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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. Extreme values that don't appear to belong with the rest of the data
outliers
unimodal
form
spread
2. Found by summing all the data values and dividing by the count
context
mean
shape
bar chart
3. The difference between the first and third quartiles
interquartile range
undercoverage
shifting
systematic sample
4. 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
randomized block
principles of experimental design
linear model
leverage
5. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
strength
census
shape
case
6. Places in order the effects that many re-expressions have on the data
random
matching
pie chart
ladder of powers
7. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
normal model
mean
5-number summary
experiment
8. A distribution that's roughly flat
case
population parameter
uniform
interquartile range
9. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
re-express data
matched
z-score
population parameter
10. Anything in a survey design that influences response
response bias
simulation
68-95-99.7 rule
regression to the mean
11. Bias introduced to a sample when a large fraction of those sampled fails to respond
census
voluntary response bias
nonresponse bias
bimodal
12. An arrangement of data in which each row represents a case and each column represents a variable
data table
principles of experimental design
spread
cluster sample
13. Numerically valued attribute of a model
quantitative variable
parameter
treatment
contingency table
14. A study based on data in which no manipulation of factors has been employed
observational study
quartile
dotplot
normal percentile
15. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
placebo effect
sample survey
mean
histogram
16. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
sampling variability
voluntary response bias
direction
pie chart
17. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
re-express data
data
distribution
outlier
18. An observational study in which subjects are followed to observe future outcomes
regression to the mean
prospective study
timeplot
bias
19. The lower of this is the value with a quarter of the data below it; the upper of this has a quarter of the data above it
model
data
parameter
quartile
20. 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
categorical variable
matched
variable
bar chart
21. When an observed difference is too large for us to believe that is is likely to have occurred naturally
randomization
random
statistically significant
response variable
22. The natural tendency of randomly drawn samples to differ
sampling variability
random numbers
variance
simple random sample
23. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
leverage
histogram
units
nonresponse bias
24. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
experiment
linear model
bias
lurking variable
25. The sequence of several components representing events that we are pretending will take place
trial
contingency table
lurking variable
population parameter
26. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
symmetric
timeplot
bias
extrapolation
27. Summarized with the mean or the median
prospective study
trial
center
mean
28. Value found by subtracting the mean and dividing by the standard deviation
nonresponse bias
single-blind
center
standardized value
29. 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
population
mode
direction
simulation
30. Graphs a dot for each case against a single axis
skewed
distribution
dotplot
tails
31. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
unimodal
statistic
center
convenience sample
32. Distributions with more than two modes
center
prospective study
experiment
multimodal
33. 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
r2
normal probability plot
undercoverage
shape
34. 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
level
spread
multistage sample
shifting
35. Sampling schemes that combine several sampling methods
standardized value
multistage sample
simple random sample
random numbers
36. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
stratified random sample
treatment
r2
regression line
37. When omitting a point from the data results in a very different regression model - the point is an ____
experiment
normal probability plot
completely randomized design
influential point
38. Lists the categories in a categorical variable and gives the count or percentage of observations for each category
interquartile range
changing center and spread
frequency table
conditional distribution
39. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
comparing distributions
retrospective study
z-score
r2
40. The ____ we care about most is straight
form
sample size
population
ladder of powers
41. When averages are taken across different groups - they can appear to contradict the overall averages
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42. When groups of experimental units are similar - it is a good idea to gather them together into these
68-95-99.7 rule
block
placebo effect
quantitative variable
43. Found by substituting the x-value in the regression equation; they're the values on the fitted line
comparing distributions
simulation
predicted value
correlation
44. A positive ____ or association means that - in general - as one variable increases - so does the other; when increases in one variable generally correspond to decreases in the other - the association is negative
randomized block
blinding
placebo effect
direction
45. Individuals on whom an experiment is performed
simpson's paradox
experimental units
spread
normal model
46. The best defense against bias - in which each individual is given a fair - random chance of selection
outliers
boxplot
randomization
spread
47. 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
symmetric
slope
statistically significant
48. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
prospective study
normal percentile
random assignment
outlier
49. 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
lurking variable
marginal distribution
stem-and-leaf display
units
50. Shows quantitative data values in a way that sketches the distribution of the data
linear model
stem-and-leaf display
level
distribution