SUBJECTS
|
BROWSE
|
CAREER CENTER
|
POPULAR
|
JOIN
|
LOGIN
Business Skills
|
Soft Skills
|
Basic Literacy
|
Certifications
About
|
Help
|
Privacy
|
Terms
|
Email
Search
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. Holds information about the same characteristic for many cases
r2
variable
statistic
trial
2. A distribution is this if the two halves on either side of the center look approximately like mirror images of each other
symmetric
normal model
bimodal
principles of experimental design
3. An event is this if we know what outcomes could happen - but not which particular values will happen
context
random
multimodal
leverage
4. 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
timeplot
convenience sample
response
matched
5. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
strength
response
scatterplots
68-95-99.7 rule
6. The most basic situation in a simulation in which something happens at random
range
form
simulation component
normal model
7. The ith ___ is the number that falls above i% of the data
lurking variable
response bias
simulation component
percentile
8. Gives the possible values of the variable and the relative frequency of each value
distribution
multimodal
mode
rescaling
9. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
randomized block
categorical variable
lurking variable
randomization
10. The ____ we care about most is straight
strength
form
cluster sample
sample
11. 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
frequency table
contingency table
census
12. A variable whose values are compared across different treatments
population parameter
response
rescaling
level
13. When either those who could influence or evaluate the results is blinded
lurking variable
comparing distributions
outlier
single-blind
14. A sampling design in which entire groups are chosen at random
area principle
sampling frame
cluster sample
blinding
15. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____
marginal distribution
bias
context
simpson's paradox
16. Shows quantitative data values in a way that sketches the distribution of the data
lurking variable
pie chart
stem-and-leaf display
voluntary response bias
17. A variable in which the numbers act as numerical values; always has units
quantitative variable
percentile
center
regression line
18. The sum of squared deviations from the mean - divided by the count minus one
quartile
statistic
blinding
variance
19. Shows a bar representing the count of each category in a categorical variable
context
bar chart
matched
sample
20. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
parameter
bias
voluntary response bias
prospective study
21. 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
randomized block
case
median
22. The natural tendency of randomly drawn samples to differ
principles of experimental design
sampling variability
randomization
pie chart
23. A study based on data in which no manipulation of factors has been employed
spread
observational study
double-blind
lurking variable
24. Useful family of models for unimodal - symmetric distributions
sample
simulation component
center
normal model
25. A list of individuals from whom the sample is drawn
sampling frame
normal model
statistic
subset
26. Lists the categories in a categorical variable and gives the count or percentage of observations for each category
frequency table
median
bias
re-express data
27. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
pie chart
z-score
distribution
scatterplots
28. When groups of experimental units are similar - it is a good idea to gather them together into these
outlier
block
changing center and spread
population
29. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
marginal distribution
standardizing
sampling frame
undercoverage
30. 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
symmetric
simpson's paradox
experiment
marginal distribution
31. To be valid - an experiment must assign experimental units to treatment groups at random
unimodal
voluntary response bias
tails
random assignment
32. An equation or formula that simplifies and represents reality
residuals
response bias
double-blind
model
33. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population
sample survey
rescaling
center
regression line
34. When averages are taken across different groups - they can appear to contradict the overall averages
Warning
: Invalid argument supplied for foreach() in
/var/www/html/basicversity.com/show_quiz.php
on line
183
35. Shows the relationship between two quantitative variables measured on the same cases
multistage sample
scatterplots
response bias
simulation
36. 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
histogram
linear model
z-score
parameter
37. Summarized with the standard deviation - interquartile range - and range
simple random sample
context
spread
level
38. 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
trial
double-blind
slope
boxplot
39. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
unimodal
sample
histogram
symmetric
40. A sample that consists of the entire population
ladder of powers
census
tails
statistic
41. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams
linear model
confounded
marginal distribution
units
42. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
stratified random sample
dotplot
experiment
skewed
43. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
standardized value
influential point
residuals
placebo effect
44. A numerically valued attribute of a model for a population
population parameter
spread
cluster sample
stem-and-leaf display
45. A variable whose levels are controlled by the experimenter
experimental units
skewed
bias
factor
46. A sample drawn by selecting individuals systematically from a sampling frame
single-blind
re-express data
systematic sample
level
47. When both those who could influence and evaluate the results are blinded
double-blind
center
frequency table
contingency table
48. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant
pie chart
block
rescaling
nonresponse bias
49. Values of this record the results of each trial with respect to what we were interested in
blinding
response variable
units
mean
50. The number of individuals in a sample
strength
sample size
distribution
normal probability plot