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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 variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
randomization
observational study
bar chart
lurking variable
2. 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
timeplot
interquartile range
standard normal model
undercoverage
3. When averages are taken across different groups - they can appear to contradict the overall averages
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4. Shows a bar representing the count of each category in a categorical variable
random
block
regression line
bar chart
5. A positive ____ or association means that - in general - as one variable increases - so does the other; when increases in one variable generally correspond to decreases in the other - the association is negative
direction
outliers
trial
mean
6. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
median
units
randomized block
normal percentile
7. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
nonresponse bias
confounded
treatment
mode
8. A distribution is this if it's not symmetric and one tail stretches out farther than the other
model
skewed
placebo
random numbers
9. An equation or formula that simplifies and represents reality
skewed
model
mean
level
10. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
context
single-blind
pie chart
least squares
11. A numerical summary of how tightly the values are clustered around the 'center'
ladder of powers
multistage sample
variance
spread
12. Places in order the effects that many re-expressions have on the data
statistically significant
frequency table
ladder of powers
units
13. Distributions with more than two modes
random assignment
retrospective study
multimodal
randomized block
14. The most basic situation in a simulation in which something happens at random
statistically significant
extrapolation
residuals
simulation component
15. 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
context
completely randomized design
categorical variable
16. Numerically valued attribute of a model
case
parameter
undercoverage
simulation
17. Shows quantitative data values in a way that sketches the distribution of the data
stem-and-leaf display
extrapolation
matching
rescaling
18. 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
independence
standard normal model
normal probability plot
model
19. The middle value with half of the data above and half below it
placebo
median
predicted value
random numbers
20. A normal model with a mean of 0 and a standard deviation of 1
level
experiment
stem-and-leaf display
standard normal model
21. The ith ___ is the number that falls above i% of the data
percentile
dotplot
bar chart
response variable
22. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
changing center and spread
control group
extrapolation
sampling variability
23. A variable in which the numbers act as numerical values; always has units
predicted value
standardized value
quantitative variable
block
24. 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
pie chart
regression line
extrapolation
single-blind
25. Any attempt to force a sample to resemble specified attributes of the population
experiment
area principle
matching
simple random sample
26. A study based on data in which no manipulation of factors has been employed
observational study
subset
simulation
direction
27. Distributions with two modes
pie chart
observational study
r2
bimodal
28. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
residuals
outliers
distribution
intercept
29. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
undercoverage
population parameter
ladder of powers
strength
30. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
outlier
timeplot
confounded
extrapolation
31. Holds information about the same characteristic for many cases
random
stratified random sample
control group
variable
32. A representative subset of a population - examined in hope of learning about the population
predicted value
influential point
simple random sample
sample
33. When groups of experimental units are similar - it is a good idea to gather them together into these
block
sample survey
simpson's paradox
categorical variable
34. 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
stem-and-leaf display
convenience sample
contingency table
stratified random sample
35. 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
marginal distribution
histogram
form
matching
36. Shows the relationship between two quantitative variables measured on the same cases
sample survey
distribution
spread
scatterplots
37. A distribution is this if the two halves on either side of the center look approximately like mirror images of each other
contingency table
sample
symmetric
intercept
38. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
center
bimodal
randomization
bias
39. An observational study in which subjects are followed to observe future outcomes
skewed
prospective study
influential point
least squares
40. An equation of the form y-hat = b0 + b1x
lurking variable
marginal distribution
case
linear model
41. A list of individuals from whom the sample is drawn
sampling frame
5-number summary
experimental units
slope
42. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
cluster sample
spread
normal probability plot
intercept
43. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
simple random sample
random numbers
trial
center
44. When either those who could influence or evaluate the results is blinded
predicted value
normal model
single-blind
nonresponse bias
45. An individual result of a component of a simulation
uniform
response
outcome
random
46. The difference between the first and third quartiles
regression to the mean
correlation
mode
interquartile range
47. 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
model
slope
independence
simulation component
48. When both those who could influence and evaluate the results are blinded
response
double-blind
normal probability plot
data
49. The sequence of several components representing events that we are pretending will take place
pie chart
trial
experiment
sampling frame
50. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
random
outlier
independence
lurking variable