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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. When an observed difference is too large for us to believe that is is likely to have occurred naturally
statistically significant
68-95-99.7 rule
regression to the mean
systematic sample
2. Places in order the effects that many re-expressions have on the data
mode
outliers
simple random sample
ladder of powers
3. An observational study in which subjects are followed to observe future outcomes
simpson's paradox
residuals
factor
prospective study
4. All experimental units have an equal chance of receiving any treatment
least squares
completely randomized design
uniform
boxplot
5. The difference between the first and third quartiles
re-express data
center
statistically significant
interquartile range
6. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
mode
variable
pie chart
bias
7. Sampling schemes that combine several sampling methods
multistage sample
observational study
retrospective study
scatterplots
8. The square root of the variance
center
conditional distribution
standard deviation
population
9. Displays data that change over time
timeplot
cluster sample
variable
tails
10. Distributions with two modes
response variable
bimodal
linear model
standardizing
11. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
level
least squares
multistage sample
median
12. The sequence of several components representing events that we are pretending will take place
model
spread
trial
distribution
13. 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
intercept
5-number summary
simple random sample
14. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
variance
intercept
representative
model
15. A numerical measure of the direction and strength of a linear association
direction
lurking variable
level
correlation
16. The best defense against bias - in which each individual is given a fair - random chance of selection
rescaling
scatterplots
randomization
data
17. 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
standardizing
categorical variable
mode
standard deviation
18. The distribution of a variable restricting the who to consider only a smaller group of individuals
conditional distribution
undercoverage
linear model
standardizing
19. 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
symmetric
r2
outliers
stem-and-leaf display
20. Control - randomize - replicate - block
form
principles of experimental design
multistage sample
predicted value
21. When both those who could influence and evaluate the results are blinded
re-express data
experimental units
double-blind
factor
22. Shows quantitative data values in a way that sketches the distribution of the data
stem-and-leaf display
influential point
prospective study
contingency table
23. Found by summing all the data values and dividing by the count
dotplot
standard deviation
mean
data table
24. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
regression line
re-express data
simulation
uniform
25. 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
quartile
bar chart
changing center and spread
principles of experimental design
26. When groups of experimental units are similar - it is a good idea to gather them together into these
block
double-blind
bimodal
standardizing
27. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
leverage
5-number summary
retrospective study
extrapolation
28. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
re-express data
prospective study
strength
form
29. Gives the possible values of the variable and the frequency or relative frequency of each value
normal percentile
convenience sample
distribution
population
30. Summarized with the mean or the median
quantitative variable
lurking variable
population parameter
center
31. A list of individuals from whom the sample is drawn
range
sampling frame
quartile
block
32. Numerically valued attribute of a model
convenience sample
parameter
voluntary response bias
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
extrapolation
bias
lurking variable
nonresponse bias
34. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
randomization
center
sample size
lurking variable
35. A representative subset of a population - examined in hope of learning about the population
area principle
sample
outlier
units
36. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
treatment
normal percentile
rescaling
slope
37. To be valid - an experiment must assign experimental units to treatment groups at random
random assignment
regression to the mean
distribution
convenience sample
38. Value calculated from data to summarize aspects of the data
cluster sample
random
statistic
simulation
39. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
histogram
center
placebo effect
normal percentile
40. Bias introduced to a sample when a large fraction of those sampled fails to respond
nonresponse bias
uniform
form
random numbers
41. 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
standard deviation
population parameter
shifting
normal probability plot
42. An individual result of a component of a simulation
outcome
linear model
outliers
sampling frame
43. Gives the possible values of the variable and the relative frequency of each value
regression to the mean
regression line
distribution
normal percentile
44. A distribution is this if the two halves on either side of the center look approximately like mirror images of each other
simulation component
symmetric
categorical variable
outlier
45. When either those who could influence or evaluate the results is blinded
single-blind
correlation
unimodal
placebo effect
46. Lists the categories in a categorical variable and gives the count or percentage of observations for each category
level
frequency table
outcome
undercoverage
47. The natural tendency of randomly drawn samples to differ
bar chart
sampling variability
shape
voluntary response bias
48. The ____ we care about most is straight
form
least squares
regression line
standard normal model
49. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant
nonresponse bias
rescaling
re-express data
standardizing
50. A study based on data in which no manipulation of factors has been employed
comparing distributions
observational study
simpson's paradox
response variable