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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. When either those who could influence or evaluate the results is blinded
single-blind
voluntary response bias
comparing distributions
strength
2. The natural tendency of randomly drawn samples to differ
r2
trial
sampling variability
variance
3. 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
linear model
matched
correlation
least squares
4. 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
mode
r2
principles of experimental design
simulation
5. Consists of the individuals who are conveniently available
regression to the mean
convenience sample
bias
single-blind
6. A list of individuals from whom the sample is drawn
matching
outcome
treatment
sampling frame
7. The specific values that the experimenter chooses for a factor
outcome
r2
level
observational study
8. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
regression to the mean
lurking variable
context
intercept
9. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below
normal percentile
residuals
regression line
histogram
10. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant
regression line
multistage sample
completely randomized design
rescaling
11. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
changing center and spread
statistically significant
nonresponse bias
outlier
12. When both those who could influence and evaluate the results are blinded
population
double-blind
spread
completely randomized design
13. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
shape
population
control group
sample survey
14. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
bias
histogram
standardizing
random
15. A point that does not fit the overall pattern seen in the scatterplot
ladder of powers
outlier
variance
quantitative variable
16. The sum of squared deviations from the mean - divided by the count minus one
matched
experimental units
variance
categorical variable
17. The number of individuals in a sample
experiment
predicted value
regression to the mean
sample size
18. An equation or formula that simplifies and represents reality
model
level
sampling frame
matched
19. Design Randomization occurring within blocks
normal probability plot
undercoverage
randomized block
area principle
20. Systematically recorded information - whether numbers or labels - together with its context
normal model
data
random assignment
units
21. Summarized with the standard deviation - interquartile range - and range
changing center and spread
control group
spread
simpson's paradox
22. The middle value with half of the data above and half below it
lurking variable
median
variance
r2
23. The best defense against bias - in which each individual is given a fair - random chance of selection
intercept
randomization
retrospective study
rescaling
24. 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
convenience sample
experiment
dotplot
randomized block
25. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters
statistically significant
quartile
representative
area principle
26. Summarized with the mean or the median
spread
center
population
random numbers
27. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
quartile
simulation
sample size
center
28. 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
regression line
conditional distribution
subset
dotplot
29. A sample drawn by selecting individuals systematically from a sampling frame
z-score
systematic sample
outlier
matched
30. 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
changing center and spread
unimodal
marginal distribution
blinding
31. Graphs a dot for each case against a single axis
distribution
form
dotplot
single-blind
32. 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
undercoverage
blinding
systematic sample
simulation
33. A distribution is this if it's not symmetric and one tail stretches out farther than the other
experimental units
skewed
sampling variability
normal percentile
34. When an observed difference is too large for us to believe that is is likely to have occurred naturally
retrospective study
statistically significant
factor
regression to the mean
35. Extreme values that don't appear to belong with the rest of the data
frequency table
least squares
randomized block
outliers
36. The difference between the lowest and highest values in a data set
sample survey
range
center
census
37. In a statistical display - each data value should be represented by the same amount of area
form
conditional distribution
simulation component
area principle
38. A variable in which the numbers act as numerical values; always has units
quantitative variable
sampling variability
5-number summary
form
39. The parts of a distribution that typically trail off on either side; they can be characterized as long or short
r2
residuals
tails
lurking variable
40. 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
random
mode
normal probability plot
block
41. An individual about whom or which we have data
random
conditional distribution
census
case
42. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
standardizing
subset
case
median
43. A representative subset of a population - examined in hope of learning about the population
bias
sample
voluntary response bias
confounded
44. An individual result of a component of a simulation
simple random sample
outcome
shape
variance
45. A variable whose values are compared across different treatments
response
variable
response bias
5-number summary
46. Found by summing all the data values and dividing by the count
bias
mean
contingency table
population parameter
47. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
units
residuals
standardized value
outliers
48. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
population
shape
placebo
statistically significant
49. A treatment known to have no effect - administered so that all groups experience the same conditions
lurking variable
form
placebo
timeplot
50. Doing this is equivalent to changing its units
standard deviation
changing center and spread
simpson's paradox
quartile