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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. 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
control group
r2
random numbers
skewed
2. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
context
strength
center
boxplot
3. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
intercept
convenience sample
placebo
simple random sample
4. Shows quantitative data values in a way that sketches the distribution of the data
standardized value
variance
shape
stem-and-leaf display
5. Sampling schemes that combine several sampling methods
systematic sample
completely randomized design
randomized block
multistage sample
6. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
control group
statistic
lurking variable
standardized value
7. Places in order the effects that many re-expressions have on the data
ladder of powers
data
quartile
level
8. When groups of experimental units are similar - it is a good idea to gather them together into these
normal percentile
treatment
block
stratified random sample
9. Gives the possible values of the variable and the relative frequency of each value
confounded
spread
distribution
blinding
10. The entire group of individuals or instances about whom we hope to learn
prospective study
population
uniform
histogram
11. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant
rescaling
distribution
conditional distribution
categorical variable
12. Distributions with more than two modes
data
multimodal
response bias
multistage sample
13. A sampling design in which entire groups are chosen at random
cluster sample
skewed
simulation
symmetric
14. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
unimodal
trial
re-express data
scatterplots
15. Lists the categories in a categorical variable and gives the count or percentage of observations for each category
stem-and-leaf display
simple random sample
correlation
frequency table
16. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
shape
trial
independence
simulation component
17. An event is this if we know what outcomes could happen - but not which particular values will happen
random
marginal distribution
histogram
ladder of powers
18. When omitting a point from the data results in a very different regression model - the point is an ____
single-blind
influential point
center
census
19. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
extrapolation
5-number summary
distribution
tails
20. An equation of the form y-hat = b0 + b1x
leverage
confounded
center
linear model
21. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
placebo effect
standardized value
sampling variability
comparing distributions
22. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
least squares
center
population parameter
bias
23. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
simulation component
confounded
lurking variable
re-express data
24. Systematically recorded information - whether numbers or labels - together with its context
5-number summary
data
extrapolation
double-blind
25. The difference between the lowest and highest values in a data set
range
timeplot
treatment
observational study
26. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
pie chart
standardizing
normal model
matching
27. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
form
placebo effect
voluntary response bias
blinding
28. The difference between the first and third quartiles
r2
outcome
distribution
interquartile range
29. A representative subset of a population - examined in hope of learning about the population
sample
placebo effect
statistically significant
re-express data
30. 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
systematic sample
68-95-99.7 rule
case
factor
31. Graphs a dot for each case against a single axis
bimodal
form
context
dotplot
32. A variable whose levels are controlled by the experimenter
factor
systematic sample
statistically significant
standard deviation
33. 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
cluster sample
scatterplots
mean
shifting
34. When both those who could influence and evaluate the results are blinded
predicted value
double-blind
random assignment
center
35. Numerically valued attribute of a model
outliers
stem-and-leaf display
standardized value
parameter
36. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
nonresponse bias
timeplot
independence
population
37. Anything in a survey design that influences response
randomization
response bias
statistically significant
linear model
38. A distribution is this if it's not symmetric and one tail stretches out farther than the other
skewed
scatterplots
strength
statistic
39. Holds information about the same characteristic for many cases
variable
extrapolation
multimodal
standardizing
40. 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
leverage
census
confounded
outlier
41. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below
normal percentile
experimental units
quantitative variable
variance
42. A distribution that's roughly flat
comparing distributions
mean
linear model
uniform
43. The parts of a distribution that typically trail off on either side; they can be characterized as long or short
tails
sample size
level
standardizing
44. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
cluster sample
control group
conditional distribution
distribution
45. The ith ___ is the number that falls above i% of the data
representative
distribution
percentile
completely randomized design
46. Value calculated from data to summarize aspects of the data
outlier
statistic
representative
sample
47. Useful family of models for unimodal - symmetric distributions
stem-and-leaf display
factor
normal model
model
48. Found by summing all the data values and dividing by the count
confounded
independence
mean
68-95-99.7 rule
49. The natural tendency of randomly drawn samples to differ
ladder of powers
sampling variability
systematic sample
observational study
50. 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
extrapolation
percentile
spread
scatterplots
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