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WorksheetsAP Statistics Vocabulary
Total questions: 100
Worksheet time: 33mins
Name
Class
Date
1.
The claim that we actually believe to be true that we are trying to find evidence for.
a)
Alternative Hypothesis
b)
Significance Test
c)
Null Hypothesis
d)
P-value
2.
When knowing the value of one variable helps to predict the value of another.
a)
Association
b)
Dependent
c)
Correlation
d)
Independent
3.
The distribution of a random variable of continuing trials until a certain number of successes.
a)
Binomial
b)
Normal
c)
Geometric
d)
Random
4.
When the design of a study would consistently give an over or underestimate of the true value.
a)
Bias
b)
Confounding
c)
Statistical Significance
d)
Inconsistancy
5.
An accurate statistic used to approximate the parameter of a population.
a)
Unbiased Estimator
b)
Sample distribution
c)
Statistic
d)
Standard Normal Curve
6.
A variable of value rather than description.
a)
Categorical
b)
Quantitative
c)
Discrete
d)
Continuous
7.
A graph of quantitative data with two clear peaks.
a)
Bimodal
b)
Approximately Normal
c)
Normal
d)
Skewed
8.
The distribution of a random variable with the number of trials set in advance.
a)
Binomial
b)
Normal
c)
Geometric
d)
Random
9.
A group of experimental units that are similar and so are treated as one experimental unit.
a)
Block
b)
Individual
c)
Strata
d)
Particiants
10.
A graph of the five-number summary.
a)
Boxplot
b)
Stemplot
c)
Histogram
d)
Density Curve
11.
A variable of description rather than value.
a)
Categorical
b)
Quantitative
c)
Discrete
d)
Continuous
12.
A variable that takes on an infinite number of values.
a)
Categorical
b)
Quantitative
c)
Discrete
d)
Continuous
13.
A variable that takes on a finite number of values (usually no decimals).
a)
Categorical
b)
Quantitative
c)
Discrete
d)
Continuous
14.
A study that attempts to survey every individual of the population.
a)
Census
b)
Experiment
c)
Observational Study
d)
Statistic
15.
A sampling distribution of at least 30 will be approx normal even if the population is not.
a)
Central Limit Theorem
b)
Law of Averages
c)
Law of Large Numbers
d)
Conditional Probability
16.
A sample by putting individuals into population-like groups and randomly choosing one group.
a)
Cluster Sample
b)
Stratified Sample
c)
Simple Random Sample
d)
Completely Randomized Design
17.
A family of distributions that always take on positive values and are skewed right.
a)
Chi-Square
b)
Approximately Normal
c)
Z-distribution
d)
T-distributions
18.
A sample obtained by putting individuals into like-groups and randomly choosing some from each.
a)
Cluster Sample
b)
Stratified Sample
c)
Simple Random Sample
d)
Completely Randomized Design
19.
A sample where each individual was randomly chosen and randomly assigned to a treatment.
a)
Cluster Sample
b)
Stratified Sample
c)
Simple Random Sample
d)
Completely Randomized Design
20.
A sample where each individual was randomly chosen from the population.
a)
Cluster Sample
b)
Stratified Sample
c)
Simple Random Sample
d)
Completely Randomized Design
21.
The fraction of the variation that can be explained by the least-squares regression line (r2).
a)
Correlation Coefficient
b)
Coefficient of Determination
c)
Residual
d)
Predicted Value
22.
Explains the linear relationship between two quantitative variables, from -1 to 1.
a)
Correlation Coefficient
b)
Coefficient of Determination
c)
Residual
d)
Predicted Value
23.
Explains how well the regression line fits the data, from 0 (weak) to 1 (strong).
a)
Correlation Coefficient
b)
Coefficient of Determination
c)
Residual
d)
Predicted Value
24.
The probability that an event does NOT happen.
a)
Complement
b)
Supplement
c)
Mutually Exclusive
d)
Random Vaiable
25.
The number of individuals of a sample found in each category in response to a survey.
a)
Components
b)
Chi-Square
c)
Observed Counts
d)
Expected Counts
26.
The individual terms that are added together to form the test statistic for categorical data.
a)
Components
b)
Chi-Square
c)
Observed Counts
d)
Expected Counts
27.
The number of individuals that would be found in each category if the Null hypothesis is true.
a)
Components
b)
Chi-Square
c)
Observed Counts
d)
Expected Counts
28.
The probability that an event will occur given that another event has already occurred.
a)
Conditional Probaility
b)
Mutually Exclusive Events
c)
Binomial Setting
d)
Geometric Setting
29.
__% of all such samples would produce a range of values that would capture the true value.
a)
Confidence Interval
b)
Confidence Level
c)
Hypothesis Test
d)
Critical Value
30.
A range of plausible values for a parameter, based on a statistic.
a)
Confidence Interval
b)
Confidence Level
c)
Hypothesis Test
d)
Critical Value
31.
When the effects of two different variables on a response variable cannot be told apart.
a)
Confounding
b)
Bias
c)
Association
d)
Control
32.
In experiments, when all variables except for the explanatory variable must be kept the same.
a)
Control
b)
Placebo
c)
Nonconfounding
d)
Matched Pairs
33.
A sample selected by taking individuals that select themselves.
a)
Convenience
b)
Volunteer
c)
Bias
d)
Single-blind
34.
A sample selected by taking individuals that were easy to reach.
a)
Convenience
b)
Volunteer
c)
Bias
d)
Selective
35.
When a group of the population does not get accurate representation in a sample.
a)
Undercoverage
b)
Non-response
c)
False Response
d)
Poor Wording
36.
When randomly selected individuals cannot be contacted or refuse to participate.
a)
Undercoverage
b)
Non-response
c)
False Response
d)
Poor Wording
37.
The number of standard deviations to be added/subtracted from the test statistic (z* or t*)
a)
Critical Value
b)
Z-score
c)
Margin of Error
d)
Standard Error
38.
When randomly selected individuals in a sample do not provide accurate information.
a)
Undercoverage
b)
Non-response
c)
False Response
d)
Poor Wording
39.
The total value to be added/subtracted from the test statistic to find the interval max/min.
a)
Critical Value
b)
Z-score
c)
Margin of Error
d)
Standard Error
40.
A study where researchers deliberately impose treatment on the individuals.
a)
Experiment
b)
Observational Study
c)
Survey
d)
Census
41.
The standard deviation of a significance test or confidence interval.
a)
Critical Value
b)
Z-score
c)
Margin of Error
d)
Standard Error
42.
The smallest collection of individuals to which a treatment is to be applied.
a)
Experimental Unit
b)
Sample
c)
Variable
d)
Treatment Group
43.
The variable that may predict the changes in another variable.
a)
Explanatory
b)
Response
c)
Random
d)
Experimental
44.
The (inaccurate) use of a regression line to estimate outside the range of the given data.
a)
Extrapolation
b)
Negative Correlation
c)
Biased Estimator
d)
Residual Calculation
45.
The four evenly sized sections of a set of ordered data.
a)
Quartiles
b)
Mean, Median, and Mode
c)
The Five-Number Summary
d)
Percentiles
46.
Minumum, Q1, Median, Q3, and Maximum values of a data set.
a)
Quartiles
b)
Mean, Median, and Mode
c)
The Five-Number Summary
d)
Percentiles
47.
The amount of counts of a variable out of all counts, often expressed as a percent.
a)
Frequency
b)
Relative Frequency
c)
Proportion
d)
Expected Values
48.
The proportion of observations that are lower than a particular observation.
a)
Percentile
b)
Quartile
c)
Standard Deviation
d)
Mode
49.
The exact counts of a variable.
a)
Frequency
b)
Relative Frequency
c)
Proportion
d)
Expected Values
50.
A graph that shows bars that have ranges for counts of a continuous variable.
a)
Histogram
b)
Bar Graph
c)
Segmented Bar Graph
d)
Density Curve
51.
An outcome of a chance process is more likely to occur if it has not occurred for a long time.
a)
Central Limit Theorem
b)
Law of Averages
c)
Law of Large Numbers
d)
Conditional Probability
52.
The range from Q1 to Q3.
a)
Inner Quartile Range
b)
Median Range
c)
Percentile Range
d)
Mid Range
53.
Making conclusions about a larger population based on sample data.
a)
Statistics
b)
Inference
c)
Experiments
d)
Normal Distribution
54.
The proportion of a chance process will approach a single value as you do more trials.
a)
Central Limit Theorem
b)
Law of Averages
c)
Law of Large Numbers
d)
Conditional Probability
55.
The occurrence of two events at the same time.
a)
Intersection
b)
Union
c)
Mutually Exclusive
d)
Conditional
56.
The occurrence of one event or the other, or both.
a)
Intersection
b)
Union
c)
Mutually Exclusive
d)
Conditional
57.
When it is not possible for two event to occur simultaneously.
a)
Intersection
b)
Union
c)
Mutually Exclusive
d)
Conditional
58.
The distribution of total values for categorical variables on a one-way or two-way table.
a)
Marginal Distribution
b)
Frequency
c)
Summative Distribution
d)
Relative Frequency
59.
A common form of blocking in comparing two different treatments, often on the same sample.
a)
Matched Pairs
b)
Stratified Random Sample
c)
Cluster Sample
d)
Double-Blind
60.
When only either the researchers or the subjects know which treatments were assigned to groups.
a)
Single-Blind
b)
Matched Pairs
c)
Double-Blind
d)
Randomized Design
61.
When neither the researchers nor the subjects know which treatments were assigned to groups.
a)
Single-Blind
b)
Matched Pairs
c)
Double-Blind
d)
Randomized Design
62.
The middle number (resistant to outliers).
a)
Mean
b)
Median
c)
Mode
d)
Expected Value
63.
The sum of the values of the observations divided by the number of observations.
a)
Mean
b)
Median
c)
Mode
d)
Expected Value
64.
A model that describes the overall pattern of a distribution.
a)
Density Curve
b)
Approximately Normal
c)
t distribution
d)
Chi-Square Distribution
65.
The typical or common distance observations are away from the mean.
a)
Standard Deviation
b)
Common Error
c)
Average Residual
d)
Correlation Coefficient
66.
The most common number.
a)
Mean
b)
Median
c)
Mode
d)
Expected Value
67.
A class of density curves that are symmetric, single-peaked, and bell-shaped.
a)
Approximately Normal
b)
Density Curves
c)
Histograms
d)
Unimodel
68.
The claim that we do not believe to be true that we are trying to find evidence against.
a)
Alternative Hypothesis
b)
Significance Test
c)
Null Hypothesis
d)
P-value
69.
Individuals are monitored for measures of variables of interest but not influenced in response.
a)
Observational Study
b)
Experiment
c)
Voluntary Response
d)
Single-Blind
70.
A number that describes some characteristic of a population.
a)
Statistic
b)
Parameter
c)
Sample
d)
Critical Value
71.
An individual that falls well outside the pattern of data.
a)
Outlier
b)
Residual
c)
Deviation
d)
Skewed Data
72.
The probability that the statistic would have taken on a value given the Null hypothesis true.
a)
P-value
b)
Significant Test
c)
Confidence Interval
d)
Critical Value
73.
A number from a sample used to estimate some characteristic of a population.
a)
Statistic
b)
Parameter
c)
Sample
d)
Critical Value
74.
An inactive (fake) treatment for which some subjects may actually respond.
a)
Placebo
b)
Bias
c)
Involuntary Response
d)
Confounding
75.
A smaller group of individuals whose information is used to infer about a larger group.
a)
Population
b)
Statistic
c)
Sample
d)
Parameter
76.
The entire group of individuals which we are interested in knowing something about.
a)
Population
b)
Statistic
c)
Sample
d)
Parameter
77.
The distribution of just one sample.
a)
Sample Distribution
b)
Sampling Distrubution
c)
Population Distribution
d)
Normal Distribution
78.
The distribution of many samples.
a)
Sample Distribution
b)
Sampling Distrubution
c)
Population Distribution
d)
Normal Distribution
79.
The probability that a test will reject the Null when the Alternative is true.
a)
Power
b)
Significance Level
c)
P-value
d)
Margin of Error
80.
The response value a Least Squares Regression Line would expect for a given explanatory value.
a)
Predicted Value
b)
Expected Value
c)
Critical Value
d)
P-value
81.
The maximum minus the minimum.
a)
Median
b)
Range
c)
Quartile
d)
Percentile
82.
A number between 0 and 1 that describes the proportion of an outcome in a chance process.
a)
Probability
b)
Correlation Coefficient
c)
Coefficient of Determination
d)
P-value
83.
Decisions based through a process of chance.
a)
Random
b)
Probability
c)
Unlucky
d)
Lucky
84.
The difference between an observed value and its predicted/expected value.
a)
Residual
b)
Standard Deviation
c)
Regression
d)
Random Variable
85.
The set of all possible outcomes of a chance process.
a)
Sample Space
b)
Sample Distribution
c)
Random Variable
d)
Simple Random Sample
86.
A procedure using a sample statistic to make a decision about the validity of a claim.
a)
Significance Level
b)
Significance Test
c)
Confidence Interval
d)
Confidence Level
87.
A graph that shows the relationship between two quantitative variables using dots.
a)
Scatterplot
b)
Histogram
c)
Stemplot
d)
Density Curve
88.
A fixed value used as a cutoff on what probability is or is not statistically significant.
a)
Significance Level
b)
Significance Test
c)
Confidence Interval
d)
Confidence Level
89.
An imitation of a chance behavior that uses a model that accurately represents the situation.
a)
Simulation
b)
Survey
c)
Experiment
d)
Observational Study
90.
A non-symmetric distribution that has a distinct tail.
a)
Skewed
b)
Bimodal
c)
Approximately Normal
d)
Uniform
91.
A Normal distribution with mean 0 and standard deviation of 1.
a)
Standard
b)
Uniform
c)
Symmetric
d)
Z-distribution
92.
The # of standard deviations an observation falls from the center of a Normal distribution.
a)
Z-score
b)
t-score
c)
Standard Error
d)
Percentile
93.
An event that rarely would have happened just by chance.
a)
Statistically Significant
b)
P-value
c)
Significance Test
d)
Simulation
94.
Occurs when we fail to reject the Null hypothesis when it was actually false.
a)
Type I Error
b)
Type II Error
95.
A family of distributions like the Normal curve expect with more variability in the samples.
a)
t-distributions
b)
Z-distributions
c)
Chi-Square Distributions
d)
Approximately Normal Distributions
96.
Occurs when we reject the Null hypothesis when it was actually true.
a)
Type I Error
b)
Type II Error
97.
When the right and left sides of a distribution are mirror images of each other.
a)
Symmetric
b)
Unimodal
c)
Uniform
d)
Normal
98.
When a distribution is even across the full range of values of the variable.
a)
Symmetric
b)
Unimodal
c)
Uniform
d)
Normal
99.
A diagram used to display the sample space of a chance process involving a sequence of outcomes
a)
Tree Diagram
b)
Stemplot
c)
Probability Plot
d)
Random Variable
100.
The science of data.
a)
Statistics
b)
Inference
c)
Experiments
d)
Graphing
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