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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. Anything in a survey design that influences response
response bias
scatterplots
sample
placebo
2. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
level
principles of experimental design
bias
voluntary response bias
3. Sampling schemes that combine several sampling methods
observational study
normal probability plot
multistage sample
center
4. Shows a bar representing the count of each category in a categorical variable
interquartile range
sampling frame
response
bar chart
5. A distribution that's roughly flat
uniform
population
percentile
subset
6. Found by substituting the x-value in the regression equation; they're the values on the fitted line
cluster sample
dotplot
predicted value
r2
7. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
ladder of powers
standardizing
shifting
outlier
8. When either those who could influence or evaluate the results is blinded
simulation
nonresponse bias
matching
single-blind
9. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
double-blind
form
matched
z-score
10. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
center
blinding
statistically significant
confounded
11. The ____ we care about most is straight
regression line
normal probability plot
comparing distributions
form
12. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
variance
direction
simple random sample
level
13. 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
bar chart
bimodal
shifting
simulation component
14. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
census
data table
lurking variable
subset
15. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
contingency table
single-blind
standardized value
stratified random sample
16. A list of individuals from whom the sample is drawn
spread
comparing distributions
pie chart
sampling frame
17. When both those who could influence and evaluate the results are blinded
leverage
completely randomized design
systematic sample
double-blind
18. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
scatterplots
control group
simulation component
correlation
19. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters
model
completely randomized design
representative
data
20. The difference between the first and third quartiles
percentile
uniform
least squares
interquartile range
21. 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
matching
systematic sample
unimodal
mode
22. 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
stratified random sample
quartile
comparing distributions
simulation
23. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
normal model
voluntary response bias
standardizing
intercept
24. The entire group of individuals or instances about whom we hope to learn
contingency table
population
matching
simpson's paradox
25. A variable whose values are compared across different treatments
pie chart
response
systematic sample
scatterplots
26. A distribution is this if it's not symmetric and one tail stretches out farther than the other
sample size
skewed
response variable
confounded
27. 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
undercoverage
randomized block
statistically significant
bar chart
28. Values of this record the results of each trial with respect to what we were interested in
standardized value
response variable
trial
outlier
29. When an observed difference is too large for us to believe that is is likely to have occurred naturally
uniform
unimodal
statistically significant
principles of experimental design
30. The specific values that the experimenter chooses for a factor
unimodal
level
matching
sampling variability
31. Useful family of models for unimodal - symmetric distributions
categorical variable
sampling variability
model
normal model
32. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below
outlier
normal percentile
independence
outlier
33. In a statistical display - each data value should be represented by the same amount of area
slope
normal model
sample
area principle
34. Numerically valued attribute of a model
parameter
boxplot
statistic
uniform
35. An individual result of a component of a simulation
outcome
control group
conditional distribution
contingency table
36. A sample drawn by selecting individuals systematically from a sampling frame
strength
completely randomized design
random numbers
systematic sample
37. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
multimodal
conditional distribution
sample survey
bias
38. A representative subset of a population - examined in hope of learning about the population
sample
shape
principles of experimental design
subset
39. Control - randomize - replicate - block
lurking variable
principles of experimental design
simple random sample
area principle
40. Graphs a dot for each case against a single axis
double-blind
dotplot
standardizing
completely randomized design
41. The middle value with half of the data above and half below it
frequency table
spread
uniform
median
42. The natural tendency of randomly drawn samples to differ
unimodal
frequency table
simulation component
sampling variability
43. An event is this if we know what outcomes could happen - but not which particular values will happen
case
sampling variability
random
correlation
44. The number of individuals in a sample
outcome
sample size
unimodal
systematic sample
45. Distributions with two modes
simulation
units
bimodal
leverage
46. 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
lurking variable
control group
influential point
extrapolation
47. Any attempt to force a sample to resemble specified attributes of the population
census
matching
population
shape
48. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
outcome
independence
mean
slope
49. Places in order the effects that many re-expressions have on the data
response
ladder of powers
model
strength
50. Gives the possible values of the variable and the relative frequency of each value
distribution
spread
blinding
shifting