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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. Doing this is equivalent to changing its units
parameter
simple random sample
distribution
changing center and spread
2. Useful family of models for unimodal - symmetric distributions
simpson's paradox
68-95-99.7 rule
normal model
prospective study
3. Value calculated from data to summarize aspects of the data
statistic
regression line
variance
retrospective study
4. 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
standard normal model
residuals
double-blind
68-95-99.7 rule
5. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped
unimodal
categorical variable
lurking variable
control group
6. A point that does not fit the overall pattern seen in the scatterplot
standardized value
5-number summary
area principle
outlier
7. When averages are taken across different groups - they can appear to contradict the overall averages
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8. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
contingency table
outliers
voluntary response bias
leverage
9. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
boxplot
census
timeplot
population
10. 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
sample size
leverage
outliers
conditional distribution
11. Summarized with the mean or the median
percentile
normal model
center
sample survey
12. The ____ we care about most is straight
form
center
scatterplots
single-blind
13. A distribution is this if it's not symmetric and one tail stretches out farther than the other
residuals
skewed
distribution
context
14. The sequence of several components representing events that we are pretending will take place
response bias
extrapolation
trial
outlier
15. Consists of the individuals who are conveniently available
matched
distribution
convenience sample
least squares
16. Design Randomization occurring within blocks
randomized block
sample survey
spread
sample size
17. An individual about whom or which we have data
cluster sample
influential point
lurking variable
case
18. Holds information about the same characteristic for many cases
variable
treatment
bias
quantitative variable
19. A variable in which the numbers act as numerical values; always has units
quartile
comparing distributions
quantitative variable
dotplot
20. In a statistical display - each data value should be represented by the same amount of area
area principle
percentile
predicted value
shape
21. A normal model with a mean of 0 and a standard deviation of 1
simulation
systematic sample
standard normal model
dotplot
22. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
predicted value
sample size
normal probability plot
pie chart
23. A treatment known to have no effect - administered so that all groups experience the same conditions
multimodal
randomized block
matching
placebo
24. 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
outlier
normal probability plot
shape
matching
25. A variable whose levels are controlled by the experimenter
median
principles of experimental design
population
factor
26. A study based on data in which no manipulation of factors has been employed
response
observational study
retrospective study
outcome
27. When an observed difference is too large for us to believe that is is likely to have occurred naturally
standard normal model
statistically significant
68-95-99.7 rule
conditional distribution
28. Gives the possible values of the variable and the frequency or relative frequency of each value
confounded
categorical variable
distribution
intercept
29. All experimental units have an equal chance of receiving any treatment
predicted value
multistage sample
completely randomized design
median
30. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one
linear model
block
regression line
z-score
31. The lower of this is the value with a quarter of the data below it; the upper of this has a quarter of the data above it
direction
factor
population
quartile
32. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population
sample survey
cluster sample
histogram
nonresponse bias
33. An equation of the form y-hat = b0 + b1x
bias
direction
linear model
ladder of powers
34. Manipulates factor levels to create treatments - randomly assigns subjects to these treatment levels - and then compares the responses of the subject groups across treatment levels
experiment
outliers
completely randomized design
bar chart
35. Shows quantitative data values in a way that sketches the distribution of the data
stem-and-leaf display
level
interquartile range
direction
36. Anything in a survey design that influences response
conditional distribution
double-blind
response bias
level
37. 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
conditional distribution
correlation
sample
r2
38. Control - randomize - replicate - block
principles of experimental design
outliers
sample survey
subset
39. A hump or local high point in the shape of the distribution of a variable; the apparent locations of these can change as the scale of a histogram is changed
median
least squares
mode
categorical variable
40. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum
simple random sample
stratified random sample
control group
mean
41. These are hard to generate - but several websites offer an unlimited supply of equally likely random values
undercoverage
random numbers
leverage
sample size
42. A list of individuals from whom the sample is drawn
scatterplots
lurking variable
sampling frame
response variable
43. Ideally tells who was measured - what was measured - how the data were collected - where the data were collected - and when and why the study was performed
context
marginal distribution
timeplot
changing center and spread
44. The difference between the lowest and highest values in a data set
shape
random numbers
frequency table
range
45. An observational study in which subjects are selected and then their previous conditions or behaviors are determined
retrospective study
systematic sample
spread
simple random sample
46. A positive ____ or association means that - in general - as one variable increases - so does the other; when increases in one variable generally correspond to decreases in the other - the association is negative
direction
spread
frequency table
control group
47. 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
block
normal probability plot
control group
48. A variable that names categories (whether with words or numerals)
symmetric
categorical variable
randomization
data
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
cluster sample
census
bar chart
simulation
50. The sum of squared deviations from the mean - divided by the count minus one
variance
spread
bimodal
experimental units