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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. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.
Ratio measurements
Binomial experiment
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Variability
2. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as
Type I errors
categorical variables
Parameter - or 'statistical parameter'
Bias
3. The collection of all possible outcomes in an experiment.
the population mean
Variable
Independence or Statistical independence
Sample space
4. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.
Credence
Type I errors
Placebo effect
the population variance
5. Rejecting a true null hypothesis.
Type 1 Error
Probability density functions
Statistical adjustment
The average - or arithmetic mean
6. A group of individuals sharing some common features that might affect the treatment.
Block
Step 3 of a statistical experiment
A random variable
Binary data
7. 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
Joint probability
Coefficient of determination
observational study
8. S^2
Experimental and observational studies
Simpson's Paradox
The standard deviation
the population variance
9. Statistical methods can be used for summarizing or describing a collection of data; this is called
descriptive statistics
Ordinal measurements
Type 2 Error
Joint distribution
10. ?
A random variable
the population correlation
Parameter
Quantitative variable
11. There are two major types of causal statistical studies: In both types of studies - the effect of differences of an independent variable (or variables) on the behavior of the dependent variable are observed. The difference between the two types lies
inferential statistics
Sampling frame
A probability space
experimental studies and observational studies.
12. Is the length of the smallest interval which contains all the data.
experimental studies and observational studies.
A data set
Independent Selection
The Range
13. Two variables such that their effects on the response variable cannot be distinguished from each other.
Interval measurements
A data set
Confounded variables
Marginal distribution
14. 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.
Nominal measurements
Estimator
Prior probability
Descriptive statistics
15. Long-term upward or downward movement over time.
Experimental and observational studies
Kurtosis
The Covariance between two random variables X and Y - with expected values E(X) =
Trend
16. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data
nominal - ordinal - interval - and ratio
Probability and statistics
Nominal measurements
Posterior probability
17. 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.
hypothesis
Correlation
Posterior probability
Conditional distribution
18. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.
Mutual independence
The variance of a random variable
Interval measurements
Particular realizations of a random variable
19. ?r
Step 1 of a statistical experiment
The Range
Type 2 Error
the population cumulants
20. Gives the probability distribution for a continuous random variable.
s-algebras
Random variables
A probability density function
experimental studies and observational studies.
21. E[X] :
An estimate of a parameter
expected value of X
Simple random sample
Type 1 Error
22. To find the average - or arithmetic mean - of a set of numbers:
Sampling Distribution
Divide the sum by the number of values.
Greek letters
Probability
23. 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.
s-algebras
A data set
Lurking variable
Sampling
24. A data value that falls outside the overall pattern of the graph.
Outlier
That value is the median value
Experimental and observational studies
the population mean
25. 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).
Conditional distribution
Quantitative variable
An event
Likert scale
26. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.
Count data
A Probability measure
Variability
An estimate of a parameter
27. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.
Statistics
Bias
Random variables
A population or statistical population
28. 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.
Coefficient of determination
Type 2 Error
Placebo effect
Statistics
29. Failing to reject a false null hypothesis.
Ordinal measurements
Cumulative distribution functions
Probability and statistics
Type 2 Error
30. 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 estimate of a parameter
Estimator
Kurtosis
A Statistical parameter
31. (cdfs) are denoted by upper case letters - e.g. F(x).
Cumulative distribution functions
A data point
Qualitative variable
Reliable measure
32. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.
Statistical adjustment
Binary data
Random variables
Joint distribution
33. Is a measure of the asymmetry of the probability distribution of a real-valued random variable. Roughly speaking - a distribution has positive skew (right-skewed) if the higher tail is longer and negative skew (left-skewed) if the lower tail is longe
Skewness
Statistical inference
Confounded variables
Correlation
34. 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 standard deviation
Probability density
Probability density functions
Beta value
35. Cov[X - Y] :
Independence or Statistical independence
covariance of X and Y
Sample space
A Statistical parameter
36. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).
Probability density functions
Bias
Trend
Correlation
37. A numerical measure that describes an aspect of a population.
Observational study
Inferential
applied statistics
Parameter
38. 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.
Law of Large Numbers
Marginal distribution
the sample or population mean
nominal - ordinal - interval - and ratio
39. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).
categorical variables
Bias
A probability space
The standard deviation
40. 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 random variable
Greek letters
Estimator
Statistics
41. Is a sample space over which a probability measure has been defined.
A probability space
the population mean
Conditional distribution
Type 2 Error
42. 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
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
The sample space
Null hypothesis
Seasonal effect
43. A numerical measure that describes an aspect of a sample.
Statistic
Type 1 Error
P-value
Sample space
44. 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
The variance of a random variable
Coefficient of determination
The sample space
Probability and statistics
45. Of a group of numbers is the center point of all those number values.
The average - or arithmetic mean
Law of Parsimony
Block
The Range
46. Many statistical methods seek to minimize the mean-squared error - and these are called
methods of least squares
Correlation coefficient
Step 3 of a statistical experiment
the population correlation
47. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.
Quantitative variable
Statistical dispersion
Placebo effect
Sampling Distribution
48. In particular - the pdf of the standard normal distribution is denoted by
f(z) - and its cdf by F(z).
A probability distribution
Type II errors
Ratio measurements
49. 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.
Block
Sampling frame
Independent Selection
Null hypothesis
50. Any specific experimental condition applied to the subjects
Variability
Nominal measurements
Interval measurements
Treatment