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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. 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.
Statistics
Conditional probability
applied statistics
Marginal distribution
2. A numerical measure that describes an aspect of a population.
Inferential
Parameter
Coefficient of determination
Ordinal measurements
3. Descriptive statistics and inferential statistics (a.k.a. - predictive statistics) together comprise
applied statistics
Skewness
The sample space
Type 2 Error
4. 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.
Simple random sample
Estimator
Beta value
Sampling
5. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.
Binary data
Probability density
Random variables
Statistical dispersion
6. A list of individuals from which the sample is actually selected.
Simpson's Paradox
The Range
Sampling frame
inferential statistics
7. ?r
An experimental study
the population cumulants
Descriptive
Sampling frame
8. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)
Individual
Type I errors
methods of least squares
Sampling frame
9. A measurement such that the random error is small
Joint probability
The Covariance between two random variables X and Y - with expected values E(X) =
Reliable measure
Type I errors
10. Is a typed measurement - it can be a boolean value - a real number - a vector (in which case it's also called a data vector) - etc.
Bias
expected value of X
Random variables
A data point
11. Are usually written in upper case roman letters: X - Y - etc.
Sampling Distribution
Bias
hypotheses
Random variables
12. To find the average - or arithmetic mean - of a set of numbers:
the population variance
The average - or arithmetic mean
Divide the sum by the number of values.
Quantitative variable
13. Performing the experiment following the experimental protocol and analyzing the data following the experimental protocol. 4. Further examining the data set in secondary analyses - to suggest new hypotheses for future study. 5. Documenting and present
Residuals
Step 3 of a statistical experiment
The average - or arithmetic mean
Kurtosis
14. 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
Independence or Statistical independence
Null hypothesis
Prior probability
Step 2 of a statistical experiment
15. A numerical measure that describes an aspect of a sample.
Valid measure
Experimental and observational studies
Statistic
Simpson's Paradox
16.
the population mean
Inferential statistics
Parameter - or 'statistical parameter'
s-algebras
17. 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).
Step 3 of a statistical experiment
Joint probability
Skewness
the population correlation
18. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.
Descriptive statistics
Atomic event
Descriptive
That value is the median value
19. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.
Conditional probability
Type II errors
Bias
Correlation coefficient
20. 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
The variance of a random variable
Correlation
Probability density
Statistical dispersion
21. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
covariance of X and Y
That value is the median value
Block
Pairwise independence
22. When you have two or more competing models - choose the simpler of the two models.
An event
Mutual independence
Law of Parsimony
Step 1 of a statistical experiment
23. (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
Variable
Quantitative variable
Statistic
The Expected value
24. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.
Conditional probability
Power of a test
Statistical adjustment
Placebo effect
25. 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.
Individual
s-algebras
Marginal probability
the sample or population mean
26. 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.
Simpson's Paradox
Beta value
Binomial experiment
Marginal distribution
27. Is a measure of its statistical dispersion - indicating how far from the expected value its values typically are. The variance of random variable X is typically designated as - - or simply s2.
The variance of a random variable
Estimator
Marginal distribution
Statistical dispersion
28. ?
Sampling Distribution
Mutual independence
Step 2 of a statistical experiment
the population correlation
29. (cdfs) are denoted by upper case letters - e.g. F(x).
Average and arithmetic mean
Individual
Cumulative distribution functions
Kurtosis
30. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as
Random variables
quantitative variables
hypotheses
Probability
31. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)
P-value
Standard error
s-algebras
Joint distribution
32. 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.
An experimental study
Inferential
Null hypothesis
A population or statistical population
33. Planning the research - including finding the number of replicates of the study - using the following information: preliminary estimates regarding the size of treatment effects - alternative hypotheses - and the estimated experimental variability. Co
Standard error
Step 1 of a statistical experiment
Step 3 of a statistical experiment
Statistical dispersion
34. (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
Binomial experiment
Placebo effect
A likelihood function
Correlation coefficient
35. Have no meaningful rank order among values.
A statistic
Average and arithmetic mean
Nominal measurements
Sample space
36. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.
A data set
Block
Prior probability
The variance of a random variable
37. 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.
Kurtosis
Bias
Standard error
That value is the median value
38. Is its expected value. The mean (or sample mean of a data set is just the average value.
Binary data
the population variance
The Mean of a random variable
Prior probability
39. The probability of correctly detecting a false null hypothesis.
Observational study
quantitative variables
Power of a test
covariance of X and Y
40. Is a parameter that indexes a family of probability distributions.
A Statistical parameter
Dependent Selection
descriptive statistics
Statistic
41. Cov[X - Y] :
A random variable
covariance of X and Y
Probability and statistics
quantitative variables
42. Is data arising from counting that can take only non-negative integer values.
Mutual independence
the population variance
Count data
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
43. A numerical facsimilie or representation of a real-world phenomenon.
Simulation
descriptive statistics
Step 1 of a statistical experiment
A Probability measure
44. Of a group of numbers is the center point of all those number values.
Descriptive
Cumulative distribution functions
Power of a test
The average - or arithmetic mean
45. 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.
Independent Selection
Outlier
A Random vector
An estimate of a parameter
46. 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.
the population mean
Seasonal effect
The variance of a random variable
experimental studies and observational studies.
47. Another name for elementary event.
observational study
A probability distribution
Atomic event
A Probability measure
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.
Variable
The median value
Block
Particular realizations of a random variable
49. S^2
Random variables
the population variance
Ordinal measurements
hypothesis
50. When there is an even number of values...
Sampling
That value is the median value
Seasonal effect
That is the median value