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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. All experimental units have an equal chance of receiving any treatment
completely randomized design
form
voluntary response bias
symmetric
2. Graphs a dot for each case against a single axis
dotplot
distribution
shifting
area principle
3. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
data
control group
direction
independence
4. A normal model with a mean of 0 and a standard deviation of 1
variance
influential point
sampling variability
standard normal model
5. Any attempt to force a sample to resemble specified attributes of the population
matching
stratified random sample
pie chart
randomized block
6. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
subset
influential point
area principle
residuals
7. 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
response
bias
standardizing
contingency table
8. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
r2
simulation component
re-express data
random numbers
9. Shows a bar representing the count of each category in a categorical variable
spread
bar chart
trial
statistically significant
10. When averages are taken across different groups - they can appear to contradict the overall averages
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11. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
trial
control group
stem-and-leaf display
skewed
12. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
distribution
regression line
simple random sample
spread
13. An event is this if we know what outcomes could happen - but not which particular values will happen
random
timeplot
outlier
least squares
14. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
simulation component
linear model
census
5-number summary
15. 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
statistically significant
shape
undercoverage
sample survey
16. 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
simple random sample
changing center and spread
random numbers
17. Individuals on whom an experiment is performed
stratified random sample
outlier
normal model
experimental units
18. Summarized with the standard deviation - interquartile range - and range
principles of experimental design
spread
sampling variability
statistic
19. When both those who could influence and evaluate the results are blinded
lurking variable
double-blind
completely randomized design
block
20. 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
random numbers
block
double-blind
shifting
21. Design Randomization occurring within blocks
variable
randomized block
68-95-99.7 rule
stem-and-leaf display
22. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
control group
histogram
ladder of powers
boxplot
23. Value found by subtracting the mean and dividing by the standard deviation
predicted value
standardized value
range
census
24. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
factor
cluster sample
treatment
sample size
25. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters
representative
stem-and-leaf display
range
distribution
26. An equation of the form y-hat = b0 + b1x
tails
treatment
distribution
linear model
27. A representative subset of a population - examined in hope of learning about the population
tails
quantitative variable
standardized value
sample
28. When groups of experimental units are similar - it is a good idea to gather them together into these
block
experimental units
z-score
confounded
29. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
data table
stratified random sample
spread
model
30. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
statistic
response bias
blinding
sample survey
31. Shows quantitative data values in a way that sketches the distribution of the data
statistic
matched
random
stem-and-leaf display
32. The middle value with half of the data above and half below it
subset
pie chart
boxplot
median
33. The natural tendency of randomly drawn samples to differ
sampling variability
observational study
scatterplots
placebo
34. Gives the possible values of the variable and the frequency or relative frequency of each value
boxplot
median
strength
distribution
35. The best defense against bias - in which each individual is given a fair - random chance of selection
conditional distribution
standard normal model
randomization
parameter
36. Numerically valued attribute of a model
median
parameter
single-blind
response bias
37. 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
z-score
placebo effect
context
sampling frame
38. The square root of the variance
single-blind
standard deviation
retrospective study
sampling variability
39. Systematically recorded information - whether numbers or labels - together with its context
distribution
completely randomized design
confounded
data
40. The specific values that the experimenter chooses for a factor
outlier
level
form
standardized value
41. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
voluntary response bias
experimental units
simpson's paradox
lurking variable
42. A sampling design in which entire groups are chosen at random
prospective study
lurking variable
interquartile range
cluster sample
43. A hump or local high point in the shape of the distribution of a variable; the apparent locations of these can change as the scale of a histogram is changed
mode
randomized block
undercoverage
scatterplots
44. 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
standard deviation
r2
68-95-99.7 rule
center
45. Gives the possible values of the variable and the relative frequency of each value
area principle
timeplot
distribution
undercoverage
46. A variable in which the numbers act as numerical values; always has units
outcome
quantitative variable
experimental units
normal probability plot
47. The distribution of a variable restricting the who to consider only a smaller group of individuals
uniform
conditional distribution
response bias
r2
48. Lists the categories in a categorical variable and gives the count or percentage of observations for each category
outlier
standard normal model
frequency table
intercept
49. The difference between the first and third quartiles
interquartile range
comparing distributions
residuals
randomization
50. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
outlier
nonresponse bias
multimodal
double-blind