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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 point that does not fit the overall pattern seen in the scatterplot
placebo
direction
stratified random sample
outlier
2. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
tails
factor
marginal distribution
control group
3. Summarized with the mean or the median
center
bias
multimodal
residuals
4. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
context
influential point
simple random sample
statistically significant
5. Individuals on whom an experiment is performed
bias
stratified random sample
experimental units
predicted value
6. 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
skewed
median
variable
contingency table
7. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
bias
statistically significant
retrospective study
random assignment
8. 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
response variable
68-95-99.7 rule
treatment
sampling frame
9. An equation or formula that simplifies and represents reality
regression to the mean
quartile
statistic
model
10. The square root of the variance
extrapolation
voluntary response bias
comparing distributions
standard deviation
11. The number of individuals in a sample
unimodal
contingency table
intercept
sample size
12. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
principles of experimental design
boxplot
sampling frame
experiment
13. Useful family of models for unimodal - symmetric distributions
5-number summary
control group
normal model
matching
14. A sample that consists of the entire population
strength
blinding
pie chart
census
15. A study based on data in which no manipulation of factors has been employed
principles of experimental design
observational study
completely randomized design
categorical variable
16. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population
completely randomized design
sample survey
variance
distribution
17. An arrangement of data in which each row represents a case and each column represents a variable
rescaling
normal probability plot
bar chart
data table
18. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
median
standardizing
matched
response
19. Shows a bar representing the count of each category in a categorical variable
standardized value
bar chart
tails
treatment
20. In a statistical display - each data value should be represented by the same amount of area
bias
area principle
variable
systematic sample
21. Gives the possible values of the variable and the frequency or relative frequency of each value
representative
distribution
contingency table
stem-and-leaf display
22. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
normal percentile
leverage
representative
lurking variable
23. The sequence of several components representing events that we are pretending will take place
normal model
trial
placebo
simpson's paradox
24. A distribution is this if it's not symmetric and one tail stretches out farther than the other
frequency table
skewed
sample survey
random
25. A distribution that's roughly flat
units
uniform
correlation
undercoverage
26. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
mode
variance
residuals
stratified random sample
27. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
outlier
principles of experimental design
bar chart
block
28. The best defense against bias - in which each individual is given a fair - random chance of selection
model
stratified random sample
multimodal
randomization
29. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
r2
response
range
regression to the mean
30. 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
single-blind
intercept
histogram
sampling frame
31. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
contingency table
simulation component
control group
pie chart
32. Distributions with more than two modes
convenience sample
ladder of powers
randomization
multimodal
33. A distribution is this if the two halves on either side of the center look approximately like mirror images of each other
percentile
blinding
random assignment
symmetric
34. 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
normal probability plot
convenience sample
variable
median
35. The entire group of individuals or instances about whom we hope to learn
population
multistage sample
median
standardizing
36. 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
quartile
response variable
outliers
extrapolation
37. The specific values that the experimenter chooses for a factor
sampling variability
level
standard normal model
voluntary response bias
38. 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
center
sample
outliers
39. Value calculated from data to summarize aspects of the data
statistic
bimodal
ladder of powers
data
40. When omitting a point from the data results in a very different regression model - the point is an ____
random
influential point
slope
mean
41. Values of this record the results of each trial with respect to what we were interested in
model
random numbers
randomization
response variable
42. Summarized with the standard deviation - interquartile range - and range
spread
variable
correlation
simulation component
43. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
symmetric
distribution
re-express data
treatment
44. A representative subset of a population - examined in hope of learning about the population
simpson's paradox
sample
response
5-number summary
45. Shows the relationship between two quantitative variables measured on the same cases
form
scatterplots
blinding
standardizing
46. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
shape
timeplot
treatment
nonresponse bias
47. 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
leverage
dotplot
unimodal
predicted value
48. The ____ we care about most is straight
case
z-score
form
outlier
49. 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
parameter
simulation
matched
influential point
50. The most basic situation in a simulation in which something happens at random
undercoverage
simulation component
marginal distribution
population parameter