcome
contingency table
random numbers
percentile
41. Found by summing all the data values and dividing by the count
interquartile range
ladder of powers
mean
sample size
42. 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
shifting
strength
categorical variable
undercoverage
43. 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
extrapolation
unimodal
census
68-95-99.7 rule
44. Summarized with the mean or the median
median
influential point
center
case
45. A numerical summary of how tightly the values are clustered around the 'center'
scatterplots
spread
placebo effect
matched
46. A representative subset of a population - examined in hope of learning about the population
r2
sample
independence
correlation
47. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
standard deviation
conditional distribution
unimodal
undercoverage
48. A variable in which the numbers act as numerical values; always has units
slope
quantitative variable
outcome
outliers
49. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
rescaling
simulation component
5-number summary
simple random sample
50. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant
categorical variable
comparing distributions
multistage sample
rescaling
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