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. 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
simpson's paradox
control group
center
undercoverage
2. A sample drawn by selecting individuals systematically from a sampling frame
timeplot
systematic sample
population parameter
standardizing
3. The middle value with half of the data above and half below it
uniform
timeplot
median
conditional distribution
4. An equation or formula that simplifies and represents reality
model
response
shifting
sample
5. 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
5-number summary
simulation
dotplot
form
6. Value calculated from data to summarize aspects of the data
random assignment
variance
statistic
retrospective study
7. Any attempt to force a sample to resemble specified attributes of the population
standardizing
mode
matched
matching
8. The specific values that the experimenter chooses for a factor
model
block
predicted value
level
9. Although linear models provide an easy way to predict values of y for a given value of x - it is unsafe to predict for values of x far from the ones used to find the linear model equation; predictions should not be trusted
statistically significant
pie chart
experiment
extrapolation
10. Bias introduced to a sample when a large fraction of those sampled fails to respond
completely randomized design
multimodal
sampling variability
nonresponse bias
11. 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
12. The natural tendency of randomly drawn samples to differ
systematic sample
sampling variability
marginal distribution
boxplot
13. A variable whose values are compared across different treatments
response
treatment
simulation
variance
14. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median
undercoverage
level
sample survey
5-number summary
15. 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
placebo
simple random sample
range
16. Found by summing all the data values and dividing by the count
changing center and spread
mean
shifting
lurking variable
17. A point that does not fit the overall pattern seen in the scatterplot
outlier
response variable
block
simulation component
18. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value
unimodal
block
contingency table
center
19. Summarized with the mean or the median
marginal distribution
response variable
quantitative variable
center
20. 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
subset
histogram
scatterplots
model
21. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
sampling frame
regression line
least squares
control group
22. 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
68-95-99.7 rule
spread
lurking variable
census
23. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below
normal percentile
residuals
comparing distributions
response variable
24. 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
multimodal
level
percentile
mode
25. 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
blinding
experiment
linear model
quartile
26. A variable whose levels are controlled by the experimenter
changing center and spread
factor
intercept
contingency table
27. Values of this record the results of each trial with respect to what we were interested in
response variable
interquartile range
stem-and-leaf display
spread
28. In a statistical display - each data value should be represented by the same amount of area
area principle
lurking variable
median
distribution
29. Displays data that change over time
random
mean
timeplot
prospective study
30. A scatterplot shows an association that is this if there is little scatter around the underlying relationship
random numbers
strength
variance
bias
31. Numerically valued attribute of a model
response
parameter
correlation
linear model
32. An event is this if we know what outcomes could happen - but not which particular values will happen
random
block
center
mode
33. The square root of the variance
standard deviation
response variable
statistically significant
statistic
34. The entire group of individuals or instances about whom we hope to learn
randomized block
tails
population
center
35. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0
intercept
conditional distribution
residuals
slope
36. Gives the possible values of the variable and the frequency or relative frequency of each value
simulation component
percentile
statistically significant
distribution
37. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two
outliers
sampling frame
lurking variable
area principle
38. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups
direction
blinding
retrospective study
timeplot
39. Systematically recorded information - whether numbers or labels - together with its context
data
census
sampling variability
bias
40. Distributions with more than two modes
leverage
matched
population
multimodal
41. Lists the categories in a categorical variable and gives the count or percentage of observations for each category
census
regression line
frequency table
least squares
42. To be valid - an experiment must assign experimental units to treatment groups at random
range
random assignment
random
case
43. Distributions with two modes
bimodal
normal percentile
randomization
boxplot
44. Extreme values that don't appear to belong with the rest of the data
outliers
treatment
level
re-express data
45. When omitting a point from the data results in a very different regression model - the point is an ____
response variable
influential point
data
parameter
46. Graphs a dot for each case against a single axis
nonresponse bias
dotplot
sample survey
sampling frame
47. Doing this is equivalent to changing its units
spread
changing center and spread
normal probability plot
regression to the mean
48. 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
histogram
leverage
normal probability plot
double-blind
49. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
stratified random sample
normal percentile
independence
categorical variable
50. A variable in which the numbers act as numerical values; always has units
variable
quantitative variable
spread
observational study