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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 sample that consists of the entire population
census
boxplot
randomization
least squares
2. An individual about whom or which we have data
standard deviation
model
undercoverage
case
3. 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
units
leverage
rescaling
case
4. A distribution is this if the two halves on either side of the center look approximately like mirror images of each other
normal model
residuals
center
symmetric
5. A sampling design in which entire groups are chosen at random
pie chart
subset
lurking variable
cluster sample
6. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
median
linear model
regression to the mean
placebo effect
7. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
influential point
case
randomization
control group
8. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
regression to the mean
boxplot
correlation
conditional distribution
9. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
form
tails
mean
retrospective study
10. The specific values that the experimenter chooses for a factor
level
prospective study
intercept
matching
11. Values of this record the results of each trial with respect to what we were interested in
response variable
range
z-score
cluster sample
12. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
residuals
data
outlier
census
13. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
center
stem-and-leaf display
rescaling
placebo
14. The best defense against bias - in which each individual is given a fair - random chance of selection
comparing distributions
principles of experimental design
shifting
randomization
15. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
comparing distributions
intercept
shape
lurking variable
16. Numerically valued attribute of a model
normal percentile
parameter
re-express data
independence
17. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
distribution
trial
interquartile range
strength
18. A numerically valued attribute of a model for a population
population parameter
sample
double-blind
re-express data
19. To be valid - an experiment must assign experimental units to treatment groups at random
timeplot
linear model
standard deviation
random assignment
20. The difference between the lowest and highest values in a data set
range
sampling variability
conditional distribution
outlier
21. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
units
least squares
outlier
quartile
22. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
influential point
bimodal
voluntary response bias
response
23. In a statistical display - each data value should be represented by the same amount of area
boxplot
area principle
uniform
r2
24. An observational study in which subjects are followed to observe future outcomes
cluster sample
standard deviation
prospective study
nonresponse bias
25. Shows a bar representing the count of each category in a categorical variable
population
random
bar chart
blinding
26. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
spread
z-score
control group
lurking variable
27. The distribution of a variable restricting the who to consider only a smaller group of individuals
random numbers
conditional distribution
tails
direction
28. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
regression to the mean
quartile
level
experimental units
29. Useful family of models for unimodal - symmetric distributions
model
normal model
normal probability plot
form
30. A treatment known to have no effect - administered so that all groups experience the same conditions
simple random sample
placebo
linear model
normal model
31. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
simulation component
outcome
standardizing
statistic
32. Gives the possible values of the variable and the relative frequency of each value
distribution
histogram
multistage sample
standardized value
33. The natural tendency of randomly drawn samples to differ
sampling variability
interquartile range
r2
factor
34. 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
single-blind
median
blinding
r2
35. Places in order the effects that many re-expressions have on the data
blinding
tails
ladder of powers
5-number summary
36. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
trial
median
simple random sample
treatment
37. An equation of the form y-hat = b0 + b1x
linear model
sampling frame
principles of experimental design
model
38. In a normal model - about 68% of values fall within 1 standard deviation of the mean - about 95% fall within 2 standard deviations of the mean - and about 99.7% fall within 3 standard deviations of the mean
center
multistage sample
ladder of powers
68-95-99.7 rule
39. Design Randomization occurring within blocks
leverage
randomized block
units
outliers
40. Shows the relationship between two quantitative variables measured on the same cases
bimodal
control group
bar chart
scatterplots
41. 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
extrapolation
contingency table
blinding
normal model
42. The middle value with half of the data above and half below it
median
convenience sample
confounded
center
43. Summarized with the mean or the median
statistically significant
68-95-99.7 rule
center
stratified random sample
44. The sequence of several components representing events that we are pretending will take place
trial
response variable
subset
bias
45. The number of individuals in a sample
residuals
level
randomization
sample size
46. The parts of a distribution that typically trail off on either side; they can be characterized as long or short
confounded
tails
census
standardized value
47. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
bias
parameter
stratified random sample
completely randomized design
48. Distributions with more than two modes
multimodal
block
center
control group
49. Lists the categories in a categorical variable and gives the count or percentage of observations for each category
leverage
frequency table
direction
nonresponse bias
50. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
spread
z-score
percentile
placebo