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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. An individual about whom or which we have data
quantitative variable
case
bimodal
independence
2. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
shape
z-score
categorical variable
timeplot
3. 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
independence
subset
random
mode
4. Graphs a dot for each case against a single axis
dotplot
random
principles of experimental design
marginal distribution
5. A sample drawn by selecting individuals systematically from a sampling frame
mode
systematic sample
sampling variability
standard normal model
6. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters
population parameter
lurking variable
r2
representative
7. Values of this record the results of each trial with respect to what we were interested in
response variable
simpson's paradox
factor
correlation
8. A normal model with a mean of 0 and a standard deviation of 1
random
contingency table
regression to the mean
standard normal model
9. An equation of the form y-hat = b0 + b1x
mean
tails
linear model
block
10. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
sample
lurking variable
units
comparing distributions
11. Sampling schemes that combine several sampling methods
influential point
multistage sample
range
control group
12. A numerical summary of how tightly the values are clustered around the 'center'
z-score
units
lurking variable
spread
13. The entire group of individuals or instances about whom we hope to learn
variable
population
prospective study
outlier
14. The natural tendency of randomly drawn samples to differ
sampling variability
independence
histogram
lurking variable
15. Numerically valued attribute of a model
symmetric
z-score
tails
parameter
16. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
confounded
shape
boxplot
quartile
17. A variable in which the numbers act as numerical values; always has units
simpson's paradox
randomization
quantitative variable
residuals
18. The number of individuals in a sample
sample size
data table
standardized value
correlation
19. The sum of squared deviations from the mean - divided by the count minus one
multimodal
units
variable
variance
20. An observational study in which subjects are followed to observe future outcomes
prospective study
rescaling
random numbers
correlation
21. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
treatment
extrapolation
undercoverage
bias
22. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
simpson's paradox
retrospective study
population parameter
blinding
23. A variable whose values are compared across different treatments
response
changing center and spread
median
spread
24. 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
comparing distributions
extrapolation
68-95-99.7 rule
context
25. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
data table
extrapolation
68-95-99.7 rule
pie chart
26. 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
contingency table
confounded
lurking variable
random assignment
27. When omitting a point from the data results in a very different regression model - the point is an ____
census
influential point
independence
outcome
28. Individuals on whom an experiment is performed
percentile
cluster sample
response bias
experimental units
29. An arrangement of data in which each row represents a case and each column represents a variable
undercoverage
data table
symmetric
random
30. Summarized with the standard deviation - interquartile range - and range
spread
simple random sample
voluntary response bias
outlier
31. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
range
outlier
boxplot
data table
32. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
outlier
simpson's paradox
lurking variable
correlation
33. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
random assignment
simple random sample
standardizing
marginal distribution
34. 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
strength
r2
placebo effect
variable
35. Shows a bar representing the count of each category in a categorical variable
bar chart
regression line
intercept
contingency table
36. 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
units
random
response
37. The difference between the lowest and highest values in a data set
comparing distributions
68-95-99.7 rule
range
statistically significant
38. Any attempt to force a sample to resemble specified attributes of the population
interquartile range
tails
distribution
matching
39. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
retrospective study
single-blind
boxplot
area principle
40. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
intercept
placebo effect
distribution
outliers
41. Consists of the individuals who are conveniently available
randomization
sample
skewed
convenience sample
42. Gives the possible values of the variable and the frequency or relative frequency of each value
distribution
voluntary response bias
quantitative variable
context
43. A distribution is this if it's not symmetric and one tail stretches out farther than the other
distribution
re-express data
randomized block
skewed
44. The distribution of a variable restricting the who to consider only a smaller group of individuals
variable
regression to the mean
conditional distribution
bar chart
45. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
population
random
comparing distributions
treatment
46. 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
model
normal probability plot
prospective study
subset
47. When averages are taken across different groups - they can appear to contradict the overall averages
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48. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
influential point
predicted value
simple random sample
conditional distribution
49. The parts of a distribution that typically trail off on either side; they can be characterized as long or short
normal percentile
standard normal model
tails
least squares
50. Doing this is equivalent to changing its units
response variable
changing center and spread
random numbers
boxplot