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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. The most basic situation in a simulation in which something happens at random
matching
quantitative variable
voluntary response bias
simulation component
2. Found by summing all the data values and dividing by the count
center
median
mean
timeplot
3. 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
boxplot
convenience sample
frequency table
4. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
multistage sample
population parameter
boxplot
rescaling
5. A normal model with a mean of 0 and a standard deviation of 1
variable
standard normal model
sampling frame
influential point
6. Distributions with two modes
linear model
case
bimodal
histogram
7. The sum of squared deviations from the mean - divided by the count minus one
population
lurking variable
variance
representative
8. 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
random assignment
double-blind
response variable
matched
9. Value found by subtracting the mean and dividing by the standard deviation
stem-and-leaf display
case
standardized value
outlier
10. 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
multistage sample
quantitative variable
distribution
subset
11. All experimental units have an equal chance of receiving any treatment
variance
sample survey
completely randomized design
spread
12. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units
multistage sample
treatment
intercept
matching
13. A distribution is this if it's not symmetric and one tail stretches out farther than the other
skewed
center
median
prospective study
14. When groups of experimental units are similar - it is a good idea to gather them together into these
multimodal
marginal distribution
block
experimental units
15. The square root of the variance
spread
influential point
standard deviation
simulation component
16. Lists the categories in a categorical variable and gives the count or percentage of observations for each category
frequency table
distribution
mode
influential point
17. The ith ___ is the number that falls above i% of the data
single-blind
leverage
mean
percentile
18. Consists of the individuals who are conveniently available
z-score
convenience sample
spread
regression to the mean
19. A distribution is this if the two halves on either side of the center look approximately like mirror images of each other
symmetric
pie chart
mean
stratified random sample
20. When an observed difference is too large for us to believe that is is likely to have occurred naturally
outcome
statistically significant
multistage sample
slope
21. 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
placebo
standardized value
contingency table
r2
22. Numerically valued attribute of a model
subset
multistage sample
data
parameter
23. An arrangement of data in which each row represents a case and each column represents a variable
data table
simulation
area principle
uniform
24. The number of individuals in a sample
simulation component
sample size
scatterplots
stem-and-leaf display
25. The ____ we care about most is straight
tails
form
experimental units
model
26. Gives the possible values of the variable and the frequency or relative frequency of each value
sampling frame
experiment
distribution
outlier
27. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set
z-score
distribution
re-express data
r2
28. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion
outliers
convenience sample
categorical variable
regression line
29. Graphs a dot for each case against a single axis
sample size
dotplot
symmetric
independence
30. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage
symmetric
outlier
bias
random numbers
31. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment
direction
sampling frame
blinding
control group
32. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value
context
single-blind
residuals
quantitative variable
33. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category
distribution
multimodal
pie chart
standardized value
34. Displays counts and - sometimes - percentages of individuals falling into named categories on two or more variables; categorizes the individuals on all variables at once - to reveal possible patterns in one variable that may be contingent on the cate
population parameter
sample
tails
contingency table
35. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals
units
cluster sample
least squares
center
36. 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
single-blind
factor
simulation
level
37. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below
random
factor
normal percentile
unimodal
38. An equation of the form y-hat = b0 + b1x
predicted value
linear model
spread
voluntary response bias
39. To be valid - an experiment must assign experimental units to treatment groups at random
systematic sample
response
random assignment
level
40. When omitting a point from the data results in a very different regression model - the point is an ____
68-95-99.7 rule
spread
ladder of powers
influential point
41. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample
spread
strength
unimodal
voluntary response bias
42. When both those who could influence and evaluate the results are blinded
lurking variable
outlier
control group
double-blind
43. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other
independence
principles of experimental design
contingency table
correlation
44. A treatment known to have no effect - administered so that all groups experience the same conditions
influential point
frequency table
boxplot
placebo
45. This of sample size n is one in which each set of n elements in the population has an equal chance of selection
simple random sample
random assignment
treatment
residuals
46. Shows a bar representing the count of each category in a categorical variable
bar chart
shifting
direction
outlier
47. 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
trial
leverage
nonresponse bias
quantitative variable
48. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related
shape
influential point
stratified random sample
lurking variable
49. Useful family of models for unimodal - symmetric distributions
prospective study
normal model
experimental units
randomization
50. The entire group of individuals or instances about whom we hope to learn
population
matched
standard deviation
dotplot