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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. Control - randomize - replicate - block
matched
principles of experimental design
distribution
area principle
2. Extreme values that don't appear to belong with the rest of the data
outliers
shape
normal probability plot
nonresponse bias
3. The ith ___ is the number that falls above i% of the data
percentile
center
histogram
regression line
4. Useful family of models for unimodal - symmetric distributions
single-blind
shifting
normal model
residuals
5. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
convenience sample
randomization
placebo effect
normal probability plot
6. 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
subset
spread
slope
blinding
7. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
intercept
re-express data
extrapolation
uniform
8. The entire group of individuals or instances about whom we hope to learn
mean
data table
population
range
9. When doing this - consider their shape - center - and spread
bias
5-number summary
single-blind
comparing distributions
10. A numerical summary of how tightly the values are clustered around the 'center'
cluster sample
variable
normal percentile
spread
11. A variable in which the numbers act as numerical values; always has units
treatment
quantitative variable
changing center and spread
experiment
12. The most basic situation in a simulation in which something happens at random
normal model
ladder of powers
area principle
simulation component
13. A list of individuals from whom the sample is drawn
standard normal model
sampling frame
boxplot
placebo
14. 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
categorical variable
intercept
tails
15. Found by substituting the x-value in the regression equation; they're the values on the fitted line
predicted value
data table
normal percentile
standard deviation
16. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
standardizing
population
systematic sample
normal probability plot
17. When averages are taken across different groups - they can appear to contradict the overall averages
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18. To be valid - an experiment must assign experimental units to treatment groups at random
distribution
population parameter
random assignment
response variable
19. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
influential point
marginal distribution
matched
bias
20. 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
changing center and spread
leverage
experiment
outliers
21. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
5-number summary
control group
standardized value
double-blind
22. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
z-score
residuals
subset
pie chart
23. A numerically valued attribute of a model for a population
subset
prospective study
population parameter
random
24. Found by summing all the data values and dividing by the count
outlier
frequency table
mean
direction
25. A variable whose levels are controlled by the experimenter
factor
response variable
z-score
case
26. When an observed difference is too large for us to believe that is is likely to have occurred naturally
statistically significant
median
ladder of powers
68-95-99.7 rule
27. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
outlier
dotplot
changing center and spread
factor
28. Shows the relationship between two quantitative variables measured on the same cases
range
skewed
intercept
scatterplots
29. 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
response variable
context
changing center and spread
linear model
30. Displays data that change over time
principles of experimental design
response variable
timeplot
observational study
31. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
population parameter
nonresponse bias
boxplot
retrospective study
32. A sampling design in which entire groups are chosen at random
random numbers
cluster sample
leverage
matched
33. Doing this is equivalent to changing its units
direction
changing center and spread
variance
principles of experimental design
34. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
simulation
distribution
blinding
dotplot
35. An equation of the form y-hat = b0 + b1x
influential point
center
context
linear model
36. Systematically recorded information - whether numbers or labels - together with its context
scatterplots
data
normal percentile
single-blind
37. Bias introduced to a sample when a large fraction of those sampled fails to respond
data table
predicted value
nonresponse bias
matched
38. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
single-blind
model
randomization
strength
39. Distributions with more than two modes
representative
multimodal
area principle
normal percentile
40. The difference between the lowest and highest values in a data set
double-blind
regression line
variable
range
41. Summarized with the mean or the median
leverage
center
simulation
quartile
42. Graphs a dot for each case against a single axis
re-express data
model
dotplot
standard normal model
43. Sampling schemes that combine several sampling methods
multistage sample
comparing distributions
mode
spread
44. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
random numbers
pie chart
bimodal
multimodal
45. Shows quantitative data values in a way that sketches the distribution of the data
randomized block
control group
bar chart
stem-and-leaf display
46. A distribution that's roughly flat
normal probability plot
uniform
ladder of powers
5-number summary
47. The natural tendency of randomly drawn samples to differ
sampling variability
response
single-blind
contingency table
48. Summarized with the standard deviation - interquartile range - and range
mean
distribution
confounded
spread
49. A display to help assess whether a distribution of data is approximately normal; if it is nearly straight - the data satisfy the nearly normal condition
bar chart
random
systematic sample
normal probability plot
50. Gives the possible values of the variable and the frequency or relative frequency of each value
outliers
standardizing
conditional distribution
distribution