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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. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
completely randomized design
area principle
5-number summary
residuals
2. 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
double-blind
simple random sample
shifting
correlation
3. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
standard deviation
voluntary response bias
control group
correlation
4. 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
undercoverage
case
representative
extrapolation
5. In a statistical display - each data value should be represented by the same amount of area
residuals
blinding
center
area principle
6. Control - randomize - replicate - block
blinding
principles of experimental design
sample size
quartile
7. Holds information about the same characteristic for many cases
confounded
tails
variable
area principle
8. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant
model
form
rescaling
linear model
9. A numerical summary of how tightly the values are clustered around the 'center'
rescaling
spread
data table
confounded
10. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
undercoverage
stem-and-leaf display
simple random sample
boxplot
11. 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
changing center and spread
simple random sample
contingency table
distribution
12. In a normal model - about 68% of values fall within 1 standard deviation of the mean - about 95% fall within 2 standard deviations of the mean - and about 99.7% fall within 3 standard deviations of the mean
cluster sample
random numbers
68-95-99.7 rule
observational study
13. 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
census
double-blind
marginal distribution
matched
14. The difference between the first and third quartiles
interquartile range
boxplot
data table
regression to the mean
15. Lists the categories in a categorical variable and gives the count or percentage of observations for each category
parameter
quantitative variable
frequency table
placebo
16. All experimental units have an equal chance of receiving any treatment
68-95-99.7 rule
spread
influential point
completely randomized design
17. An individual about whom or which we have data
case
scatterplots
tails
statistic
18. 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
comparing distributions
multistage sample
mode
random
19. An observational study in which subjects are followed to observe future outcomes
prospective study
interquartile range
simpson's paradox
randomized block
20. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
normal probability plot
treatment
population parameter
convenience sample
21. Found by substituting the x-value in the regression equation; they're the values on the fitted line
predicted value
control group
outlier
extrapolation
22. When either those who could influence or evaluate the results is blinded
context
single-blind
retrospective study
randomized block
23. Numerically valued attribute of a model
parameter
matching
comparing distributions
factor
24. Value calculated from data to summarize aspects of the data
spread
spread
statistic
outlier
25. When omitting a point from the data results in a very different regression model - the point is an ____
placebo
influential point
regression line
multimodal
26. A numerically valued attribute of a model for a population
stem-and-leaf display
population parameter
nonresponse bias
z-score
27. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
symmetric
placebo
placebo effect
simple random sample
28. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
outlier
placebo effect
standardizing
stratified random sample
29. Shows a bar representing the count of each category in a categorical variable
factor
ladder of powers
bar chart
sampling variability
30. A normal model with a mean of 0 and a standard deviation of 1
standard normal model
strength
predicted value
normal percentile
31. Useful family of models for unimodal - symmetric distributions
normal model
least squares
slope
comparing distributions
32. The specific values that the experimenter chooses for a factor
level
sample size
linear model
shifting
33. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
bimodal
area principle
population
standardizing
34. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
double-blind
convenience sample
standard deviation
least squares
35. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
variance
population
placebo
independence
36. The sequence of several components representing events that we are pretending will take place
sampling frame
voluntary response bias
trial
random numbers
37. Summarized with the standard deviation - interquartile range - and range
statistically significant
nonresponse bias
principles of experimental design
spread
38. A sampling design in which entire groups are chosen at random
strength
cluster sample
shifting
shape
39. The natural tendency of randomly drawn samples to differ
simulation component
interquartile range
sampling variability
lurking variable
40. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
voluntary response bias
random numbers
distribution
extrapolation
41. A numerical measure of the direction and strength of a linear association
principles of experimental design
standardizing
correlation
double-blind
42. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
histogram
timeplot
nonresponse bias
outlier
43. Graphs a dot for each case against a single axis
experimental units
standard deviation
undercoverage
dotplot
44. Individuals on whom an experiment is performed
standardizing
experimental units
intercept
retrospective study
45. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
variance
census
z-score
re-express data
46. Found by summing all the data values and dividing by the count
range
mean
sampling frame
model
47. When doing this - consider their shape - center - and spread
dotplot
outlier
comparing distributions
68-95-99.7 rule
48. A list of individuals from whom the sample is drawn
observational study
treatment
sampling frame
68-95-99.7 rule
49. A distribution that's roughly flat
lurking variable
simulation
uniform
placebo effect
50. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
intercept
undercoverage
units
center