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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 normal model with a mean of 0 and a standard deviation of 1
variance
standard normal model
bimodal
sample size
2. A sampling design in which entire groups are chosen at random
conditional distribution
cluster sample
matched
representative
3. Displays data that change over time
timeplot
randomized block
model
factor
4. 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
experimental units
sample survey
contingency table
normal percentile
5. When an observed difference is too large for us to believe that is is likely to have occurred naturally
statistically significant
center
standard normal model
spread
6. A distribution that's roughly flat
sample survey
uniform
random
residuals
7. When omitting a point from the data results in a very different regression model - the point is an ____
sampling frame
representative
influential point
randomized block
8. An equation of the form y-hat = b0 + b1x
regression to the mean
standardizing
linear model
percentile
9. Values of this record the results of each trial with respect to what we were interested in
bias
cluster sample
least squares
response variable
10. A sample that consists of the entire population
standard deviation
census
bimodal
bias
11. An equation or formula that simplifies and represents reality
random numbers
linear model
context
model
12. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
double-blind
residuals
normal percentile
tails
13. A numerical measure of the direction and strength of a linear association
correlation
population parameter
z-score
statistically significant
14. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
center
response variable
rescaling
68-95-99.7 rule
15. Gives the possible values of the variable and the frequency or relative frequency of each value
distribution
normal model
lurking variable
least squares
16. The sequence of several components representing events that we are pretending will take place
conditional distribution
shifting
regression to the mean
trial
17. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
random numbers
variable
timeplot
z-score
18. Gives the possible values of the variable and the relative frequency of each value
mean
distribution
variance
experiment
19. Places in order the effects that many re-expressions have on the data
systematic sample
randomized block
ladder of powers
completely randomized design
20. A distribution is this if it's not symmetric and one tail stretches out farther than the other
center
trial
skewed
sampling variability
21. The middle value with half of the data above and half below it
response variable
median
multistage sample
distribution
22. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
z-score
retrospective study
variance
standardizing
23. An event is this if we know what outcomes could happen - but not which particular values will happen
bar chart
random
statistic
completely randomized design
24. Found by substituting the x-value in the regression equation; they're the values on the fitted line
area principle
predicted value
boxplot
sample survey
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
predicted value
center
matched
sample survey
26. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
influential point
treatment
correlation
independence
27. Value calculated from data to summarize aspects of the data
retrospective study
regression to the mean
statistic
normal probability plot
28. Shows the relationship between two quantitative variables measured on the same cases
sample size
normal model
random assignment
scatterplots
29. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
units
median
outliers
form
30. Design Randomization occurring within blocks
percentile
randomized block
sampling frame
5-number summary
31. When groups of experimental units are similar - it is a good idea to gather them together into these
stem-and-leaf display
block
quantitative variable
timeplot
32. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
spread
random
blinding
regression line
33. A numerically valued attribute of a model for a population
contingency table
population parameter
independence
standardizing
34. An observational study in which subjects are followed to observe future outcomes
area principle
prospective study
confounded
census
35. A sample drawn by selecting individuals systematically from a sampling frame
categorical variable
observational study
systematic sample
normal model
36. Graphs a dot for each case against a single axis
data
influential point
scatterplots
dotplot
37. Sampling schemes that combine several sampling methods
influential point
control group
multistage sample
unimodal
38. Numerically valued attribute of a model
categorical variable
parameter
standard normal model
rescaling
39. The specific values that the experimenter chooses for a factor
outlier
multimodal
level
influential point
40. Found by summing all the data values and dividing by the count
mean
tails
conditional distribution
standardizing
41. 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
bias
simulation
form
timeplot
42. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
stratified random sample
treatment
data table
spread
43. Shows quantitative data values in a way that sketches the distribution of the data
principles of experimental design
normal model
statistic
stem-and-leaf display
44. A variable that names categories (whether with words or numerals)
categorical variable
lurking variable
observational study
retrospective study
45. A variable whose levels are controlled by the experimenter
interquartile range
factor
sample survey
response variable
46. Distributions with two modes
bimodal
spread
completely randomized design
categorical variable
47. A point that does not fit the overall pattern seen in the scatterplot
standard deviation
regression line
outlier
randomized block
48. Shows a bar representing the count of each category in a categorical variable
sample size
correlation
bar chart
variable
49. The most basic situation in a simulation in which something happens at random
population
retrospective study
simulation component
context
50. The natural tendency of randomly drawn samples to differ
outliers
sampling variability
bimodal
response variable