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Test your basic knowledge |
CLEP General Mathematics: Probability And Statistics
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Instructions:
Answer 50 questions in 15 minutes.
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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. Is the probability of two events occurring together. The joint probability of A and B is written P(A and B) or P(A - B).
Joint probability
Law of Large Numbers
A data point
Step 3 of a statistical experiment
2. Is a function of the known data that is used to estimate an unknown parameter; an estimate is the result from the actual application of the function to a particular set of data. The mean can be used as an estimator.
A Distribution function
Estimator
the population variance
expected value of X
3. A collection of events is mutually independent if for any subset of the collection - the joint probability of all events occurring is equal to the product of the joint probabilities of the individual events. Think of the result of a series of coin-fl
nominal - ordinal - interval - and ratio
Seasonal effect
Step 2 of a statistical experiment
Mutual independence
4. Is used in 'mathematical statistics' (alternatively - 'statistical theory') to study the sampling distributions of sample statistics and - more generally - the properties of statistical procedures. The use of any statistical method is valid when the
Probability
nominal - ordinal - interval - and ratio
Cumulative distribution functions
Prior probability
5. A list of individuals from which the sample is actually selected.
Binomial experiment
Individual
categorical variables
Sampling frame
6. Is its expected value. The mean (or sample mean of a data set is just the average value.
A random variable
A data point
An Elementary event
The Mean of a random variable
7. Many statistical methods seek to minimize the mean-squared error - and these are called
Outlier
Correlation coefficient
methods of least squares
Conditional probability
8. Changes over time that show a regular periodicity in the data where regular means over a fixed interval; the time between repetitions is called the period.
Divide the sum by the number of values.
Credence
Seasonal effect
A probability distribution
9. Is a set of entities about which statistical inferences are to be drawn - often based on random sampling. One can also talk about a population of measurements or values.
Law of Parsimony
Observational study
A population or statistical population
A data point
10. Another name for elementary event.
inferential statistics
Atomic event
Kurtosis
variance of X
11. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as
Simpson's Paradox
The average - or arithmetic mean
quantitative variables
Type 1 Error
12. (or multivariate random variable) is a vector whose components are random variables on the same probability space.
Block
A Random vector
Parameter - or 'statistical parameter'
inferential statistics
13. Is a process of selecting observations to obtain knowledge about a population. There are many methods to choose on which sample to do the observations.
The Range
Seasonal effect
Correlation coefficient
Sampling
14. Gives the probability distribution for a continuous random variable.
Estimator
A probability density function
Simulation
A likelihood function
15. The collection of all possible outcomes in an experiment.
Sample space
Marginal probability
Parameter
A probability distribution
16. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.
Type II errors
the population mean
Probability
Seasonal effect
17. Is the function that gives the probability distribution of a random variable. It cannot be negative - and its integral on the probability space is equal to 1.
Greek letters
Parameter - or 'statistical parameter'
A Distribution function
the population mean
18. Summarize the population data by describing what was observed in the sample numerically or graphically. Numerical descriptors include mean and standard deviation for continuous data types (like heights or weights) - while frequency and percentage are
Descriptive statistics
An estimate of a parameter
Estimator
applied statistics
19. Probability of accepting a false null hypothesis.
Average and arithmetic mean
Beta value
A probability space
Mutual independence
20. (or expectation) of a random variable is the sum of the probability of each possible outcome of the experiment multiplied by its payoff ('value'). Thus - it represents the average amount one 'expects' to win per bet if bets with identical odds are re
The Expected value
The Mean of a random variable
Type II errors
Treatment
21. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.
Power of a test
the sample or population mean
Likert scale
Binomial experiment
22. Involves taking measurements of the system under study - manipulating the system - and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements.
A likelihood function
An experimental study
The median value
Variability
23. Statistical methods can be used for summarizing or describing a collection of data; this is called
Statistical inference
Particular realizations of a random variable
hypotheses
descriptive statistics
24. Is the study of the collection - organization - analysis - and interpretation of data. It deals with all aspects of this - including the planning of data collection in terms of the design of surveys and experiments.
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Statistics
Conditional probability
That is the median value
25. Is a sample and the associated data points.
Probability and statistics
A data set
Divide the sum by the number of values.
Step 2 of a statistical experiment
26. Is denoted by - pronounced 'x bar'.
A Random vector
The average - or arithmetic mean
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
The standard deviation
27. Are two related but separate academic disciplines. Statistical analysis often uses probability distributions - and the two topics are often studied together. However - probability theory contains much that is of mostly of mathematical interest and no
Probability and statistics
covariance of X and Y
descriptive statistics
Simpson's Paradox
28. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)
Individual
Probability density functions
hypothesis
The standard deviation
29. A variable describes an individual by placing the individual into a category or a group.
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Alpha value (Level of Significance)
Qualitative variable
Probability density
30. Have imprecise differences between consecutive values - but have a meaningful order to those values
That is the median value
categorical variables
Ordinal measurements
inferential statistics
31. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
Block
Likert scale
Descriptive
A statistic
32. In number theory - scatter plots of data generated by a distribution function may be transformed with familiar tools used in statistics to reveal underlying patterns - which may then lead to
Posterior probability
The average - or arithmetic mean
observational study
hypotheses
33. Rejecting a true null hypothesis.
An experimental study
Type 1 Error
Placebo effect
An event
34. Is defined as the expected value of random variable (X -
Conditional distribution
Null hypothesis
the sample or population mean
The Covariance between two random variables X and Y - with expected values E(X) =
35. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
Quantitative variable
Pairwise independence
Estimator
A probability density function
36. Failing to reject a false null hypothesis.
Type 2 Error
Confounded variables
Posterior probability
Random variables
37. Patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations - and are then used for drawing inferences about the process or population being studied; this is called
inferential statistics
applied statistics
experimental studies and observational studies.
A data set
38. In particular - the pdf of the standard normal distribution is denoted by
f(z) - and its cdf by F(z).
Nominal measurements
A random variable
the sample or population mean
39. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.
Credence
Probability
Step 3 of a statistical experiment
Descriptive
40. Long-term upward or downward movement over time.
Count data
Quantitative variable
Trend
Alpha value (Level of Significance)
41. Given two jointly distributed random variables X and Y - the marginal distribution of X is simply the probability distribution of X ignoring information about Y.
s-algebras
Marginal distribution
Type I errors & Type II errors
Ratio measurements
42. (cdfs) are denoted by upper case letters - e.g. F(x).
Skewness
Cumulative distribution functions
Prior probability
A Probability measure
43. A data value that falls outside the overall pattern of the graph.
Outlier
Sampling
Ordinal measurements
Experimental and observational studies
44. Have both a meaningful zero value and the distances between different measurements defined; they provide the greatest flexibility in statistical methods that can be used for analyzing the data
Skewness
Inferential
A sample
Ratio measurements
45. Are usually written in upper case roman letters: X - Y - etc.
Lurking variable
Binary data
Placebo effect
Random variables
46. Given two random variables X and Y - the joint distribution of X and Y is the probability distribution of X and Y together.
The Mean of a random variable
The sample space
Trend
Joint distribution
47. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.
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48. Is the exact middle value of a set of numbers Arrange the numbers in numerical order. Find the value in the middle of the list.
The median value
The Range
A sample
Type II errors
49. (or just likelihood) is a conditional probability function considered a function of its second argument with its first argument held fixed. For example - imagine pulling a numbered ball with the number k from a bag of n balls - numbered 1 to n. Then
Cumulative distribution functions
A likelihood function
Trend
A Probability measure
50. Is the probability of an event - ignoring any information about other events. The marginal probability of A is written P(A). Contrast with conditional probability.
Mutual independence
A Probability measure
Marginal probability
A data set