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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. 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
prospective study
marginal distribution
trial
sample size
2. The sequence of several components representing events that we are pretending will take place
contingency table
scatterplots
trial
treatment
3. The difference between the lowest and highest values in a data set
range
standard deviation
cluster sample
least squares
4. A numerically valued attribute of a model for a population
randomization
mode
population parameter
multimodal
5. Systematically recorded information - whether numbers or labels - together with its context
conditional distribution
extrapolation
simulation
data
6. An equation or formula that simplifies and represents reality
model
distribution
range
trial
7. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
multimodal
distribution
treatment
response variable
8. 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
matched
tails
control group
observational study
9. The parts of a distribution that typically trail off on either side; they can be characterized as long or short
randomization
timeplot
tails
categorical variable
10. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
5-number summary
random numbers
mode
normal probability plot
11. An individual about whom or which we have data
randomized block
case
principles of experimental design
statistically significant
12. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population
trial
least squares
sample survey
variance
13. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
residuals
intercept
direction
simulation component
14. Bias introduced to a sample when a large fraction of those sampled fails to respond
nonresponse bias
mean
standardized value
re-express data
15. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters
representative
regression to the mean
random
cluster sample
16. A sampling scheme that biases the sample in a way that gives a part of the population less representation than it has in the population
undercoverage
median
voluntary response bias
simpson's paradox
17. 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
sampling frame
variance
stem-and-leaf display
normal probability plot
18. When either those who could influence or evaluate the results is blinded
representative
response bias
single-blind
stratified random sample
19. Anything in a survey design that influences response
correlation
z-score
response bias
spread
20. When doing this - consider their shape - center - and spread
statistically significant
slope
randomized block
comparing distributions
21. Manipulates factor levels to create treatments - randomly assigns subjects to these treatment levels - and then compares the responses of the subject groups across treatment levels
experiment
multimodal
response
lurking variable
22. Uses adjacent bars to show the distribution of vales in a quantitative variable; each bar represents the frequency (or relative frequency) of values falling in an interval of values
least squares
block
histogram
symmetric
23. To be valid - an experiment must assign experimental units to treatment groups at random
stem-and-leaf display
percentile
random assignment
direction
24. The distribution of a variable restricting the who to consider only a smaller group of individuals
model
normal percentile
conditional distribution
independence
25. An observational study in which subjects are followed to observe future outcomes
r2
prospective study
center
data table
26. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
r2
random
spread
strength
27. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
influential point
spread
residuals
experimental units
28. Gives a value in 'y-units per x-unit'; changes of one unit in x are associated with changes of b1 units in predicted values of y
slope
sampling frame
block
experiment
29. 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
representative
normal percentile
r2
random numbers
30. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
retrospective study
statistic
re-express data
factor
31. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
experimental units
trial
retrospective study
blinding
32. A variable in which the numbers act as numerical values; always has units
slope
quantitative variable
nonresponse bias
multistage sample
33. A normal model with a mean of 0 and a standard deviation of 1
response
standardizing
standard normal model
skewed
34. Although linear models provide an easy way to predict values of y for a given value of x - it is unsafe to predict for values of x far from the ones used to find the linear model equation; predictions should not be trusted
treatment
outlier
extrapolation
principles of experimental design
35. 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
timeplot
bar chart
mode
distribution
36. A variable whose levels are controlled by the experimenter
outliers
random assignment
shape
factor
37. A point that does not fit the overall pattern seen in the scatterplot
data table
outlier
lurking variable
undercoverage
38. 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
predicted value
marginal distribution
normal model
contingency table
39. Shows the relationship between two quantitative variables measured on the same cases
independence
scatterplots
skewed
boxplot
40. A representative subset of a population - examined in hope of learning about the population
sample
z-score
sample size
area principle
41. The ith ___ is the number that falls above i% of the data
predicted value
percentile
outcome
treatment
42. A study based on data in which no manipulation of factors has been employed
units
timeplot
rescaling
observational study
43. Doing this is equivalent to changing its units
changing center and spread
context
percentile
convenience sample
44. The square root of the variance
unimodal
standard deviation
units
experimental units
45. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
slope
placebo effect
sampling frame
range
46. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
unimodal
matched
distribution
mean
47. A sample that consists of the entire population
area principle
boxplot
multimodal
census
48. 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
random numbers
marginal distribution
simulation
matching
49. Found by substituting the x-value in the regression equation; they're the values on the fitted line
interquartile range
placebo
strength
predicted value
50. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
center
single-blind
simpson's paradox
simple random sample