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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. Gives the possible values of the variable and the relative frequency of each value
matching
normal percentile
standard deviation
distribution
2. 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
skewed
mode
response bias
timeplot
3. Useful family of models for unimodal - symmetric distributions
rescaling
distribution
response
normal model
4. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
voluntary response bias
randomization
lurking variable
case
5. When an observed difference is too large for us to believe that is is likely to have occurred naturally
factor
statistically significant
statistic
matched
6. A list of individuals from whom the sample is drawn
simpson's paradox
sampling frame
center
histogram
7. A distribution that's roughly flat
simple random sample
frequency table
response bias
uniform
8. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
outlier
normal probability plot
bias
predicted value
9. The sum of squared deviations from the mean - divided by the count minus one
placebo effect
block
trial
variance
10. Individuals on whom an experiment is performed
lurking variable
experimental units
subset
symmetric
11. 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
completely randomized design
shifting
uniform
treatment
12. When both those who could influence and evaluate the results are blinded
cluster sample
principles of experimental design
double-blind
categorical variable
13. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
form
residuals
blinding
single-blind
14. A representative subset of a population - examined in hope of learning about the population
area principle
sample
prospective study
scatterplots
15. 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
systematic sample
simulation
population parameter
sample
16. Sampling schemes that combine several sampling methods
prospective study
matched
outlier
multistage sample
17. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
sample survey
block
convenience sample
regression to the mean
18. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
bimodal
retrospective study
simulation component
center
19. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
blinding
undercoverage
level
direction
20. A variable that names categories (whether with words or numerals)
categorical variable
normal probability plot
conditional distribution
sampling frame
21. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
68-95-99.7 rule
regression line
timeplot
shape
22. The difference between the lowest and highest values in a data set
double-blind
range
categorical variable
systematic sample
23. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
observational study
shape
linear model
census
24. 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
slope
predicted value
quartile
multistage sample
25. When omitting a point from the data results in a very different regression model - the point is an ____
prospective study
shifting
influential point
retrospective study
26. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
median
stem-and-leaf display
unimodal
contingency table
27. The middle value with half of the data above and half below it
frequency table
median
double-blind
pie chart
28. Summarized with the mean or the median
randomized block
ladder of powers
center
spread
29. The ith ___ is the number that falls above i% of the data
percentile
normal model
scatterplots
form
30. 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
extrapolation
subset
conditional distribution
5-number summary
31. 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
contingency table
matched
form
intercept
32. Numerically valued attribute of a model
stratified random sample
distribution
parameter
response bias
33. An individual result of a component of a simulation
quantitative variable
residuals
ladder of powers
outcome
34. A variable whose levels are controlled by the experimenter
factor
conditional distribution
normal probability plot
census
35. Found by summing all the data values and dividing by the count
mean
distribution
predicted value
mode
36. A sample that consists of the entire population
census
normal percentile
standardizing
residuals
37. Lists the categories in a categorical variable and gives the count or percentage of observations for each category
median
response bias
frequency table
subset
38. Consists of the individuals who are conveniently available
census
convenience sample
scatterplots
response
39. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
random
leverage
simulation
intercept
40. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
blinding
confounded
center
placebo effect
41. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
outlier
uniform
trial
unimodal
42. When either those who could influence or evaluate the results is blinded
quartile
single-blind
rescaling
shape
43. A numerically valued attribute of a model for a population
normal model
outlier
stratified random sample
population parameter
44. When doing this - consider their shape - center - and spread
comparing distributions
ladder of powers
treatment
bar chart
45. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
cluster sample
quartile
z-score
interquartile range
46. In a statistical display - each data value should be represented by the same amount of area
area principle
blinding
systematic sample
percentile
47. Summarized with the standard deviation - interquartile range - and range
spread
conditional distribution
factor
simulation
48. A study based on data in which no manipulation of factors has been employed
observational study
sample
random numbers
leverage
49. 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
matched
undercoverage
block
simulation
50. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant
scatterplots
simpson's paradox
lurking variable
rescaling