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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. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
statistically significant
response
lurking variable
random
2. 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
leverage
area principle
strength
5-number summary
3. The ith ___ is the number that falls above i% of the data
statistic
percentile
prospective study
statistically significant
4. The sum of squared deviations from the mean - divided by the count minus one
variance
factor
z-score
simulation
5. A numerically valued attribute of a model for a population
range
skewed
context
population parameter
6. Places in order the effects that many re-expressions have on the data
treatment
ladder of powers
undercoverage
outcome
7. Distributions with two modes
response
median
sample survey
bimodal
8. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
bimodal
response
strength
block
9. Found by substituting the x-value in the regression equation; they're the values on the fitted line
context
random assignment
block
predicted value
10. A positive ____ or association means that - in general - as one variable increases - so does the other; when increases in one variable generally correspond to decreases in the other - the association is negative
stem-and-leaf display
direction
blinding
lurking variable
11. Numerically valued attribute of a model
parameter
census
experimental units
uniform
12. A variable in which the numbers act as numerical values; always has units
dotplot
factor
shifting
quantitative variable
13. The natural tendency of randomly drawn samples to differ
representative
matching
sampling variability
area principle
14. Summarized with the standard deviation - interquartile range - and range
spread
outlier
pie chart
random assignment
15. Found by summing all the data values and dividing by the count
spread
mean
subset
standardized value
16. Shows a bar representing the count of each category in a categorical variable
placebo
independence
bar chart
level
17. A variable whose levels are controlled by the experimenter
68-95-99.7 rule
factor
influential point
prospective study
18. A variable whose values are compared across different treatments
random numbers
response
prospective study
variable
19. Doing this is equivalent to changing its units
sampling frame
interquartile range
nonresponse bias
changing center and spread
20. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
intercept
normal probability plot
matched
mean
21. The most basic situation in a simulation in which something happens at random
statistic
simulation component
quartile
independence
22. Anything in a survey design that influences response
quartile
response bias
correlation
treatment
23. Holds information about the same characteristic for many cases
sample
observational study
variable
simpson's paradox
24. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
confounded
context
outliers
z-score
25. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
units
outlier
interquartile range
bar chart
26. Displays data that change over time
median
timeplot
retrospective study
placebo effect
27. 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
outliers
median
least squares
28. When either those who could influence or evaluate the results is blinded
outlier
sample
level
single-blind
29. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
regression line
median
completely randomized design
normal model
30. Gives the possible values of the variable and the frequency or relative frequency of each value
re-express data
observational study
distribution
multistage sample
31. An equation of the form y-hat = b0 + b1x
outlier
control group
linear model
timeplot
32. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
independence
least squares
outlier
correlation
33. A distribution is this if the two halves on either side of the center look approximately like mirror images of each other
symmetric
single-blind
ladder of powers
dotplot
34. When both those who could influence and evaluate the results are blinded
normal model
mean
form
double-blind
35. Values of this record the results of each trial with respect to what we were interested in
scatterplots
subset
correlation
response variable
36. 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
median
5-number summary
trial
shifting
37. Sampling schemes that combine several sampling methods
multistage sample
frequency table
double-blind
sampling variability
38. The number of individuals in a sample
distribution
shifting
mode
sample size
39. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
blinding
normal model
trial
timeplot
40. Any attempt to force a sample to resemble specified attributes of the population
factor
matching
stratified random sample
context
41. 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
placebo
68-95-99.7 rule
prospective study
population parameter
42. An event is this if we know what outcomes could happen - but not which particular values will happen
model
placebo effect
random
response
43. An observational study in which subjects are followed to observe future outcomes
prospective study
comparing distributions
placebo
model
44. A variable that names categories (whether with words or numerals)
normal model
categorical variable
shape
sampling frame
45. 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
normal probability plot
sample survey
lurking variable
linear model
46. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
sampling variability
mean
regression to the mean
matching
47. The middle value with half of the data above and half below it
factor
median
spread
level
48. Ideally tells who was measured - what was measured - how the data were collected - where the data were collected - and when and why the study was performed
multimodal
context
level
bimodal
49. A numerical measure of the direction and strength of a linear association
regression to the mean
normal probability plot
correlation
area principle
50. Individuals on whom an experiment is performed
experimental units
5-number summary
randomization
random numbers