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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. Found by substituting the x-value in the regression equation; they're the values on the fitted line
regression line
simpson's paradox
re-express data
predicted value
2. The difference between the first and third quartiles
interquartile range
randomization
data table
distribution
3. Bias introduced to a sample when a large fraction of those sampled fails to respond
standardized value
bimodal
nonresponse bias
principles of experimental design
4. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
timeplot
bar chart
bias
independence
5. The square of the correlation between y and x; gives the fraction of the variability of y accounted for by the least squares linear regression on x; an overall measure of how successful the regression is in linearly relating y to x
r2
bimodal
trial
standardizing
6. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
outlier
random numbers
normal model
mean
7. When omitting a point from the data results in a very different regression model - the point is an ____
influential point
convenience sample
uniform
cluster sample
8. 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
distribution
simulation
normal model
units
9. In a statistical display - each data value should be represented by the same amount of area
experiment
area principle
distribution
marginal distribution
10. 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
spread
intercept
histogram
standard normal model
11. 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
statistically significant
tails
matched
matching
12. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
independence
data table
timeplot
dotplot
13. The ____ we care about most is straight
contingency table
pie chart
form
level
14. When either those who could influence or evaluate the results is blinded
matching
simulation component
quantitative variable
single-blind
15. Value calculated from data to summarize aspects of the data
percentile
predicted value
boxplot
statistic
16. A variable whose levels are controlled by the experimenter
contingency table
population parameter
z-score
factor
17. Doing this is equivalent to changing its units
sampling frame
changing center and spread
direction
regression to the mean
18. 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
categorical variable
regression line
subset
regression to the mean
19. A distribution is this if it's not symmetric and one tail stretches out farther than the other
skewed
bias
multimodal
categorical variable
20. Graphs a dot for each case against a single axis
stratified random sample
dotplot
scatterplots
simple random sample
21. The entire group of individuals or instances about whom we hope to learn
random assignment
population
dotplot
extrapolation
22. A treatment known to have no effect - administered so that all groups experience the same conditions
regression to the mean
mode
random
placebo
23. A distribution that's roughly flat
categorical variable
uniform
treatment
subset
24. Sampling schemes that combine several sampling methods
pie chart
direction
multistage sample
population parameter
25. 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
regression to the mean
subset
marginal distribution
simulation component
26. Found by summing all the data values and dividing by the count
retrospective study
experiment
mean
cluster sample
27. Individuals on whom an experiment is performed
standard normal model
trial
experimental units
subset
28. The most basic situation in a simulation in which something happens at random
outlier
simulation component
parameter
5-number summary
29. 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
changing center and spread
68-95-99.7 rule
stem-and-leaf display
matching
30. Values of this record the results of each trial with respect to what we were interested in
independence
interquartile range
response variable
experimental units
31. Value found by subtracting the mean and dividing by the standard deviation
trial
median
form
standardized value
32. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
symmetric
units
shape
blinding
33. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
completely randomized design
residuals
treatment
units
34. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below
normal probability plot
simple random sample
normal percentile
center
35. The sum of squared deviations from the mean - divided by the count minus one
outlier
variance
conditional distribution
statistic
36. A point that does not fit the overall pattern seen in the scatterplot
context
level
predicted value
outlier
37. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
stratified random sample
parameter
standardizing
sample survey
38. When averages are taken across different groups - they can appear to contradict the overall averages
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39. A sample that consists of the entire population
center
census
simulation component
voluntary response bias
40. Numerically valued attribute of a model
tails
parameter
block
regression to the mean
41. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
pie chart
outlier
stratified random sample
multistage sample
42. A variable in which the numbers act as numerical values; always has units
response variable
rescaling
quantitative variable
changing center and spread
43. A normal model with a mean of 0 and a standard deviation of 1
sample survey
standard normal model
categorical variable
spread
44. A numerically valued attribute of a model for a population
lurking variable
spread
regression to the mean
population parameter
45. When an observed difference is too large for us to believe that is is likely to have occurred naturally
extrapolation
conditional distribution
statistically significant
factor
46. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
spread
control group
simple random sample
stem-and-leaf display
47. Shows a bar representing the count of each category in a categorical variable
bar chart
model
normal model
placebo effect
48. Distributions with more than two modes
matching
multimodal
rescaling
subset
49. The best defense against bias - in which each individual is given a fair - random chance of selection
sampling variability
regression to the mean
randomization
block
50. The sequence of several components representing events that we are pretending will take place
variance
population
trial
slope