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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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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. A numerical summary of how tightly the values are clustered around the 'center'
simple random sample
spread
uniform
simulation component
2. 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
tails
census
mean
3. The difference between the lowest and highest values in a data set
multimodal
regression to the mean
population
range
4. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
population
sampling frame
categorical variable
confounded
5. The square root of the variance
mean
observational study
standard deviation
leverage
6. Values of this record the results of each trial with respect to what we were interested in
response variable
least squares
scatterplots
simple random sample
7. The entire group of individuals or instances about whom we hope to learn
population
control group
sampling frame
double-blind
8. When an observed difference is too large for us to believe that is is likely to have occurred naturally
statistically significant
quantitative variable
simulation
variable
9. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
re-express data
dotplot
sample
random numbers
10. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
regression line
random
frequency table
census
11. Shows the relationship between two quantitative variables measured on the same cases
scatterplots
form
mode
outlier
12. Graphs a dot for each case against a single axis
outlier
sampling frame
dotplot
shape
13. 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
regression line
simulation
symmetric
model
14. 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
contingency table
population
extrapolation
categorical variable
15. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
representative
frequency table
treatment
response bias
16. The sum of squared deviations from the mean - divided by the count minus one
variance
z-score
normal probability plot
random
17. When groups of experimental units are similar - it is a good idea to gather them together into these
undercoverage
statistic
block
randomization
18. Any attempt to force a sample to resemble specified attributes of the population
skewed
systematic sample
matching
ladder of powers
19. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
lurking variable
independence
factor
context
20. A representative subset of a population - examined in hope of learning about the population
sample
quartile
random numbers
simpson's paradox
21. The parts of a distribution that typically trail off on either side; they can be characterized as long or short
random assignment
contingency table
units
tails
22. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
randomized block
direction
sampling variability
units
23. A distribution is this if it's not symmetric and one tail stretches out farther than the other
units
range
regression line
skewed
24. Found by summing all the data values and dividing by the count
normal probability plot
mean
parameter
undercoverage
25. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
level
strength
pie chart
simpson's paradox
26. Lists the categories in a categorical variable and gives the count or percentage of observations for each category
outlier
representative
level
frequency table
27. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
standard normal model
conditional distribution
randomized block
re-express data
28. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
residuals
quantitative variable
units
center
29. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
timeplot
simulation
least squares
experiment
30. A variable in which the numbers act as numerical values; always has units
quantitative variable
variable
outlier
nonresponse bias
31. 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
direction
bimodal
standardizing
response
32. Anything in a survey design that influences response
parameter
simulation component
response bias
randomized block
33. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
5-number summary
tails
lurking variable
rescaling
34. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
response
5-number summary
center
conditional distribution
35. 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
outliers
matched
double-blind
multimodal
36. The most basic situation in a simulation in which something happens at random
normal percentile
data
bimodal
simulation component
37. When either those who could influence or evaluate the results is blinded
nonresponse bias
level
single-blind
quantitative variable
38. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
regression line
matching
symmetric
standardizing
39. Places in order the effects that many re-expressions have on the data
outliers
timeplot
normal model
ladder of powers
40. A sampling design in which entire groups are chosen at random
cluster sample
form
z-score
response variable
41. Shows quantitative data values in a way that sketches the distribution of the data
sample
matching
bias
stem-and-leaf display
42. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
intercept
statistic
data table
sample size
43. 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
normal percentile
census
stem-and-leaf display
quartile
44. Summarized with the standard deviation - interquartile range - and range
spread
blinding
treatment
correlation
45. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
simulation component
control group
lurking variable
sampling frame
46. Value found by subtracting the mean and dividing by the standard deviation
response bias
regression to the mean
standardized value
matched
47. The distribution of a variable restricting the who to consider only a smaller group of individuals
prospective study
standard normal model
normal probability plot
conditional distribution
48. The difference between the first and third quartiles
lurking variable
convenience sample
interquartile range
population
49. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
slope
contingency table
simple random sample
response
50. To be valid - an experiment must assign experimental units to treatment groups at random
conditional distribution
random assignment
placebo
boxplot
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