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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 sample that consists of the entire population
conditional distribution
double-blind
block
census
2. Gives the possible values of the variable and the frequency or relative frequency of each value
shape
distribution
statistic
control group
3. The specific values that the experimenter chooses for a factor
level
factor
convenience sample
treatment
4. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
unimodal
units
ladder of powers
spread
5. 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
bias
simulation
changing center and spread
data
6. A list of individuals from whom the sample is drawn
retrospective study
sampling frame
random numbers
unimodal
7. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
skewed
center
mode
confounded
8. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant
z-score
rescaling
strength
range
9. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
conditional distribution
observational study
boxplot
random
10. 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
experiment
r2
placebo effect
marginal distribution
11. The middle value with half of the data above and half below it
principles of experimental design
median
percentile
unimodal
12. 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
simulation
distribution
variance
contingency table
13. A numerical summary of how tightly the values are clustered around the 'center'
population
spread
distribution
data
14. The sum of squared deviations from the mean - divided by the count minus one
categorical variable
uniform
variance
multistage sample
15. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
undercoverage
completely randomized design
placebo effect
histogram
16. 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
marginal distribution
completely randomized design
randomized block
bimodal
17. Doing this is equivalent to changing its units
range
influential point
changing center and spread
systematic sample
18. When averages are taken across different groups - they can appear to contradict the overall averages
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19. To be valid - an experiment must assign experimental units to treatment groups at random
randomization
random assignment
scatterplots
principles of experimental design
20. A point that does not fit the overall pattern seen in the scatterplot
predicted value
cluster sample
confounded
outlier
21. A variable whose values are compared across different treatments
response
distribution
tails
response variable
22. Displays data that change over time
symmetric
boxplot
outlier
timeplot
23. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
control group
center
treatment
statistically significant
24. A numerically valued attribute of a model for a population
contingency table
population parameter
cluster sample
outliers
25. 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
outlier
5-number summary
matched
uniform
26. Extreme values that don't appear to belong with the rest of the data
experiment
re-express data
outliers
area principle
27. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below
normal percentile
re-express data
5-number summary
uniform
28. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
percentile
z-score
population
independence
29. Design Randomization occurring within blocks
voluntary response bias
rescaling
randomized block
quartile
30. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
comparing distributions
outlier
block
subset
31. 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
completely randomized design
bar chart
r2
quartile
32. When omitting a point from the data results in a very different regression model - the point is an ____
outliers
marginal distribution
randomized block
influential point
33. A distribution is this if it's not symmetric and one tail stretches out farther than the other
simulation
68-95-99.7 rule
treatment
skewed
34. A sampling design in which entire groups are chosen at random
cluster sample
spread
predicted value
conditional distribution
35. In a statistical display - each data value should be represented by the same amount of area
placebo
strength
multimodal
area principle
36. The number of individuals in a sample
direction
sample size
standard deviation
center
37. Systematically recorded information - whether numbers or labels - together with its context
experiment
response variable
data
distribution
38. A variable in which the numbers act as numerical values; always has units
pie chart
multistage sample
quantitative variable
independence
39. Anything in a survey design that influences response
sample size
response bias
r2
nonresponse bias
40. 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
rescaling
variable
r2
confounded
41. The distribution of a variable restricting the who to consider only a smaller group of individuals
conditional distribution
parameter
direction
trial
42. Individuals on whom an experiment is performed
population
boxplot
experiment
experimental units
43. When doing this - consider their shape - center - and spread
distribution
lurking variable
statistic
comparing distributions
44. An arrangement of data in which each row represents a case and each column represents a variable
simulation component
data table
parameter
regression to the mean
45. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
center
simulation
block
random numbers
46. Summarized with the mean or the median
center
undercoverage
mean
pie chart
47. 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
undercoverage
median
r2
trial
48. Shows the relationship between two quantitative variables measured on the same cases
intercept
standardizing
quartile
scatterplots
49. 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
convenience sample
level
subset
placebo effect
50. Ideally tells who was measured - what was measured - how the data were collected - where the data were collected - and when and why the study was performed
regression line
sampling variability
context
leverage