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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. Although linear models provide an easy way to predict values of y for a given value of x - it is unsafe to predict for values of x far from the ones used to find the linear model equation; predictions should not be trusted
experimental units
model
block
extrapolation
2. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
response
regression line
normal probability plot
data table
3. Summarized with the mean or the median
center
context
conditional distribution
factor
4. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
shape
experimental units
re-express data
randomization
5. Extreme values that don't appear to belong with the rest of the data
influential point
completely randomized design
context
outliers
6. A variable whose levels are controlled by the experimenter
residuals
factor
prospective study
undercoverage
7. An equation or formula that simplifies and represents reality
standard deviation
histogram
matched
model
8. 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
standardized value
placebo effect
multistage sample
9. Gives a value in 'y-units per x-unit'; changes of one unit in x are associated with changes of b1 units in predicted values of y
linear model
simulation component
population
slope
10. A numerical measure of the direction and strength of a linear association
matching
quantitative variable
correlation
simple random sample
11. Summarized with the standard deviation - interquartile range - and range
retrospective study
spread
outliers
outlier
12. A treatment known to have no effect - administered so that all groups experience the same conditions
principles of experimental design
placebo
center
normal model
13. Holds information about the same characteristic for many cases
tails
experimental units
sampling variability
variable
14. The ith ___ is the number that falls above i% of the data
variable
slope
linear model
percentile
15. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
standardizing
direction
trial
single-blind
16. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
frequency table
5-number summary
response
lurking variable
17. The difference between the first and third quartiles
statistic
interquartile range
sample
nonresponse bias
18. Doing this is equivalent to changing its units
changing center and spread
re-express data
dotplot
pie chart
19. 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
simulation
factor
randomization
residuals
20. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
ladder of powers
changing center and spread
level
treatment
21. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
regression to the mean
stem-and-leaf display
population parameter
strength
22. 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
sample size
voluntary response bias
re-express data
quartile
23. In a statistical display - each data value should be represented by the same amount of area
population
ladder of powers
area principle
variance
24. An equation of the form y-hat = b0 + b1x
normal percentile
z-score
5-number summary
linear model
25. Consists of the individuals who are conveniently available
response variable
trial
pie chart
convenience sample
26. A sampling design in which entire groups are chosen at random
conditional distribution
residuals
randomized block
cluster sample
27. Gives the possible values of the variable and the frequency or relative frequency of each value
shifting
distribution
quantitative variable
lurking variable
28. A distribution is this if the two halves on either side of the center look approximately like mirror images of each other
stem-and-leaf display
intercept
factor
symmetric
29. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
cluster sample
normal probability plot
lurking variable
voluntary response bias
30. The square root of the variance
bar chart
random assignment
sample
standard deviation
31. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
contingency table
boxplot
uniform
independence
32. The ____ we care about most is straight
strength
r2
form
conditional distribution
33. 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
voluntary response bias
normal probability plot
skewed
range
34. The most basic situation in a simulation in which something happens at random
experiment
simulation component
parameter
distribution
35. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
factor
census
z-score
area principle
36. A sample drawn by selecting individuals systematically from a sampling frame
trial
multistage sample
systematic sample
placebo
37. The distribution of either variable alone in a contingency table; the counts or percentages are the totals found in the margins (last row or column) of the table
response
marginal distribution
voluntary response bias
random
38. A numerical summary of how tightly the values are clustered around the 'center'
quartile
statistically significant
spread
leverage
39. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
center
stem-and-leaf display
bimodal
random numbers
40. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
randomization
bias
interquartile range
variable
41. 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
population parameter
context
treatment
contingency table
42. 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
regression line
5-number summary
undercoverage
random assignment
43. Design Randomization occurring within blocks
randomized block
outlier
r2
standardizing
44. A normal model with a mean of 0 and a standard deviation of 1
simulation component
independence
direction
standard normal model
45. Value calculated from data to summarize aspects of the data
experimental units
response
statistic
bar chart
46. Shows quantitative data values in a way that sketches the distribution of the data
confounded
stem-and-leaf display
histogram
completely randomized design
47. Any attempt to force a sample to resemble specified attributes of the population
predicted value
matching
treatment
outlier
48. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
simple random sample
independence
double-blind
interquartile range
49. When an observed difference is too large for us to believe that is is likely to have occurred naturally
direction
statistically significant
subset
principles of experimental design
50. The natural tendency of randomly drawn samples to differ
quantitative variable
changing center and spread
single-blind
sampling variability