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Test your basic knowledge |
CLEP General Mathematics: Probability And Statistics
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Subjects
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clep
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math
Instructions:
Answer 50 questions in 15 minutes.
If you are not ready to take this test, you can
study here
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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. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.
Parameter
Statistic
Descriptive
Reliable measure
2. Is the probability of some event A - assuming event B. Conditional probability is written P(A|B) - and is read 'the probability of A - given B'
A Random vector
Probability density
Conditional probability
Law of Parsimony
3. Some commonly used symbols for sample statistics
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Type I errors
Prior probability
Nominal measurements
4. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.
Likert scale
Particular realizations of a random variable
Seasonal effect
Statistical dispersion
5. To prove the guiding theory further - these predictions are tested as well - as part of the scientific method. If the inference holds true - then the descriptive statistics of the new data increase the soundness of that
hypothesis
The Mean of a random variable
Kurtosis
Average and arithmetic mean
6. Statistics involve methods of using information from a sample to draw conclusions regarding the population.
descriptive statistics
Statistics
Inferential
inferential statistics
7. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
Likert scale
variance of X
An experimental study
A sampling distribution
8. Is a subset of the sample space - to which a probability can be assigned. For example - on rolling a die - 'getting a five or a six' is an event (with a probability of one third if the die is fair).
Law of Parsimony
expected value of X
An event
Joint distribution
9. A subjective estimate of probability.
Marginal distribution
Credence
experimental studies and observational studies.
Skewness
10. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
inferential statistics
Random variables
Null hypothesis
Quantitative variable
11. 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 sample or population mean
Standard error
expected value of X
Sampling
12. Probability of accepting a false null hypothesis.
Beta value
Individual
The median value
Joint probability
13. Is one that explores the correlation between smoking and lung cancer. This type of study typically uses a survey to collect observations about the area of interest and then performs statistical analysis. In this case - the researchers would collect o
Power of a test
Observational study
Sampling frame
Type II errors
14. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).
The standard deviation
The average - or arithmetic mean
The Range
Parameter - or 'statistical parameter'
15. 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.
Simpson's Paradox
Inferential
Type 2 Error
A population or statistical population
16. (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 variance of a random variable
Probability density functions
Posterior probability
17. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.
The sample space
Sampling Distribution
quantitative variables
Law of Large Numbers
18. 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.
Lurking variable
Nominal measurements
Marginal probability
Posterior probability
19. Cov[X - Y] :
The Expected value
Statistical inference
s-algebras
covariance of X and Y
20. 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.
Marginal distribution
Pairwise independence
observational study
Sample space
21. Is a function that gives the probability of all elements in a given space: see List of probability distributions
The Covariance between two random variables X and Y - with expected values E(X) =
The sample space
Reliable measure
A probability distribution
22. Given two jointly distributed random variables X and Y - the conditional probability distribution of Y given X (written 'Y | X') is the probability distribution of Y when X is known to be a particular value.
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
s-algebras
Power of a test
Conditional distribution
23. Error also refers to the extent to which individual observations in a sample differ from a central value - such as
Correlation
Experimental and observational studies
the sample or population mean
Probability and statistics
24. A list of individuals from which the sample is actually selected.
Likert scale
Greek letters
Law of Large Numbers
Sampling frame
25. 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
A Distribution function
Independent Selection
Law of Parsimony
26.
Sample space
the population mean
Alpha value (Level of Significance)
The Mean of a random variable
27. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.
Seasonal effect
Variability
P-value
Outlier
28. When there is an even number of values...
A Random vector
Seasonal effect
Lurking variable
That is the median value
29. Is its expected value. The mean (or sample mean of a data set is just the average value.
Descriptive
The Mean of a random variable
The standard deviation
Probability and statistics
30. Describes the spread in the values of the sample statistic when many samples are taken.
An event
Placebo effect
categorical variables
Variability
31. Describes a characteristic of an individual to be measured or observed.
observational study
Variable
Ratio measurements
Lurking variable
32. Failing to reject a false null hypothesis.
Type 2 Error
Probability and statistics
Beta value
The Covariance between two random variables X and Y - with expected values E(X) =
33. Is denoted by - pronounced 'x bar'.
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
the population mean
Lurking variable
Trend
34. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.
Parameter - or 'statistical parameter'
the sample or population mean
s-algebras
Bias
35. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Pairwise independence
variance of X
the sample or population mean
nominal - ordinal - interval - and ratio
36. The standard deviation of a sampling distribution.
A probability space
Correlation
the population variance
Standard error
37. A numerical facsimilie or representation of a real-world phenomenon.
quantitative variables
Simulation
Reliable measure
Law of Parsimony
38. Is defined as the expected value of random variable (X -
applied statistics
The Covariance between two random variables X and Y - with expected values E(X) =
The average - or arithmetic mean
Bias
39. 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).
An Elementary event
Joint probability
A probability density function
Qualitative variable
40. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as
Probability density functions
A sample
quantitative variables
Alpha value (Level of Significance)
41. Is used to describe probability in a continuous probability distribution. For example - you can't say that the probability of a man being six feet tall is 20% - but you can say he has 20% of chances of being between five and six feet tall. Probabilit
Probability density functions
Probability density
Law of Parsimony
The average - or arithmetic mean
42. Is a parameter that indexes a family of probability distributions.
Law of Large Numbers
A population or statistical population
A Statistical parameter
A Random vector
43. A numerical measure that assesses the strength of a linear relationship between two variables.
Step 3 of a statistical experiment
Null hypothesis
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Correlation coefficient
44. (or atomic event) is an event with only one element. For example - when pulling a card out of a deck - 'getting the jack of spades' is an elementary event - while 'getting a king or an ace' is not.
Parameter
An Elementary event
the population correlation
Conditional probability
45. Is a measure of the 'peakedness' of the probability distribution of a real-valued random variable. Higher kurtosis means more of the variance is due to infrequent extreme deviations - as opposed to frequent modestly sized deviations.
Kurtosis
Descriptive statistics
Outlier
Statistical inference
46. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data
Valid measure
s-algebras
The variance of a random variable
Posterior probability
47. To find the median value of a set of numbers: Arrange the numbers in numerical order. Locate the two middle numbers in the list. Find the average of those two middle values.
Average and arithmetic mean
A population or statistical population
The median value
That value is the median value
48. S^2
descriptive statistics
the population variance
hypotheses
A statistic
49. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.
Law of Large Numbers
categorical variables
Parameter - or 'statistical parameter'
Atomic event
50. Gives the probability of events in a probability space.
Type II errors
Inferential statistics
A Probability measure
An experimental study