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Test your basic knowledge |
AP Statistics Vocab
Start Test
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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. Value calculated from data to summarize aspects of the data
lurking variable
block
principles of experimental design
statistic
2. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
slope
ladder of powers
placebo effect
tails
3. An event is this if we know what outcomes could happen - but not which particular values will happen
random
blinding
case
mode
4. Graphs a dot for each case against a single axis
response
dotplot
control group
random
5. The distribution of a variable restricting the who to consider only a smaller group of individuals
sample
percentile
conditional distribution
comparing distributions
6. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
regression line
normal percentile
matched
boxplot
7. A distribution that's roughly flat
uniform
randomization
bimodal
normal percentile
8. Extreme values that don't appear to belong with the rest of the data
slope
direction
intercept
outliers
9. Systematically recorded information - whether numbers or labels - together with its context
mode
independence
data
frequency table
10. 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
histogram
leverage
undercoverage
intercept
11. In a retrospective or prospective study Subjects who are similar in ways not under study may be ____ and then compared with each other on the variables of interest
matched
parameter
placebo
statistic
12. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
outliers
influential point
intercept
response variable
13. 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
normal probability plot
unimodal
principles of experimental design
14. Distributions with more than two modes
multimodal
principles of experimental design
shifting
strength
15. The sum of squared deviations from the mean - divided by the count minus one
histogram
variance
matched
center
16. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
multimodal
lurking variable
randomized block
response
17. 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
standard normal model
r2
blinding
sample
18. Found by substituting the x-value in the regression equation; they're the values on the fitted line
standard normal model
frequency table
treatment
predicted value
19. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant
response
direction
uniform
rescaling
20. When doing this - consider their shape - center - and spread
subset
representative
frequency table
comparing distributions
21. A normal model with a mean of 0 and a standard deviation of 1
standard normal model
linear model
data table
response bias
22. A distribution is this if it's not symmetric and one tail stretches out farther than the other
independence
skewed
confounded
single-blind
23. Design Randomization occurring within blocks
influential point
rescaling
skewed
randomized block
24. Holds information about the same characteristic for many cases
control group
sampling variability
observational study
variable
25. A variable whose levels are controlled by the experimenter
simpson's paradox
trial
factor
sampling variability
26. 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
68-95-99.7 rule
range
statistically significant
undercoverage
27. A treatment known to have no effect - administered so that all groups experience the same conditions
outlier
unimodal
placebo
representative
28. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters
median
random assignment
lurking variable
representative
29. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
single-blind
skewed
timeplot
z-score
30. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
census
representative
conditional distribution
control group
31. Any attempt to force a sample to resemble specified attributes of the population
shifting
predicted value
matching
dotplot
32. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
timeplot
voluntary response bias
sample
statistically significant
33. A numerically valued attribute of a model for a population
standard deviation
response variable
population parameter
outlier
34. Numerically valued attribute of a model
units
population
parameter
pie chart
35. An observational study in which subjects are followed to observe future outcomes
mean
68-95-99.7 rule
prospective study
intercept
36. 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
quantitative variable
case
subset
extrapolation
37. The entire group of individuals or instances about whom we hope to learn
population
standardizing
distribution
outlier
38. An equation or formula that simplifies and represents reality
response variable
response bias
model
shifting
39. Consists of the individuals who are conveniently available
center
normal percentile
convenience sample
re-express data
40. Doing this is equivalent to changing its units
changing center and spread
comparing distributions
unimodal
random
41. When an observed difference is too large for us to believe that is is likely to have occurred naturally
z-score
model
marginal distribution
statistically significant
42. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
distribution
standardizing
independence
blinding
43. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
units
factor
quartile
control group
44. Gives the possible values of the variable and the relative frequency of each value
distribution
prospective study
dotplot
double-blind
45. A sample that consists of the entire population
randomized block
census
categorical variable
r2
46. Gives the possible values of the variable and the frequency or relative frequency of each value
response variable
bias
distribution
categorical variable
47. A numerical measure of the direction and strength of a linear association
conditional distribution
correlation
data
simple random sample
48. An arrangement of data in which each row represents a case and each column represents a variable
response bias
shifting
percentile
data table
49. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
re-express data
standard deviation
experiment
representative
50. Individuals on whom an experiment is performed
experimental units
range
units
shifting
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