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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. A numerical summary of how tightly the values are clustered around the 'center'
leverage
5-number summary
spread
categorical variable
2. The sequence of several components representing events that we are pretending will take place
outliers
trial
parameter
symmetric
3. A numerically valued attribute of a model for a population
percentile
population parameter
placebo effect
comparing distributions
4. An event is this if we know what outcomes could happen - but not which particular values will happen
random
double-blind
mode
uniform
5. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below
level
retrospective study
normal percentile
stratified random sample
6. A sample that consists of the entire population
placebo
census
sampling frame
shape
7. The ____ we care about most is straight
timeplot
subset
outliers
form
8. Shows quantitative data values in a way that sketches the distribution of the data
random
randomization
stem-and-leaf display
simulation
9. A distribution is this if it's not symmetric and one tail stretches out farther than the other
response
completely randomized design
skewed
confounded
10. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
context
treatment
stratified random sample
randomization
11. A normal model with a mean of 0 and a standard deviation of 1
random numbers
mode
standard normal model
rescaling
12. Holds information about the same characteristic for many cases
variable
marginal distribution
pie chart
model
13. 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
multistage sample
sample survey
leverage
simulation component
14. 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
extrapolation
matched
independence
boxplot
15. A representative subset of a population - examined in hope of learning about the population
simulation
r2
principles of experimental design
sample
16. Numerically valued attribute of a model
skewed
normal model
parameter
confounded
17. A list of individuals from whom the sample is drawn
normal model
randomization
sampling frame
convenience sample
18. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
parameter
center
control group
comparing distributions
19. Anything in a survey design that influences response
independence
distribution
response bias
bias
20. 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
random assignment
normal percentile
simulation
independence
21. An equation or formula that simplifies and represents reality
response variable
model
conditional distribution
voluntary response bias
22. A variable whose levels are controlled by the experimenter
factor
variable
data table
parameter
23. 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
sampling variability
simple random sample
subset
variance
24. A distribution that's roughly flat
intercept
z-score
uniform
context
25. An individual about whom or which we have data
percentile
spread
categorical variable
case
26. A sample drawn by selecting individuals systematically from a sampling frame
spread
systematic sample
standardizing
slope
27. Graphs a dot for each case against a single axis
dotplot
cluster sample
independence
outliers
28. The specific values that the experimenter chooses for a factor
level
placebo effect
sample size
response bias
29. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
68-95-99.7 rule
dotplot
z-score
stratified random sample
30. When averages are taken across different groups - they can appear to contradict the overall averages
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31. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
regression line
5-number summary
context
range
32. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
bias
population
cluster sample
percentile
33. 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
rescaling
standard normal model
quartile
strength
34. An arrangement of data in which each row represents a case and each column represents a variable
symmetric
data table
median
sample
35. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
leverage
lurking variable
treatment
model
36. 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
symmetric
frequency table
treatment
experiment
37. When either those who could influence or evaluate the results is blinded
spread
changing center and spread
single-blind
sampling variability
38. Gives the possible values of the variable and the relative frequency of each value
multistage sample
comparing distributions
context
distribution
39. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
placebo effect
voluntary response bias
categorical variable
lurking variable
40. The distribution of either variable alone in a contingency table; the counts or percentages are the totals found in the margins (last row or column) of the table
response variable
marginal distribution
model
tails
41. Value calculated from data to summarize aspects of the data
regression line
mean
spread
statistic
42. The difference between the first and third quartiles
interquartile range
units
standardized value
predicted value
43. Any attempt to force a sample to resemble specified attributes of the population
bimodal
nonresponse bias
level
matching
44. 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
linear model
block
r2
variance
45. When omitting a point from the data results in a very different regression model - the point is an ____
standard normal model
influential point
symmetric
interquartile range
46. Summarized with the standard deviation - interquartile range - and range
spread
scatterplots
lurking variable
simulation
47. 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
blinding
random
voluntary response bias
48. The middle value with half of the data above and half below it
mean
median
range
quartile
49. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
skewed
bimodal
distribution
lurking variable
50. The most basic situation in a simulation in which something happens at random
simulation component
standardizing
lurking variable
random assignment