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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 arrangement of data in which each row represents a case and each column represents a variable
distribution
data table
lurking variable
independence
2. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
retrospective study
correlation
extrapolation
variable
3. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
intercept
matched
response variable
random
4. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
simple random sample
regression line
sampling variability
convenience sample
5. In a statistical display - each data value should be represented by the same amount of area
area principle
outlier
independence
predicted value
6. Gives the possible values of the variable and the relative frequency of each value
distribution
timeplot
dotplot
68-95-99.7 rule
7. A sampling design in which entire groups are chosen at random
marginal distribution
units
standardized value
cluster sample
8. Found by summing all the data values and dividing by the count
principles of experimental design
correlation
mean
convenience sample
9. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
lurking variable
convenience sample
re-express data
systematic sample
10. When doing this - consider their shape - center - and spread
comparing distributions
lurking variable
data
convenience sample
11. Shows a bar representing the count of each category in a categorical variable
regression to the mean
standard normal model
residuals
bar chart
12. 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
contingency table
census
units
13. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
factor
uniform
regression to the mean
r2
14. Any attempt to force a sample to resemble specified attributes of the population
re-express data
slope
uniform
matching
15. 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
simpson's paradox
bar chart
contingency table
matched
16. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
bimodal
slope
normal probability plot
shape
17. Places in order the effects that many re-expressions have on the data
bar chart
outcome
ladder of powers
trial
18. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
response bias
residuals
lurking variable
outliers
19. Extreme values that don't appear to belong with the rest of the data
sample survey
bias
outliers
factor
20. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
median
sample
independence
influential point
21. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
strength
regression to the mean
completely randomized design
bias
22. A numerical measure of the direction and strength of a linear association
correlation
parameter
stem-and-leaf display
case
23. An individual result of a component of a simulation
area principle
percentile
center
outcome
24. To be valid - an experiment must assign experimental units to treatment groups at random
response variable
uniform
double-blind
random assignment
25. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
form
experimental units
model
units
26. A distribution is this if the two halves on either side of the center look approximately like mirror images of each other
shifting
comparing distributions
symmetric
single-blind
27. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
scatterplots
standardizing
spread
center
28. Systematically recorded information - whether numbers or labels - together with its context
mode
data
spread
strength
29. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
response bias
blinding
normal percentile
extrapolation
30. A normal model with a mean of 0 and a standard deviation of 1
placebo
standard normal model
simpson's paradox
outcome
31. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
z-score
response
random numbers
stratified random sample
32. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
regression line
r2
sample
placebo
33. The ____ we care about most is straight
form
random assignment
stratified random sample
variable
34. The lower of this is the value with a quarter of the data below it; the upper of this has a quarter of the data above it
convenience sample
sampling frame
direction
quartile
35. Summarized with the standard deviation - interquartile range - and range
spread
skewed
distribution
interquartile range
36. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
5-number summary
bias
random numbers
model
37. All experimental units have an equal chance of receiving any treatment
prospective study
r2
random
completely randomized design
38. An equation of the form y-hat = b0 + b1x
linear model
normal probability plot
randomized block
correlation
39. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
shape
single-blind
unimodal
random
40. A treatment known to have no effect - administered so that all groups experience the same conditions
standard deviation
placebo
confounded
center
41. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
response
variable
variance
pie chart
42. Value calculated from data to summarize aspects of the data
double-blind
convenience sample
statistic
stem-and-leaf display
43. 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
prospective study
regression line
contingency table
sampling frame
44. Values of this record the results of each trial with respect to what we were interested in
treatment
response variable
quantitative variable
correlation
45. Useful family of models for unimodal - symmetric distributions
normal model
intercept
influential point
parameter
46. An event is this if we know what outcomes could happen - but not which particular values will happen
random numbers
matched
subset
random
47. 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
sample survey
experiment
undercoverage
least squares
48. Individuals on whom an experiment is performed
normal percentile
representative
experimental units
least squares
49. Found by substituting the x-value in the regression equation; they're the values on the fitted line
strength
predicted value
range
shape
50. An individual about whom or which we have data
variable
z-score
case
random