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. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below
factor
normal percentile
normal model
mode
2. 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
standard normal model
histogram
normal probability plot
matching
3. When groups of experimental units are similar - it is a good idea to gather them together into these
response variable
block
outliers
mode
4. 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
multistage sample
center
r2
unimodal
5. When either those who could influence or evaluate the results is blinded
census
single-blind
voluntary response bias
distribution
6. The distribution of a variable restricting the who to consider only a smaller group of individuals
r2
distribution
uniform
conditional distribution
7. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes
standardizing
lurking variable
distribution
experiment
8. Bias introduced to a sample when a large fraction of those sampled fails to respond
nonresponse bias
outlier
range
linear model
9. Value found by subtracting the mean and dividing by the standard deviation
stratified random sample
simulation component
unimodal
standardized value
10. Shows quantitative data values in a way that sketches the distribution of the data
shape
stem-and-leaf display
quartile
matching
11. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
variable
observational study
lurking variable
simulation
12. When both those who could influence and evaluate the results are blinded
shifting
double-blind
independence
multistage sample
13. A numerically valued attribute of a model for a population
single-blind
extrapolation
population parameter
influential point
14. Found by substituting the x-value in the regression equation; they're the values on the fitted line
data
factor
predicted value
convenience sample
15. 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
convenience sample
case
simulation
symmetric
16. Useful family of models for unimodal - symmetric distributions
case
retrospective study
area principle
normal model
17. 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
18. A study based on data in which no manipulation of factors has been employed
units
observational study
outcome
subset
19. A distribution is this if it's not symmetric and one tail stretches out farther than the other
convenience sample
blinding
skewed
predicted value
20. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
control group
randomization
sample
parameter
21. 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
bimodal
conditional distribution
nonresponse bias
normal probability plot
22. When doing this - consider their shape - center - and spread
z-score
68-95-99.7 rule
comparing distributions
double-blind
23. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean
regression to the mean
pie chart
experimental units
center
24. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
case
stratified random sample
random numbers
randomized block
25. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo
sampling variability
percentile
placebo effect
data table
26. An arrangement of data in which each row represents a case and each column represents a variable
influential point
outlier
data table
multimodal
27. A variable that names categories (whether with words or numerals)
uniform
random
stem-and-leaf display
categorical variable
28. Graphs a dot for each case against a single axis
dotplot
lurking variable
symmetric
treatment
29. An equation or formula that simplifies and represents reality
simulation component
68-95-99.7 rule
normal percentile
model
30. A variable whose values are compared across different treatments
outcome
response
randomization
correlation
31. Sampling schemes that combine several sampling methods
sample
stem-and-leaf display
outcome
multistage sample
32. Displays data that change over time
shifting
timeplot
tails
blinding
33. A sample drawn by selecting individuals systematically from a sampling frame
census
random
voluntary response bias
systematic sample
34. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
center
least squares
pie chart
marginal distribution
35. A sampling scheme that biases the sample in a way that gives a part of the population less representation than it has in the population
lurking variable
double-blind
undercoverage
sample
36. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
randomization
randomized block
retrospective study
prospective study
37. The natural tendency of randomly drawn samples to differ
mean
sample
sampling variability
simulation component
38. The best defense against bias - in which each individual is given a fair - random chance of selection
random
normal probability plot
randomization
multistage sample
39. A treatment known to have no effect - administered so that all groups experience the same conditions
simple random sample
lurking variable
standard normal model
placebo
40. The ____ we care about most is straight
form
statistic
range
case
41. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
statistic
bimodal
residuals
population parameter
42. The square root of the variance
standard deviation
sampling frame
shifting
statistic
43. Values of this record the results of each trial with respect to what we were interested in
response variable
observational study
standardized value
lurking variable
44. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population
random
sample survey
blinding
independence
45. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
experiment
z-score
histogram
rescaling
46. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
outlier
ladder of powers
form
case
47. An individual result of a component of a simulation
boxplot
bias
influential point
outcome
48. The most basic situation in a simulation in which something happens at random
simulation
population
matching
simulation component
49. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
68-95-99.7 rule
5-number summary
sample size
undercoverage
50. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
rescaling
factor
intercept
unimodal