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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. Displays data that change over time
experimental units
response bias
interquartile range
timeplot
2. Numerically valued attribute of a model
interquartile range
trial
parameter
slope
3. Gives the possible values of the variable and the frequency or relative frequency of each value
response variable
sampling frame
blinding
distribution
4. A study based on data in which no manipulation of factors has been employed
observational study
experimental units
shape
rescaling
5. An event is this if we know what outcomes could happen - but not which particular values will happen
trial
matched
percentile
random
6. 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
mode
68-95-99.7 rule
prospective study
matched
7. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
statistically significant
simple random sample
histogram
outlier
8. Extreme values that don't appear to belong with the rest of the data
uniform
single-blind
normal probability plot
outliers
9. The entire group of individuals or instances about whom we hope to learn
68-95-99.7 rule
case
cluster sample
population
10. 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
center
contingency table
systematic sample
block
11. 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
re-express data
shifting
quartile
extrapolation
12. 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
context
normal probability plot
model
control group
13. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
stem-and-leaf display
regression line
placebo
bias
14. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
single-blind
simulation component
randomized block
stratified random sample
15. When an observed difference is too large for us to believe that is is likely to have occurred naturally
statistically significant
area principle
data
bias
16. A variable whose levels are controlled by the experimenter
bimodal
area principle
experiment
factor
17. A sample drawn by selecting individuals systematically from a sampling frame
placebo effect
parameter
randomization
systematic sample
18. Uses adjacent bars to show the distribution of vales in a quantitative variable; each bar represents the frequency (or relative frequency) of values falling in an interval of values
spread
principles of experimental design
timeplot
histogram
19. An individual result of a component of a simulation
interquartile range
center
outcome
form
20. The sequence of several components representing events that we are pretending will take place
range
data table
outliers
trial
21. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
simple random sample
sampling variability
nonresponse bias
dotplot
22. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant
randomized block
rescaling
mode
pie chart
23. The middle value with half of the data above and half below it
stratified random sample
cluster sample
matching
median
24. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
boxplot
convenience sample
histogram
shifting
25. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
data
independence
parameter
cluster sample
26. In a statistical display - each data value should be represented by the same amount of area
area principle
frequency table
histogram
random assignment
27. A variable whose values are compared across different treatments
simpson's paradox
random
unimodal
response
28. 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
68-95-99.7 rule
mode
extrapolation
statistically significant
29. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
confounded
interquartile range
multistage sample
model
30. The natural tendency of randomly drawn samples to differ
bimodal
sampling variability
conditional distribution
experiment
31. Distributions with two modes
response variable
level
spread
bimodal
32. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below
normal percentile
outliers
simulation component
scatterplots
33. Doing this is equivalent to changing its units
random assignment
bias
parameter
changing center and spread
34. A distribution that's roughly flat
uniform
outliers
random assignment
bimodal
35. A point that does not fit the overall pattern seen in the scatterplot
factor
regression line
outlier
median
36. Places in order the effects that many re-expressions have on the data
ladder of powers
68-95-99.7 rule
distribution
outlier
37. The sum of squared deviations from the mean - divided by the count minus one
sampling variability
variance
sample survey
rescaling
38. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
simpson's paradox
least squares
retrospective study
68-95-99.7 rule
39. Values of this record the results of each trial with respect to what we were interested in
matching
response variable
placebo effect
unimodal
40. 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
comparing distributions
undercoverage
random
contingency table
41. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
placebo effect
outcome
units
random numbers
42. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
observational study
treatment
census
statistic
43. When averages are taken across different groups - they can appear to contradict the overall averages
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44. When both those who could influence and evaluate the results are blinded
response bias
double-blind
placebo
simpson's paradox
45. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
range
population
lurking variable
regression line
46. A numerical measure of the direction and strength of a linear association
correlation
outlier
factor
changing center and spread
47. A list of individuals from whom the sample is drawn
sampling frame
matched
interquartile range
trial
48. If data consist of two or more groups that have been thrown together - it is usually best to fit different linear models to each group than to try to fit a single model to all of the data
single-blind
influential point
subset
normal percentile
49. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
lurking variable
shape
experiment
mean
50. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
mode
simple random sample
regression to the mean
standardized value