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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. Anything in a survey design that influences response
context
retrospective study
response bias
timeplot
2. Useful family of models for unimodal - symmetric distributions
marginal distribution
prospective study
normal model
blinding
3. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
normal percentile
multistage sample
strength
units
4. Numerically valued attribute of a model
sample size
interquartile range
randomization
parameter
5. The best defense against bias - in which each individual is given a fair - random chance of selection
center
randomization
regression to the mean
median
6. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
parameter
stratified random sample
independence
bar chart
7. Bias introduced to a sample when a large fraction of those sampled fails to respond
quartile
uniform
nonresponse bias
experimental units
8. 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
marginal distribution
subset
standard deviation
response
9. The ith ___ is the number that falls above i% of the data
percentile
outlier
units
tails
10. 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
case
undercoverage
outlier
form
11. The square root of the variance
boxplot
standard deviation
standard normal model
mode
12. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
regression to the mean
unimodal
single-blind
experiment
13. 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
z-score
principles of experimental design
bar chart
direction
14. Summarized with the standard deviation - interquartile range - and range
spread
outlier
conditional distribution
re-express data
15. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
data table
residuals
bar chart
blinding
16. A distribution is this if it's not symmetric and one tail stretches out farther than the other
skewed
dotplot
comparing distributions
stem-and-leaf display
17. A numerical measure of the direction and strength of a linear association
sampling frame
census
completely randomized design
correlation
18. When groups of experimental units are similar - it is a good idea to gather them together into these
lurking variable
simpson's paradox
block
slope
19. Displays counts and - sometimes - percentages of individuals falling into named categories on two or more variables; categorizes the individuals on all variables at once - to reveal possible patterns in one variable that may be contingent on the cate
statistically significant
variance
contingency table
population
20. Value calculated from data to summarize aspects of the data
regression line
lurking variable
statistic
blinding
21. The sequence of several components representing events that we are pretending will take place
sample survey
lurking variable
standard deviation
trial
22. The distribution of a variable restricting the who to consider only a smaller group of individuals
re-express data
outlier
conditional distribution
area principle
23. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
z-score
blinding
convenience sample
standardized value
24. An arrangement of data in which each row represents a case and each column represents a variable
spread
population parameter
scatterplots
data table
25. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
blinding
correlation
regression line
intercept
26. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant
symmetric
spread
normal percentile
rescaling
27. When either those who could influence or evaluate the results is blinded
normal model
outlier
unimodal
single-blind
28. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
shape
quartile
retrospective study
experiment
29. A distribution that's roughly flat
residuals
uniform
simulation component
nonresponse bias
30. Graphs a dot for each case against a single axis
normal probability plot
factor
sample
dotplot
31. The parts of a distribution that typically trail off on either side; they can be characterized as long or short
tails
sample survey
pie chart
spread
32. When doing this - consider their shape - center - and spread
z-score
data
comparing distributions
conditional distribution
33. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
z-score
blinding
sampling frame
independence
34. Control - randomize - replicate - block
principles of experimental design
independence
percentile
slope
35. 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
experiment
lurking variable
units
matching
36. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
5-number summary
lurking variable
mean
spread
37. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
tails
sample survey
least squares
matched
38. Shows a bar representing the count of each category in a categorical variable
bar chart
experiment
experimental units
quartile
39. The entire group of individuals or instances about whom we hope to learn
bias
units
population
conditional distribution
40. Shows quantitative data values in a way that sketches the distribution of the data
influential point
stem-and-leaf display
strength
comparing distributions
41. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
conditional distribution
center
boxplot
residuals
42. 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
frequency table
observational study
normal model
context
43. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
convenience sample
confounded
center
mode
44. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
categorical variable
unimodal
placebo
lurking variable
45. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
retrospective study
linear model
residuals
units
46. A treatment known to have no effect - administered so that all groups experience the same conditions
placebo
slope
population parameter
stem-and-leaf display
47. Value found by subtracting the mean and dividing by the standard deviation
z-score
sample
block
standardized value
48. Found by substituting the x-value in the regression equation; they're the values on the fitted line
predicted value
standardized value
residuals
variable
49. When both those who could influence and evaluate the results are blinded
factor
residuals
double-blind
distribution
50. 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
distribution
sample
dotplot
simulation