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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. Systematically recorded information - whether numbers or labels - together with its context
blinding
sample size
subset
data
2. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
retrospective study
systematic sample
bias
multimodal
3. 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
simulation
strength
cluster sample
bias
4. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
nonresponse bias
center
control group
population parameter
5. Found by summing all the data values and dividing by the count
subset
direction
mean
parameter
6. 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
simple random sample
shifting
correlation
standardized value
7. The difference between the first and third quartiles
systematic sample
interquartile range
outliers
contingency table
8. Control - randomize - replicate - block
model
data table
form
principles of experimental design
9. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
influential point
simpson's paradox
unimodal
shape
10. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
population parameter
68-95-99.7 rule
bar chart
blinding
11. The entire group of individuals or instances about whom we hope to learn
68-95-99.7 rule
random numbers
response bias
population
12. A numerical summary of how tightly the values are clustered around the 'center'
stem-and-leaf display
spread
normal model
response
13. Gives the possible values of the variable and the frequency or relative frequency of each value
matched
convenience sample
distribution
pie chart
14. Shows the relationship between two quantitative variables measured on the same cases
form
strength
scatterplots
placebo
15. The best defense against bias - in which each individual is given a fair - random chance of selection
strength
outcome
response bias
randomization
16. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
units
median
population
simulation
17. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
residuals
random
re-express data
data
18. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
placebo effect
normal percentile
treatment
bar chart
19. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
shape
random numbers
outliers
standardizing
20. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
voluntary response bias
form
multistage sample
undercoverage
21. When either those who could influence or evaluate the results is blinded
mean
shifting
single-blind
level
22. Holds information about the same characteristic for many cases
completely randomized design
random
variable
sampling variability
23. A list of individuals from whom the sample is drawn
direction
normal probability plot
independence
sampling frame
24. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
changing center and spread
correlation
stratified random sample
simple random sample
25. 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
subset
correlation
categorical variable
standard deviation
26. The sum of squared deviations from the mean - divided by the count minus one
representative
variance
residuals
strength
27. 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
block
trial
placebo
28. Consists of the individuals who are conveniently available
distribution
conditional distribution
mean
convenience sample
29. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
lurking variable
representative
random numbers
randomized block
30. Value found by subtracting the mean and dividing by the standard deviation
units
standardized value
matching
principles of experimental design
31. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
outlier
contingency table
skewed
direction
32. An arrangement of data in which each row represents a case and each column represents a variable
census
random numbers
case
data table
33. Anything in a survey design that influences response
confounded
statistically significant
response bias
boxplot
34. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
outlier
confounded
predicted value
spread
35. Shows a bar representing the count of each category in a categorical variable
single-blind
voluntary response bias
bar chart
cluster sample
36. 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
data table
parameter
leverage
multimodal
37. Graphs a dot for each case against a single axis
quantitative variable
dotplot
sample survey
comparing distributions
38. The natural tendency of randomly drawn samples to differ
influential point
ladder of powers
uniform
sampling variability
39. 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
lurking variable
r2
tails
timeplot
40. A variable whose levels are controlled by the experimenter
factor
subset
correlation
least squares
41. 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
experiment
normal model
blinding
42. The specific values that the experimenter chooses for a factor
sample size
quantitative variable
level
population parameter
43. When an observed difference is too large for us to believe that is is likely to have occurred naturally
confounded
data table
mean
statistically significant
44. An event is this if we know what outcomes could happen - but not which particular values will happen
random
completely randomized design
68-95-99.7 rule
placebo
45. A study based on data in which no manipulation of factors has been employed
observational study
single-blind
skewed
response bias
46. Any attempt to force a sample to resemble specified attributes of the population
matching
stem-and-leaf display
sampling frame
standard normal model
47. The difference between the lowest and highest values in a data set
factor
area principle
range
block
48. The distribution of a variable restricting the who to consider only a smaller group of individuals
interquartile range
conditional distribution
spread
confounded
49. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
normal percentile
scatterplots
shape
simpson's paradox
50. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
skewed
unimodal
least squares
ladder of powers