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Test your basic knowledge |
AP Statistics Vocab
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Subjects
:
statistics
,
ap
Instructions:
Answer 50 questions in 15 minutes.
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.
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. Individuals on whom an experiment is performed
matching
parameter
experimental units
stratified random sample
2. 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
sampling variability
population parameter
context
scatterplots
3. A variable that names categories (whether with words or numerals)
center
data table
categorical variable
block
4. Found by summing all the data values and dividing by the count
model
mean
linear model
random
5. The difference between the lowest and highest values in a data set
multimodal
range
unimodal
randomization
6. A study based on data in which no manipulation of factors has been employed
mode
r2
changing center and spread
observational study
7. A variable whose levels are controlled by the experimenter
factor
response variable
outlier
normal model
8. Value found by subtracting the mean and dividing by the standard deviation
mode
standardized value
response bias
representative
9. 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
mode
boxplot
skewed
quartile
10. Shows the relationship between two quantitative variables measured on the same cases
block
scatterplots
percentile
experiment
11. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
direction
regression to the mean
bias
experimental units
12. 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
simulation
strength
completely randomized design
mode
13. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
simpson's paradox
influential point
unimodal
variable
14. 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
linear model
subset
standardizing
regression line
15. The number of individuals in a sample
systematic sample
sample size
intercept
uniform
16. The sum of squared deviations from the mean - divided by the count minus one
sample
predicted value
variance
response
17. When groups of experimental units are similar - it is a good idea to gather them together into these
block
scatterplots
median
matching
18. Shows a bar representing the count of each category in a categorical variable
random assignment
bar chart
regression to the mean
median
19. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
spread
bias
random numbers
pie chart
20. Extreme values that don't appear to belong with the rest of the data
outliers
blinding
simulation
tails
21. The difference between the first and third quartiles
interquartile range
regression line
frequency table
standardized value
22. When an observed difference is too large for us to believe that is is likely to have occurred naturally
statistically significant
standard normal model
units
shape
23. 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
variable
predicted value
histogram
population parameter
24. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
sample size
single-blind
z-score
range
25. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
center
shifting
normal model
independence
26. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
census
confounded
re-express data
normal model
27. Lists the categories in a categorical variable and gives the count or percentage of observations for each category
frequency table
influential point
scatterplots
convenience sample
28. A distribution is this if it's not symmetric and one tail stretches out farther than the other
units
skewed
randomized block
lurking variable
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
r2
shifting
block
randomized block
30. The distribution of a variable restricting the who to consider only a smaller group of individuals
outlier
control group
conditional distribution
pie chart
31. When omitting a point from the data results in a very different regression model - the point is an ____
influential point
linear model
blinding
strength
32. When averages are taken across different groups - they can appear to contradict the overall averages
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33. An arrangement of data in which each row represents a case and each column represents a variable
standardized value
data table
spread
treatment
34. A numerical measure of the direction and strength of a linear association
tails
experiment
correlation
sampling variability
35. 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
simple random sample
marginal distribution
treatment
completely randomized design
36. A treatment known to have no effect - administered so that all groups experience the same conditions
standard normal model
bias
placebo
frequency table
37. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
intercept
influential point
form
normal model
38. When doing this - consider their shape - center - and spread
retrospective study
comparing distributions
form
center
39. Sampling schemes that combine several sampling methods
distribution
normal model
distribution
multistage sample
40. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
uniform
pie chart
rescaling
convenience sample
41. Design Randomization occurring within blocks
randomized block
multistage sample
simulation component
correlation
42. The middle value with half of the data above and half below it
leverage
median
pie chart
sampling variability
43. 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
68-95-99.7 rule
slope
lurking variable
changing center and spread
44. Distributions with more than two modes
multimodal
placebo effect
standardizing
standard normal model
45. The square root of the variance
symmetric
comparing distributions
standard deviation
undercoverage
46. 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
direction
context
47. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
contingency table
standard normal model
linear model
stratified random sample
48. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
leverage
re-express data
timeplot
lurking variable
49. The sequence of several components representing events that we are pretending will take place
regression line
units
trial
random assignment
50. An observational study in which subjects are followed to observe future outcomes
prospective study
blinding
regression to the mean
population
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