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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. A list of individuals from which the sample is actually selected.
Sampling frame
Observational study
Coefficient of determination
Greek letters
2. A sample selected in such a way that each individual is equally likely to be selected as well as any group of size n is equally likely to be selected.
Correlation
A probability distribution
covariance of X and Y
Simple random sample
3. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
Quantitative variable
That is the median value
Beta value
Particular realizations of a random variable
4. 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.
Inferential
Standard error
experimental studies and observational studies.
A Distribution function
5. Describes a characteristic of an individual to be measured or observed.
methods of least squares
Variable
Variability
applied statistics
6. Is defined as the expected value of random variable (X -
Dependent Selection
Observational study
The Covariance between two random variables X and Y - with expected values E(X) =
Type 2 Error
7. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.
Beta value
An experimental study
Statistical inference
An estimate of a parameter
8. Is its expected value. The mean (or sample mean of a data set is just the average value.
Inferential statistics
A Probability measure
Type II errors
The Mean of a random variable
9. 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
Credence
Standard error
Trend
Step 3 of a statistical experiment
10. 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.
Alpha value (Level of Significance)
The median value
Observational study
Sampling
11. 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
covariance of X and Y
inferential statistics
Pairwise independence
12. Some commonly used symbols for sample statistics
Law of Large Numbers
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Joint probability
Residuals
13. Probability of accepting a false null hypothesis.
That value is the median value
Bias
Beta value
A probability space
14. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.
observational study
Sampling frame
Placebo effect
Cumulative distribution functions
15. Is data that can take only two values - usually represented by 0 and 1.
Binary data
methods of least squares
Valid measure
Lurking variable
16. Have imprecise differences between consecutive values - but have a meaningful order to those values
Ordinal measurements
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Observational study
Credence
17. When there is an even number of values...
Correlation coefficient
The Expected value
covariance of X and Y
That is the median value
18. When you have two or more competing models - choose the simpler of the two models.
Law of Parsimony
applied statistics
An Elementary event
That is the median value
19. 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.
The variance of a random variable
P-value
Marginal probability
Probability density
20. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively
Residuals
Variable
Type 2 Error
Statistical inference
21. Var[X] :
Outlier
Statistical adjustment
Greek letters
variance of X
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.
The variance of a random variable
Skewness
Marginal probability
An experimental study
23. A measure that is relevant or appropriate as a representation of that property.
Type 2 Error
The median value
Random variables
Valid measure
24. Samples are drawn from two different populations such that there is a matching of the first sample data drawn and a corresponding data value in the second sample data.
Dependent Selection
Posterior probability
Conditional distribution
Cumulative distribution functions
25. Is a parameter that indexes a family of probability distributions.
A Random vector
categorical variables
Law of Parsimony
A Statistical parameter
26. Is a sample space over which a probability measure has been defined.
the population correlation
Qualitative variable
An event
A probability space
27. Any specific experimental condition applied to the subjects
Treatment
A population or statistical population
Placebo effect
Descriptive
28. Have no meaningful rank order among values.
The sample space
Nominal measurements
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
A Distribution function
29. Are simply two different terms for the same thing. Add the given values
Statistical dispersion
Average and arithmetic mean
Ordinal measurements
Statistical adjustment
30. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.
Particular realizations of a random variable
Joint probability
Quantitative variable
A Probability measure
31. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.
Statistical dispersion
Placebo effect
inferential statistics
The Expected value
32. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.
Nominal measurements
Particular realizations of a random variable
Statistical adjustment
Atomic event
33. Is that part of a population which is actually observed.
A sample
Average and arithmetic mean
Interval measurements
Likert scale
34. 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
Ordinal measurements
Sampling
Null hypothesis
The Covariance between two random variables X and Y - with expected values E(X) =
35. Are usually written in upper case roman letters: X - Y - etc.
Random variables
That is the median value
Bias
Alpha value (Level of Significance)
36. The probability of correctly detecting a false null hypothesis.
Marginal probability
Statistical adjustment
Power of a test
hypotheses
37. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.
Binomial experiment
applied statistics
Qualitative variable
Experimental and observational studies
38. 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.
Simulation
Bias
Parameter
Random variables
39. Error also refers to the extent to which individual observations in a sample differ from a central value - such as
A data set
the sample or population mean
Step 2 of a statistical experiment
applied statistics
40. There are four main levels of measurement used in statistics: Each of these have different degrees of usefulness in statistical research.
Probability density functions
Type 1 Error
nominal - ordinal - interval - and ratio
Bias
41. Gives the probability of events in a probability space.
Step 2 of a statistical experiment
methods of least squares
A Probability measure
Statistic
42. 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
Seasonal effect
Residuals
A random variable
Descriptive statistics
43. Can be - for example - the possible outcomes of a dice roll (but it is not assigned a value). The distribution function of a random variable gives the probability of different results. We can also derive the mean and variance of a random variable.
A sample
Count data
Statistical dispersion
A random variable
44. (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
An experimental study
Cumulative distribution functions
Variable
A likelihood function
45. Some commonly used symbols for population parameters
quantitative variables
s-algebras
the population mean
Statistical adjustment
46. 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
A statistic
Descriptive
An Elementary event
47. 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.
An Elementary event
Variability
Kurtosis
The average - or arithmetic mean
48. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Pairwise independence
Count data
expected value of X
Seasonal effect
49. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).
Interval measurements
s-algebras
The standard deviation
applied statistics
50. 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
Coefficient of determination
Probability
hypothesis
quantitative variables