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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. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
lurking variable
marginal distribution
regression line
response bias
2. 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
skewed
simulation component
leverage
experiment
3. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
standardized value
shape
simpson's paradox
stratified random sample
4. 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
slope
response
extrapolation
regression to the mean
5. Displays data that change over time
factor
outliers
timeplot
stem-and-leaf display
6. An event is this if we know what outcomes could happen - but not which particular values will happen
random
random numbers
symmetric
context
7. Control - randomize - replicate - block
stratified random sample
boxplot
direction
principles of experimental design
8. 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
case
spread
re-express data
9. 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
context
normal probability plot
normal model
rescaling
10. The sequence of several components representing events that we are pretending will take place
trial
block
center
correlation
11. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
sample
random assignment
random numbers
response
12. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
uniform
shape
slope
prospective study
13. 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
conditional distribution
mode
independence
multistage sample
14. A distribution is this if it's not symmetric and one tail stretches out farther than the other
skewed
subset
representative
pie chart
15. A list of individuals from whom the sample is drawn
range
bias
skewed
sampling frame
16. 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
linear model
uniform
unimodal
17. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
influential point
standard deviation
independence
systematic sample
18. The distribution of a variable restricting the who to consider only a smaller group of individuals
conditional distribution
response bias
quartile
experiment
19. Shows a bar representing the count of each category in a categorical variable
bar chart
principles of experimental design
correlation
simulation
20. 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
extrapolation
5-number summary
uniform
predicted value
21. When doing this - consider their shape - center - and spread
factor
comparing distributions
unimodal
area principle
22. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
experimental units
form
boxplot
influential point
23. The ith ___ is the number that falls above i% of the data
percentile
contingency table
mode
simple random sample
24. Shows the relationship between two quantitative variables measured on the same cases
context
rescaling
scatterplots
principles of experimental design
25. A variable whose levels are controlled by the experimenter
population
re-express data
retrospective study
factor
26. A variable whose values are compared across different treatments
scatterplots
completely randomized design
response
outliers
27. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
center
pie chart
skewed
lurking variable
28. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
mean
voluntary response bias
principles of experimental design
area principle
29. When averages are taken across different groups - they can appear to contradict the overall averages
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30. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters
representative
sampling variability
range
distribution
31. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
undercoverage
outlier
control group
scatterplots
32. An arrangement of data in which each row represents a case and each column represents a variable
data table
experimental units
area principle
least squares
33. Useful family of models for unimodal - symmetric distributions
normal probability plot
normal model
5-number summary
trial
34. Extreme values that don't appear to belong with the rest of the data
variable
context
blinding
outliers
35. The natural tendency of randomly drawn samples to differ
extrapolation
sampling variability
convenience sample
completely randomized design
36. When an observed difference is too large for us to believe that is is likely to have occurred naturally
response variable
statistically significant
case
marginal distribution
37. To be valid - an experiment must assign experimental units to treatment groups at random
independence
prospective study
random assignment
leverage
38. An individual about whom or which we have data
sampling variability
outlier
categorical variable
case
39. A study based on data in which no manipulation of factors has been employed
observational study
placebo
sample
ladder of powers
40. Doing this is equivalent to changing its units
block
outlier
frequency table
changing center and spread
41. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population
matching
retrospective study
sample survey
census
42. 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
trial
matched
control group
units
43. An individual result of a component of a simulation
outcome
multistage sample
stem-and-leaf display
z-score
44. A sampling design in which entire groups are chosen at random
randomization
cluster sample
data
categorical variable
45. Bias introduced to a sample when a large fraction of those sampled fails to respond
nonresponse bias
independence
rescaling
symmetric
46. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
treatment
random assignment
simulation component
correlation
47. The difference between the lowest and highest values in a data set
z-score
cluster sample
bias
range
48. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
undercoverage
5-number summary
factor
sampling variability
49. The sum of squared deviations from the mean - divided by the count minus one
variance
bias
strength
factor
50. 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
voluntary response bias
interquartile range
outliers
simulation