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Test your basic knowledge |
AP Statistics Vocab
Start Test
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Subjects
:
statistics
,
ap
Instructions:
Answer 50 questions in 15 minutes.
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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. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
voluntary response bias
random assignment
outcome
control group
2. When both those who could influence and evaluate the results are blinded
double-blind
predicted value
statistic
sample
3. A numerically valued attribute of a model for a population
residuals
population parameter
bar chart
context
4. Gives the possible values of the variable and the frequency or relative frequency of each value
contingency table
trial
distribution
mean
5. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
area principle
confounded
mode
5-number summary
6. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
nonresponse bias
spread
simple random sample
variable
7. A numerical summary of how tightly the values are clustered around the 'center'
matched
case
spread
normal percentile
8. Summarized with the standard deviation - interquartile range - and range
placebo effect
unimodal
area principle
spread
9. A sample that consists of the entire population
conditional distribution
census
nonresponse bias
correlation
10. Holds information about the same characteristic for many cases
extrapolation
variable
sample size
simple random sample
11. 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
subset
sample size
frequency table
influential point
12. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
blinding
strength
normal percentile
correlation
13. The best defense against bias - in which each individual is given a fair - random chance of selection
cluster sample
spread
randomization
linear model
14. The entire group of individuals or instances about whom we hope to learn
rescaling
area principle
model
population
15. Uses adjacent bars to show the distribution of vales in a quantitative variable; each bar represents the frequency (or relative frequency) of values falling in an interval of values
experimental units
histogram
median
voluntary response bias
16. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
regression line
matching
rescaling
skewed
17. The specific values that the experimenter chooses for a factor
independence
level
68-95-99.7 rule
outliers
18. The middle value with half of the data above and half below it
stem-and-leaf display
outlier
independence
median
19. Control - randomize - replicate - block
response
independence
random assignment
principles of experimental design
20. 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
bimodal
shifting
block
ladder of powers
21. When omitting a point from the data results in a very different regression model - the point is an ____
pie chart
form
influential point
skewed
22. Anything in a survey design that influences response
68-95-99.7 rule
lurking variable
influential point
response bias
23. 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
representative
treatment
normal probability plot
influential point
24. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant
sample survey
rescaling
statistically significant
simpson's paradox
25. Distributions with two modes
linear model
bimodal
experimental units
center
26. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
symmetric
blinding
intercept
random numbers
27. 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
placebo
mean
slope
outcome
28. Values of this record the results of each trial with respect to what we were interested in
response variable
multimodal
shifting
control group
29. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
response bias
regression to the mean
placebo effect
skewed
30. Consists of the individuals who are conveniently available
convenience sample
sample size
response variable
center
31. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
contingency table
center
principles of experimental design
comparing distributions
32. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
principles of experimental design
least squares
independence
retrospective study
33. An arrangement of data in which each row represents a case and each column represents a variable
data table
simpson's paradox
direction
outlier
34. When an observed difference is too large for us to believe that is is likely to have occurred naturally
undercoverage
outcome
statistically significant
percentile
35. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
population
rescaling
strength
conditional distribution
36. When groups of experimental units are similar - it is a good idea to gather them together into these
independence
5-number summary
block
parameter
37. A numerical measure of the direction and strength of a linear association
experiment
correlation
scatterplots
percentile
38. Value found by subtracting the mean and dividing by the standard deviation
matching
lurking variable
regression line
standardized value
39. A normal model with a mean of 0 and a standard deviation of 1
outlier
range
standard normal model
random numbers
40. 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
re-express data
shifting
68-95-99.7 rule
influential point
41. 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
unimodal
predicted value
contingency table
sample size
42. The ____ we care about most is straight
lurking variable
response bias
symmetric
form
43. 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
mode
treatment
unimodal
block
44. Extreme values that don't appear to belong with the rest of the data
population parameter
outliers
outlier
experimental units
45. A distribution is this if it's not symmetric and one tail stretches out farther than the other
skewed
randomization
timeplot
spread
46. An event is this if we know what outcomes could happen - but not which particular values will happen
frequency table
cluster sample
random
changing center and spread
47. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
bimodal
lurking variable
unimodal
influential point
48. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
least squares
categorical variable
standard deviation
68-95-99.7 rule
49. An individual result of a component of a simulation
systematic sample
outcome
conditional distribution
least squares
50. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
influential point
unimodal
shape
subset
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