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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. Places in order the effects that many re-expressions have on the data
standardizing
experiment
area principle
ladder of powers
2. 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
r2
context
placebo
frequency table
3. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
quartile
experiment
frequency table
retrospective study
4. 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
undercoverage
outlier
sampling variability
slope
5. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
control group
parameter
completely randomized design
randomized block
6. A point that does not fit the overall pattern seen in the scatterplot
outlier
standardized value
cluster sample
voluntary response bias
7. An arrangement of data in which each row represents a case and each column represents a variable
data table
independence
distribution
frequency table
8. 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
treatment
population
68-95-99.7 rule
retrospective study
9. Summarized with the standard deviation - interquartile range - and range
spread
lurking variable
conditional distribution
statistic
10. 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
strength
simulation
factor
experiment
11. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
control group
comparing distributions
bias
data table
12. 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
68-95-99.7 rule
form
normal probability plot
simulation
13. 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
distribution
distribution
double-blind
14. Individuals on whom an experiment is performed
response
standardized value
subset
experimental units
15. A representative subset of a population - examined in hope of learning about the population
sample survey
sample
data table
randomized block
16. Doing this is equivalent to changing its units
linear model
random assignment
simple random sample
changing center and spread
17. Design Randomization occurring within blocks
randomized block
experiment
factor
tails
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
unimodal
model
quantitative variable
19. Found by substituting the x-value in the regression equation; they're the values on the fitted line
predicted value
context
data
block
20. A treatment known to have no effect - administered so that all groups experience the same conditions
placebo
data
pie chart
block
21. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
principles of experimental design
center
response
completely randomized design
22. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
context
standardizing
independence
data table
23. In a statistical display - each data value should be represented by the same amount of area
standard normal model
area principle
correlation
interquartile range
24. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
center
standardizing
population parameter
random numbers
25. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
lurking variable
units
sample survey
spread
26. A sample that consists of the entire population
quantitative variable
census
frequency table
predicted value
27. Values of this record the results of each trial with respect to what we were interested in
z-score
response variable
stem-and-leaf display
regression to the mean
28. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
single-blind
nonresponse bias
case
re-express data
29. An individual about whom or which we have data
direction
spread
case
sample survey
30. The difference between the first and third quartiles
outliers
interquartile range
unimodal
control group
31. Distributions with two modes
intercept
bimodal
z-score
experimental units
32. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
factor
interquartile range
strength
cluster sample
33. When groups of experimental units are similar - it is a good idea to gather them together into these
block
census
blinding
scatterplots
34. All experimental units have an equal chance of receiving any treatment
completely randomized design
voluntary response bias
mode
data
35. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
independence
outcome
5-number summary
randomized block
36. A numerical summary of how tightly the values are clustered around the 'center'
spread
influential point
simulation component
outcome
37. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
control group
least squares
shape
extrapolation
38. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
lurking variable
sampling variability
convenience sample
blinding
39. When an observed difference is too large for us to believe that is is likely to have occurred naturally
statistically significant
stratified random sample
data table
control group
40. Bias introduced to a sample when a large fraction of those sampled fails to respond
principles of experimental design
symmetric
nonresponse bias
outlier
41. 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
marginal distribution
response variable
shifting
re-express data
42. The sum of squared deviations from the mean - divided by the count minus one
single-blind
shape
variance
systematic sample
43. The square root of the variance
regression line
prospective study
standard deviation
quartile
44. Systematically recorded information - whether numbers or labels - together with its context
factor
data
independence
outlier
45. When either those who could influence or evaluate the results is blinded
uniform
regression line
outliers
single-blind
46. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
voluntary response bias
random assignment
matching
blinding
47. The best defense against bias - in which each individual is given a fair - random chance of selection
observational study
bar chart
randomization
distribution
48. 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
voluntary response bias
comparing distributions
subset
median
49. The specific values that the experimenter chooses for a factor
correlation
skewed
level
slope
50. A sample drawn by selecting individuals systematically from a sampling frame
systematic sample
stratified random sample
population parameter
changing center and spread