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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. An arrangement of data in which each row represents a case and each column represents a variable
units
pie chart
blinding
data table
2. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant
conditional distribution
rescaling
standard deviation
representative
3. Sampling schemes that combine several sampling methods
regression to the mean
parameter
bias
multistage sample
4. Found by summing all the data values and dividing by the count
mean
context
statistic
blinding
5. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
lurking variable
matched
least squares
bar chart
6. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness
standard deviation
standardized value
shape
symmetric
7. Shows a bar representing the count of each category in a categorical variable
bar chart
voluntary response bias
sample size
prospective study
8. Individuals on whom an experiment is performed
residuals
statistically significant
experimental units
matching
9. When omitting a point from the data results in a very different regression model - the point is an ____
population parameter
bar chart
shifting
influential point
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
subset
histogram
area principle
contingency table
11. Extreme values that don't appear to belong with the rest of the data
slope
simulation component
parameter
outliers
12. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
center
direction
systematic sample
lurking variable
13. A list of individuals from whom the sample is drawn
least squares
shifting
sampling frame
categorical variable
14. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
treatment
confounded
parameter
random assignment
15. The difference between the lowest and highest values in a data set
strength
observational study
z-score
range
16. When either those who could influence or evaluate the results is blinded
variance
normal model
outcome
single-blind
17. An individual about whom or which we have data
placebo
case
experiment
outcome
18. Doing this is equivalent to changing its units
single-blind
response variable
changing center and spread
model
19. A sample drawn by selecting individuals systematically from a sampling frame
normal percentile
distribution
systematic sample
categorical variable
20. The entire group of individuals or instances about whom we hope to learn
undercoverage
spread
random numbers
population
21. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
re-express data
uniform
quantitative variable
pie chart
22. 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
randomized block
sample size
scatterplots
23. When averages are taken across different groups - they can appear to contradict the overall averages
24. Summarized with the mean or the median
lurking variable
nonresponse bias
dotplot
center
25. Values of this record the results of each trial with respect to what we were interested in
simple random sample
single-blind
mean
response variable
26. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
placebo effect
independence
experiment
boxplot
27. A representative subset of a population - examined in hope of learning about the population
context
observational study
matching
sample
28. Gives the possible values of the variable and the relative frequency of each value
distribution
completely randomized design
population
scatterplots
29. An equation of the form y-hat = b0 + b1x
double-blind
linear model
treatment
sampling frame
30. The specific values that the experimenter chooses for a factor
normal percentile
blinding
response variable
level
31. An individual result of a component of a simulation
outcome
outlier
outliers
multimodal
32. Distributions with two modes
random numbers
bimodal
marginal distribution
outlier
33. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
strength
pie chart
tails
double-blind
34. An observational study in which subjects are followed to observe future outcomes
population
standardizing
center
prospective study
35. The distribution of a variable restricting the who to consider only a smaller group of individuals
sampling frame
sample survey
conditional distribution
distribution
36. An equation or formula that simplifies and represents reality
model
simple random sample
completely randomized design
lurking variable
37. When an observed difference is too large for us to believe that is is likely to have occurred naturally
multistage sample
systematic sample
shape
statistically significant
38. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
linear model
random numbers
control group
form
39. A point that does not fit the overall pattern seen in the scatterplot
placebo effect
model
influential point
outlier
40. Value calculated from data to summarize aspects of the data
predicted value
statistic
range
marginal distribution
41. A sampling design in which entire groups are chosen at random
cluster sample
linear model
bias
outliers
42. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
5-number summary
re-express data
random assignment
distribution
43. A numerical summary of how tightly the values are clustered around the 'center'
correlation
population parameter
spread
block
44. The difference between the first and third quartiles
timeplot
response bias
interquartile range
variable
45. A variable whose values are compared across different treatments
sample size
response
bimodal
median
46. A sample that consists of the entire population
randomization
standardizing
census
rescaling
47. The best defense against bias - in which each individual is given a fair - random chance of selection
case
comparing distributions
random assignment
randomization
48. Found by substituting the x-value in the regression equation; they're the values on the fitted line
predicted value
randomized block
experimental units
population
49. All experimental units have an equal chance of receiving any treatment
completely randomized design
68-95-99.7 rule
statistically significant
slope
50. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below
unimodal
data table
normal percentile
conditional distribution