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Test your basic knowledge |
CLEP General Mathematics: Probability And Statistics
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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. Long-term upward or downward movement over time.
Trend
the population correlation
methods of least squares
Variability
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'
An estimate of a parameter
An experimental study
Conditional probability
The sample space
3. Another name for elementary event.
Atomic event
Probability density
Ordinal measurements
A Random vector
4. Two variables such that their effects on the response variable cannot be distinguished from each other.
Statistics
Confounded variables
Lurking variable
Descriptive statistics
5. Some commonly used symbols for sample statistics
Variable
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Ratio measurements
Probability density functions
6. Data are gathered and correlations between predictors and response are investigated.
Joint distribution
observational study
Type 2 Error
Kurtosis
7. Some commonly used symbols for population parameters
Valid measure
A probability space
Coefficient of determination
the population mean
8. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.
Binomial experiment
Average and arithmetic mean
Cumulative distribution functions
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
9. The collection of all possible outcomes in an experiment.
A Probability measure
Mutual independence
Sample space
Sampling Distribution
10. 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
Observational study
The Mean of a random variable
Lurking variable
Beta value
11.
Skewness
Inferential
Simpson's Paradox
the population mean
12. Are simply two different terms for the same thing. Add the given values
applied statistics
Sample space
Law of Parsimony
Average and arithmetic mean
13. Error also refers to the extent to which individual observations in a sample differ from a central value - such as
A sample
Residuals
the sample or population mean
A probability distribution
14. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.
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15. A numerical facsimilie or representation of a real-world phenomenon.
Statistical dispersion
Binary data
The Covariance between two random variables X and Y - with expected values E(X) =
Simulation
16. In particular - the pdf of the standard normal distribution is denoted by
The median value
A Statistical parameter
f(z) - and its cdf by F(z).
A statistic
17. Interpretation of statistical information in that the assumption is that whatever is proposed as a cause has no effect on the variable being measured can often involve the development of a
Null hypothesis
Reliable measure
Lurking variable
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
18. A numerical measure that describes an aspect of a population.
Treatment
Independence or Statistical independence
the population mean
Parameter
19. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.
A data set
P-value
The Mean of a random variable
Atomic event
20. A variable that has an important effect on the response variable and the relationship among the variables in a study but is not one of the explanatory variables studied either because it is unknown or not measured.
Lurking variable
Cumulative distribution functions
Inferential statistics
The standard deviation
21. Cov[X - Y] :
A data set
The standard deviation
covariance of X and Y
Sampling frame
22. Is the set of possible outcomes of an experiment. For example - the sample space for rolling a six-sided die will be {1 - 2 - 3 - 4 - 5 - 6}.
An experimental study
The sample space
expected value of X
Simulation
23. Can refer either to a sample not being representative of the population - or to the difference between the expected value of an estimator and the true value.
the population variance
Bias
A sampling distribution
Power of a test
24. Where the null hypothesis is falsely rejected giving a 'false positive'.
Simulation
Probability density functions
Type I errors
Joint probability
25. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)
s-algebras
Residuals
Simulation
Ordinal measurements
26. Of a group of numbers is the center point of all those number values.
Standard error
Parameter
Marginal distribution
The average - or arithmetic mean
27. A measure that is relevant or appropriate as a representation of that property.
observational study
Correlation
Statistical dispersion
Valid measure
28. 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).
Bias
Posterior probability
Joint probability
the sample or population mean
29. Samples are drawn from two different populations such that the sample data drawn from one population is completely unrelated to the selection of sample data from the other population.
A sample
An experimental study
Independent Selection
the population correlation
30. A data value that falls outside the overall pattern of the graph.
Correlation coefficient
Outlier
Type II errors
experimental studies and observational studies.
31. Is the length of the smallest interval which contains all the data.
Count data
Pairwise independence
The Range
Conditional probability
32. Gives the probability of events in a probability space.
Skewness
A Probability measure
Random variables
The Expected value
33. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
Type I errors
Descriptive
Step 3 of a statistical experiment
Likert scale
34. Failing to reject a false null hypothesis.
P-value
Type 2 Error
A Statistical parameter
An experimental study
35. 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.
Binary data
A population or statistical population
Individual
quantitative variables
36. Is a function that gives the probability of all elements in a given space: see List of probability distributions
A probability distribution
Estimator
Simple random sample
A probability space
37. 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.
Conditional distribution
Skewness
Block
Residuals
38. Var[X] :
methods of least squares
That value is the median value
variance of X
Quantitative variable
39. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data
Seasonal effect
A random variable
Reliable measure
Posterior probability
40. (cdfs) are denoted by upper case letters - e.g. F(x).
Cumulative distribution functions
applied statistics
Joint distribution
Sampling frame
41. Probability of rejecting a true null hypothesis.
Step 3 of a statistical experiment
An experimental study
Alpha value (Level of Significance)
Statistical dispersion
42. Statistical methods can be used for summarizing or describing a collection of data; this is called
Quantitative variable
Likert scale
descriptive statistics
A probability density function
43. (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
Ratio measurements
Observational study
A likelihood function
Confounded variables
44. When you have two or more competing models - choose the simpler of the two models.
Law of Parsimony
Probability and statistics
Count data
Parameter - or 'statistical parameter'
45. Is defined as the expected value of random variable (X -
Statistical adjustment
The Covariance between two random variables X and Y - with expected values E(X) =
s-algebras
Descriptive
46. Is a sample space over which a probability measure has been defined.
That is the median value
observational study
The standard deviation
A probability space
47. ?
the population correlation
A data point
Outlier
Binomial experiment
48. 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
Cumulative distribution functions
Type 1 Error
Probability
Ratio measurements
49. Is the probability distribution - under repeated sampling of the population - of a given statistic.
Ratio measurements
A sampling distribution
A data set
Divide the sum by the number of values.
50. S^2
Joint distribution
the population variance
Type 1 Error
Variable