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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 list of individuals from whom the sample is drawn
sampling frame
completely randomized design
variance
scatterplots
2. 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
units
quartile
standardizing
regression line
3. The number of individuals in a sample
outcome
5-number summary
bias
sample size
4. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
placebo effect
tails
data
extrapolation
5. The difference between the first and third quartiles
census
sampling variability
range
interquartile range
6. Useful family of models for unimodal - symmetric distributions
normal model
independence
population
shifting
7. Design Randomization occurring within blocks
standardized value
double-blind
voluntary response bias
randomized block
8. Consists of the individuals who are conveniently available
convenience sample
slope
boxplot
matching
9. Found by summing all the data values and dividing by the count
population
mean
population parameter
sample
10. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
outcome
5-number summary
regression to the mean
changing center and spread
11. Shows quantitative data values in a way that sketches the distribution of the data
double-blind
stem-and-leaf display
bias
boxplot
12. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
variance
population
standardizing
pie chart
13. A study based on data in which no manipulation of factors has been employed
center
level
skewed
observational study
14. When an observed difference is too large for us to believe that is is likely to have occurred naturally
experiment
random numbers
model
statistically significant
15. Doing this is equivalent to changing its units
factor
random assignment
standard deviation
changing center and spread
16. Value calculated from data to summarize aspects of the data
extrapolation
control group
simpson's paradox
statistic
17. When both those who could influence and evaluate the results are blinded
sampling frame
regression line
changing center and spread
double-blind
18. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
bimodal
boxplot
stratified random sample
regression line
19. Distributions with two modes
bimodal
context
variable
population
20. When averages are taken across different groups - they can appear to contradict the overall averages
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21. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
median
bias
scatterplots
normal probability plot
22. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
case
blinding
independence
census
23. The sequence of several components representing events that we are pretending will take place
trial
principles of experimental design
outliers
sample survey
24. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
control group
sampling variability
principles of experimental design
random numbers
25. 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
matching
matched
bimodal
representative
26. Summarized with the standard deviation - interquartile range - and range
placebo
spread
random assignment
quartile
27. A numerical summary of how tightly the values are clustered around the 'center'
form
lurking variable
spread
influential point
28. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
correlation
factor
standard deviation
voluntary response bias
29. An individual result of a component of a simulation
timeplot
outcome
symmetric
spread
30. Summarized with the mean or the median
5-number summary
predicted value
center
normal percentile
31. The ith ___ is the number that falls above i% of the data
random numbers
percentile
factor
conditional distribution
32. Values of this record the results of each trial with respect to what we were interested in
response variable
changing center and spread
rescaling
comparing distributions
33. 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
conditional distribution
multimodal
outliers
34. Any attempt to force a sample to resemble specified attributes of the population
distribution
matching
simpson's paradox
independence
35. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
observational study
z-score
frequency table
unimodal
36. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
center
regression line
shape
changing center and spread
37. Lists the categories in a categorical variable and gives the count or percentage of observations for each category
treatment
frequency table
confounded
units
38. Value found by subtracting the mean and dividing by the standard deviation
center
standardized value
standard normal model
standard deviation
39. To be valid - an experiment must assign experimental units to treatment groups at random
subset
random assignment
random
regression line
40. Gives the possible values of the variable and the frequency or relative frequency of each value
principles of experimental design
standardized value
response variable
distribution
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
simple random sample
normal probability plot
double-blind
contingency table
42. A variable that names categories (whether with words or numerals)
influential point
center
categorical variable
population parameter
43. 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
sample
factor
quantitative variable
context
44. The most basic situation in a simulation in which something happens at random
matching
simulation component
experimental units
random assignment
45. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
mode
residuals
least squares
quartile
46. When doing this - consider their shape - center - and spread
histogram
outlier
comparing distributions
experiment
47. An individual about whom or which we have data
stratified random sample
shifting
center
case
48. The difference between the lowest and highest values in a data set
range
quantitative variable
68-95-99.7 rule
bias
49. An observational study in which subjects are followed to observe future outcomes
standardizing
prospective study
tails
sample survey
50. A sample drawn by selecting individuals systematically from a sampling frame
systematic sample
randomized block
standardized value
slope