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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. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
intercept
shifting
trial
z-score
2. Displays data that change over time
sample survey
timeplot
completely randomized design
control group
3. The ____ we care about most is straight
form
regression line
stem-and-leaf display
intercept
4. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
blinding
bias
undercoverage
center
5. Summarized with the standard deviation - interquartile range - and range
spread
model
randomization
regression to the mean
6. Lists the categories in a categorical variable and gives the count or percentage of observations for each category
strength
frequency table
correlation
undercoverage
7. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
symmetric
data table
placebo effect
mean
8. The sum of squared deviations from the mean - divided by the count minus one
independence
dotplot
standard normal model
variance
9. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
distribution
regression line
cluster sample
statistically significant
10. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters
quartile
retrospective study
statistically significant
representative
11. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
residuals
confounded
timeplot
slope
12. The difference between the lowest and highest values in a data set
stratified random sample
standardized value
intercept
range
13. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
randomization
contingency table
least squares
re-express data
14. The parts of a distribution that typically trail off on either side; they can be characterized as long or short
sampling variability
sample size
z-score
tails
15. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population
sample survey
bar chart
quartile
predicted value
16. Summarized with the mean or the median
center
r2
blinding
lurking variable
17. A variable in which the numbers act as numerical values; always has units
correlation
slope
quantitative variable
5-number summary
18. Sampling schemes that combine several sampling methods
experiment
principles of experimental design
multistage sample
68-95-99.7 rule
19. A treatment known to have no effect - administered so that all groups experience the same conditions
placebo
predicted value
stem-and-leaf display
statistically significant
20. Gives the possible values of the variable and the frequency or relative frequency of each value
voluntary response bias
bimodal
distribution
normal model
21. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
units
unimodal
single-blind
stratified random sample
22. A numerically valued attribute of a model for a population
response
population parameter
uniform
independence
23. The natural tendency of randomly drawn samples to differ
68-95-99.7 rule
sampling frame
shape
sampling variability
24. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
timeplot
quartile
68-95-99.7 rule
regression to the mean
25. When doing this - consider their shape - center - and spread
lurking variable
comparing distributions
quantitative variable
re-express data
26. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
placebo
range
nonresponse bias
standardizing
27. 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
outliers
context
random
uniform
28. An event is this if we know what outcomes could happen - but not which particular values will happen
random
completely randomized design
data table
histogram
29. Shows a bar representing the count of each category in a categorical variable
bar chart
block
correlation
convenience sample
30. Graphs a dot for each case against a single axis
lurking variable
independence
model
dotplot
31. Found by substituting the x-value in the regression equation; they're the values on the fitted line
predicted value
shape
normal model
z-score
32. 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
randomized block
leverage
strength
68-95-99.7 rule
33. A normal model with a mean of 0 and a standard deviation of 1
standard normal model
boxplot
range
quantitative variable
34. A numerical summary of how tightly the values are clustered around the 'center'
spread
parameter
simpson's paradox
shifting
35. Shows the relationship between two quantitative variables measured on the same cases
randomization
marginal distribution
retrospective study
scatterplots
36. Found by summing all the data values and dividing by the count
undercoverage
quartile
center
mean
37. A sample that consists of the entire population
census
factor
blinding
sample
38. Values of this record the results of each trial with respect to what we were interested in
quantitative variable
response variable
sampling frame
multimodal
39. Design Randomization occurring within blocks
randomized block
normal model
stem-and-leaf display
simulation
40. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
stratified random sample
skewed
voluntary response bias
range
41. 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
mode
least squares
cluster sample
range
42. The distribution of either variable alone in a contingency table; the counts or percentages are the totals found in the margins (last row or column) of the table
conditional distribution
bar chart
distribution
marginal distribution
43. The ith ___ is the number that falls above i% of the data
observational study
percentile
symmetric
subset
44. When averages are taken across different groups - they can appear to contradict the overall averages
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45. A sampling design in which entire groups are chosen at random
double-blind
cluster sample
census
retrospective study
46. 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
observational study
simulation
stem-and-leaf display
case
47. Consists of the individuals who are conveniently available
simulation
convenience sample
prospective study
percentile
48. A study based on data in which no manipulation of factors has been employed
experiment
center
units
observational study
49. A variable whose values are compared across different treatments
data table
percentile
convenience sample
response
50. An equation of the form y-hat = b0 + b1x
simpson's paradox
least squares
center
linear model