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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. The middle value with half of the data above and half below it
median
matching
residuals
cluster sample
2. 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
case
simpson's paradox
standardizing
quartile
3. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
double-blind
lurking variable
statistically significant
shifting
4. 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
contingency table
direction
frequency table
variable
5. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
confounded
outliers
slope
context
6. Displays data that change over time
convenience sample
direction
correlation
timeplot
7. 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
block
ladder of powers
mode
lurking variable
8. Value calculated from data to summarize aspects of the data
principles of experimental design
boxplot
confounded
statistic
9. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
independence
stratified random sample
single-blind
placebo
10. An equation or formula that simplifies and represents reality
model
outcome
correlation
contingency table
11. Holds information about the same characteristic for many cases
re-express data
ladder of powers
outcome
variable
12. A variable whose levels are controlled by the experimenter
factor
mean
comparing distributions
units
13. An individual result of a component of a simulation
sample survey
timeplot
outcome
uniform
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
influential point
extrapolation
multistage sample
spread
15. The sum of squared deviations from the mean - divided by the count minus one
principles of experimental design
bimodal
shape
variance
16. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
lurking variable
conditional distribution
5-number summary
scatterplots
17. Any attempt to force a sample to resemble specified attributes of the population
frequency table
simulation component
standardizing
matching
18. A distribution is this if it's not symmetric and one tail stretches out farther than the other
skewed
model
ladder of powers
response bias
19. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
pie chart
interquartile range
conditional distribution
matching
20. A distribution that's roughly flat
data table
standardized value
convenience sample
uniform
21. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters
census
representative
undercoverage
center
22. A treatment known to have no effect - administered so that all groups experience the same conditions
mean
trial
5-number summary
placebo
23. A numerical measure of the direction and strength of a linear association
systematic sample
bar chart
correlation
shape
24. 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
subset
blinding
regression line
variable
25. Value found by subtracting the mean and dividing by the standard deviation
variance
spread
block
standardized value
26. Summarized with the mean or the median
quartile
distribution
center
double-blind
27. Adding a constant to each data value adds the same constant to the mean - the median - and the quartiles - but does not change the standard deviation or IQR
population
shifting
treatment
sample survey
28. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
68-95-99.7 rule
statistic
area principle
standardizing
29. When an observed difference is too large for us to believe that is is likely to have occurred naturally
single-blind
conditional distribution
response variable
statistically significant
30. Numerically valued attribute of a model
sample survey
matching
parameter
influential point
31. Control - randomize - replicate - block
units
skewed
bias
principles of experimental design
32. 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
simulation component
ladder of powers
experiment
prospective study
33. 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
sample survey
slope
matching
skewed
34. In a statistical display - each data value should be represented by the same amount of area
data
comparing distributions
area principle
conditional distribution
35. Consists of the individuals who are conveniently available
shape
systematic sample
statistically significant
convenience sample
36. Extreme values that don't appear to belong with the rest of the data
treatment
outliers
multimodal
z-score
37. The best defense against bias - in which each individual is given a fair - random chance of selection
form
area principle
bias
randomization
38. 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
leverage
experiment
range
regression line
39. Individuals on whom an experiment is performed
uniform
prospective study
experimental units
influential point
40. A variable whose values are compared across different treatments
outlier
response
stratified random sample
standardized value
41. A point that does not fit the overall pattern seen in the scatterplot
influential point
dotplot
outlier
center
42. An observational study in which subjects are followed to observe future outcomes
experiment
boxplot
prospective study
regression to the mean
43. Shows quantitative data values in a way that sketches the distribution of the data
quantitative variable
histogram
outliers
stem-and-leaf display
44. Values of this record the results of each trial with respect to what we were interested in
convenience sample
regression to the mean
response variable
stem-and-leaf display
45. An equation of the form y-hat = b0 + b1x
population parameter
linear model
area principle
simulation
46. Found by substituting the x-value in the regression equation; they're the values on the fitted line
population parameter
predicted value
prospective study
sample size
47. An individual about whom or which we have data
statistic
mean
undercoverage
case
48. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below
slope
normal percentile
sampling frame
timeplot
49. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
68-95-99.7 rule
regression to the mean
randomized block
outliers
50. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
response variable
blinding
multimodal
data