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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. An individual result of a component of a simulation
unimodal
outlier
outcome
strength
2. A numerically valued attribute of a model for a population
retrospective study
block
population parameter
r2
3. Shows the relationship between two quantitative variables measured on the same cases
contingency table
multimodal
scatterplots
treatment
4. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters
representative
regression to the mean
distribution
single-blind
5. Value found by subtracting the mean and dividing by the standard deviation
level
standardized value
extrapolation
simulation
6. The best defense against bias - in which each individual is given a fair - random chance of selection
area principle
randomization
model
unimodal
7. The sequence of several components representing events that we are pretending will take place
placebo effect
trial
percentile
center
8. A variable in which the numbers act as numerical values; always has units
case
bias
quantitative variable
dotplot
9. 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
retrospective study
simpson's paradox
control group
slope
10. 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
68-95-99.7 rule
spread
extrapolation
contingency table
11. An arrangement of data in which each row represents a case and each column represents a variable
data table
independence
normal model
interquartile range
12. A distribution is this if the two halves on either side of the center look approximately like mirror images of each other
systematic sample
influential point
symmetric
response
13. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
simple random sample
scatterplots
outlier
conditional distribution
14. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
tails
treatment
normal probability plot
median
15. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
multistage sample
blinding
context
leverage
16. Doing this is equivalent to changing its units
changing center and spread
systematic sample
units
population parameter
17. When doing this - consider their shape - center - and spread
data table
subset
sampling frame
comparing distributions
18. The sum of squared deviations from the mean - divided by the count minus one
histogram
least squares
variance
bimodal
19. Graphs a dot for each case against a single axis
dotplot
completely randomized design
tails
categorical variable
20. Places in order the effects that many re-expressions have on the data
ladder of powers
simulation
units
predicted value
21. A numerical measure of the direction and strength of a linear association
predicted value
convenience sample
correlation
boxplot
22. A study based on data in which no manipulation of factors has been employed
observational study
strength
boxplot
simpson's paradox
23. 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
single-blind
variable
nonresponse bias
24. An equation of the form y-hat = b0 + b1x
linear model
subset
form
shifting
25. The middle value with half of the data above and half below it
median
standardized value
blinding
prospective study
26. An equation or formula that simplifies and represents reality
bimodal
normal model
model
contingency 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
re-express data
simpson's paradox
variable
distribution
28. When either those who could influence or evaluate the results is blinded
single-blind
undercoverage
lurking variable
pie chart
29. 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
quartile
treatment
variance
simulation
30. 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
experiment
simulation component
subset
response bias
31. An event is this if we know what outcomes could happen - but not which particular values will happen
symmetric
completely randomized design
shape
random
32. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
scatterplots
regression line
interquartile range
independence
33. 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
standardizing
randomization
symmetric
normal probability plot
34. Data points whose x-values are far from the mean of x are said to exert ____ on a linear model; with high enough ____ - residuals can appear to be deceptively small
prospective study
mode
leverage
control group
35. Found by substituting the x-value in the regression equation; they're the values on the fitted line
predicted value
spread
spread
undercoverage
36. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
intercept
level
regression to the mean
statistically significant
37. A numerical summary of how tightly the values are clustered around the 'center'
tails
spread
randomized block
response variable
38. Shows a bar representing the count of each category in a categorical variable
bar chart
sampling frame
cluster sample
correlation
39. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
lurking variable
block
standard normal model
double-blind
40. A distribution that's roughly flat
categorical variable
uniform
lurking variable
boxplot
41. Sampling schemes that combine several sampling methods
multistage sample
placebo effect
lurking variable
simple random sample
42. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
completely randomized design
5-number summary
lurking variable
rescaling
43. 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
matched
boxplot
marginal distribution
5-number summary
44. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
r2
nonresponse bias
cluster sample
stratified random sample
45. 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
principles of experimental design
outliers
mode
sampling frame
46. Summarized with the standard deviation - interquartile range - and range
spread
block
form
principles of experimental design
47. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
predicted value
standard deviation
rescaling
center
48. Useful family of models for unimodal - symmetric distributions
normal model
simple random sample
response
strength
49. The square root of the variance
standard deviation
outlier
uniform
outlier
50. The most basic situation in a simulation in which something happens at random
timeplot
context
correlation
simulation component