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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.
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 both those who could influence and evaluate the results are blinded
z-score
double-blind
response bias
multistage sample
2. An event is this if we know what outcomes could happen - but not which particular values will happen
lurking variable
variance
factor
random
3. A numerically valued attribute of a model for a population
control group
mean
population parameter
tails
4. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
census
units
predicted value
frequency table
5. When an observed difference is too large for us to believe that is is likely to have occurred naturally
statistically significant
statistic
factor
symmetric
6. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
linear model
least squares
intercept
outlier
7. The ____ we care about most is straight
form
experiment
scatterplots
lurking variable
8. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
census
center
strength
unimodal
9. Distributions with more than two modes
random assignment
convenience sample
variance
multimodal
10. Found by summing all the data values and dividing by the count
range
mean
model
retrospective study
11. An equation of the form y-hat = b0 + b1x
random assignment
linear model
sample size
block
12. Individuals on whom an experiment is performed
independence
statistically significant
quartile
experimental units
13. A numerical summary of how tightly the values are clustered around the 'center'
random numbers
spread
voluntary response bias
population
14. The ith ___ is the number that falls above i% of the data
percentile
normal model
normal percentile
dotplot
15. A treatment known to have no effect - administered so that all groups experience the same conditions
trial
tails
distribution
placebo
16. A variable in which the numbers act as numerical values; always has units
lurking variable
quantitative variable
placebo
principles of experimental design
17. 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
unimodal
matching
bias
slope
18. Shows the relationship between two quantitative variables measured on the same cases
histogram
units
randomized block
scatterplots
19. A variable whose levels are controlled by the experimenter
factor
sampling variability
influential point
variable
20. A sampling design in which entire groups are chosen at random
scatterplots
histogram
residuals
cluster sample
21. Summarized with the mean or the median
influential point
level
normal percentile
center
22. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
randomization
r2
stratified random sample
linear model
23. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below
cluster sample
normal percentile
percentile
leverage
24. 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
outcome
lurking variable
r2
population parameter
25. Graphs a dot for each case against a single axis
context
lurking variable
convenience sample
dotplot
26. When omitting a point from the data results in a very different regression model - the point is an ____
prospective study
block
influential point
normal model
27. In a statistical display - each data value should be represented by the same amount of area
matched
control group
lurking variable
area principle
28. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
contingency table
model
re-express data
regression to the mean
29. A study based on data in which no manipulation of factors has been employed
observational study
dotplot
representative
re-express data
30. Shows a bar representing the count of each category in a categorical variable
statistically significant
bar chart
5-number summary
model
31. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
area principle
standardizing
mode
residuals
32. 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
experiment
center
contingency table
matched
33. Value calculated from data to summarize aspects of the data
marginal distribution
retrospective study
statistic
subset
34. Control - randomize - replicate - block
5-number summary
timeplot
completely randomized design
principles of experimental design
35. 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
cluster sample
normal probability plot
categorical variable
slope
36. Sampling schemes that combine several sampling methods
multistage sample
changing center and spread
outcome
categorical variable
37. Value found by subtracting the mean and dividing by the standard deviation
prospective study
principles of experimental design
simulation component
standardized value
38. 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
level
shape
skewed
experiment
39. 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
sampling variability
matching
confounded
40. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant
confounded
simple random sample
rescaling
skewed
41. The difference between the first and third quartiles
uniform
interquartile range
principles of experimental design
level
42. 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
linear model
direction
sampling frame
regression line
43. The distribution of a variable restricting the who to consider only a smaller group of individuals
conditional distribution
range
leverage
shape
44. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population
retrospective study
leverage
sample survey
stem-and-leaf display
45. 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
extrapolation
population parameter
sample survey
46. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
outlier
experiment
intercept
representative
47. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
comparing distributions
intercept
randomized block
random numbers
48. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
bar chart
contingency table
confounded
double-blind
49. 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
residuals
form
z-score
extrapolation
50. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
response variable
sample
conditional distribution
lurking variable
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