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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 study based on data in which no manipulation of factors has been employed
random assignment
simulation
contingency table
observational study
2. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
boxplot
lurking variable
simpson's paradox
principles of experimental design
3. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
extrapolation
regression line
random
contingency table
4. An equation of the form y-hat = b0 + b1x
linear model
r2
outcome
mode
5. An arrangement of data in which each row represents a case and each column represents a variable
uniform
data table
direction
statistically significant
6. Extreme values that don't appear to belong with the rest of the data
stem-and-leaf display
outliers
distribution
68-95-99.7 rule
7. The parts of a distribution that typically trail off on either side; they can be characterized as long or short
tails
matched
categorical variable
unimodal
8. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
control group
population
retrospective study
census
9. The specific values that the experimenter chooses for a factor
lurking variable
level
simpson's paradox
percentile
10. The middle value with half of the data above and half below it
changing center and spread
multistage sample
trial
median
11. When averages are taken across different groups - they can appear to contradict the overall averages
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12. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
marginal distribution
standard normal model
linear model
simple random sample
13. Lists the categories in a categorical variable and gives the count or percentage of observations for each category
dotplot
frequency table
treatment
form
14. 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
subset
normal model
percentile
random numbers
15. The sum of squared deviations from the mean - divided by the count minus one
leverage
normal model
variance
median
16. A representative subset of a population - examined in hope of learning about the population
outlier
sample
marginal distribution
context
17. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
residuals
area principle
model
ladder of powers
18. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
linear model
outlier
nonresponse bias
standardizing
19. 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
case
statistic
mode
independence
20. Value calculated from data to summarize aspects of the data
symmetric
statistic
response variable
sample size
21. The best defense against bias - in which each individual is given a fair - random chance of selection
randomization
population parameter
histogram
slope
22. Systematically recorded information - whether numbers or labels - together with its context
data
sample
outliers
principles of experimental design
23. The number of individuals in a sample
distribution
sample size
regression to the mean
variable
24. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
stratified random sample
median
lurking variable
completely randomized design
25. When either those who could influence or evaluate the results is blinded
extrapolation
least squares
simple random sample
single-blind
26. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
stratified random sample
shape
blinding
distribution
27. A variable in which the numbers act as numerical values; always has units
quantitative variable
normal probability plot
independence
outlier
28. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
boxplot
voluntary response bias
stratified random sample
lurking variable
29. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
5-number summary
level
uniform
outlier
30. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
center
5-number summary
bar chart
simple random sample
31. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
sample survey
shifting
z-score
population parameter
32. 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
scatterplots
randomization
r2
frequency table
33. A sampling design in which entire groups are chosen at random
control group
cluster sample
pie chart
timeplot
34. The difference between the lowest and highest values in a data set
stem-and-leaf display
model
shape
range
35. When groups of experimental units are similar - it is a good idea to gather them together into these
double-blind
multimodal
block
mode
36. A sample drawn by selecting individuals systematically from a sampling frame
normal probability plot
systematic sample
spread
spread
37. Anything in a survey design that influences response
standard deviation
response bias
regression to the mean
leverage
38. 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
convenience sample
placebo effect
context
5-number summary
39. 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
frequency table
level
shifting
outcome
40. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
distribution
population parameter
block
stratified random sample
41. Shows the relationship between two quantitative variables measured on the same cases
normal percentile
shifting
sampling variability
scatterplots
42. Distributions with two modes
pie chart
factor
frequency table
bimodal
43. Consists of the individuals who are conveniently available
prospective study
r2
convenience sample
retrospective study
44. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
spread
stem-and-leaf display
re-express data
single-blind
45. Individuals on whom an experiment is performed
percentile
distribution
experimental units
quantitative variable
46. The difference between the first and third quartiles
changing center and spread
experimental units
interquartile range
residuals
47. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
r2
principles of experimental design
lurking variable
simulation
48. A display to help assess whether a distribution of data is approximately normal; if it is nearly straight - the data satisfy the nearly normal condition
nonresponse bias
form
simpson's paradox
normal probability plot
49. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
least squares
simple random sample
factor
dotplot
50. Displays data that change over time
block
timeplot
standard deviation
pie chart