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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. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Pairwise independence
Bias
Kurtosis
Sampling frame
2. The probability of correctly detecting a false null hypothesis.
Power of a test
Probability density functions
descriptive statistics
covariance of X and Y
3. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.
Standard error
Probability density functions
An estimate of a parameter
Simulation
4. 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
Confounded variables
Independent Selection
Greek letters
5. Working from a null hypothesis two basic forms of error are recognized:
Conditional distribution
Type I errors & Type II errors
Inferential statistics
The Range
6. A subjective estimate of probability.
Pairwise independence
Parameter
Credence
the population mean
7. Can be a population parameter - a distribution parameter - an unobserved parameter (with different shades of meaning). In statistics - this is often a quantity to be estimated.
8. Have no meaningful rank order among values.
Average and arithmetic mean
Nominal measurements
Variable
Interval measurements
9. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.
10. Failing to reject a false null hypothesis.
Type 2 Error
Nominal measurements
Random variables
Inferential
11. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.
Credence
Particular realizations of a random variable
P-value
covariance of X and Y
12. 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.
The variance of a random variable
Law of Large Numbers
Kurtosis
Interval measurements
13. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)
A Probability measure
s-algebras
Variability
Parameter - or 'statistical parameter'
14. Any specific experimental condition applied to the subjects
the population mean
The Expected value
That is the median value
Treatment
15. 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).
Marginal distribution
Simulation
The sample space
An event
16. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data
Posterior probability
the population cumulants
Alpha value (Level of Significance)
A probability density function
17. 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
variance of X
Step 1 of a statistical experiment
A likelihood function
Count data
18. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.
Trend
the population cumulants
Prior probability
Observational study
19. Is a sample space over which a probability measure has been defined.
Treatment
expected value of X
A probability space
Probability
20. When you have two or more competing models - choose the simpler of the two models.
Law of Parsimony
categorical variables
P-value
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
21. 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.
Bias
Step 3 of a statistical experiment
Lurking variable
categorical variables
22. Two variables such that their effects on the response variable cannot be distinguished from each other.
Null hypothesis
Confounded variables
A data point
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
23. Are simply two different terms for the same thing. Add the given values
Average and arithmetic mean
Statistical dispersion
descriptive statistics
The sample space
24. Have both a meaningful zero value and the distances between different measurements defined; they provide the greatest flexibility in statistical methods that can be used for analyzing the data
Ratio measurements
Correlation coefficient
Conditional distribution
Probability density
25. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as
Greek letters
quantitative variables
Lurking variable
Statistics
26. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.
Valid measure
Treatment
Bias
An experimental study
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.
Sampling
Type 1 Error
experimental studies and observational studies.
The variance of a random variable
28. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).
Probability density functions
Step 3 of a statistical experiment
Conditional distribution
Law of Large Numbers
29. Is denoted by - pronounced 'x bar'.
Independence or Statistical independence
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
A Probability measure
An Elementary event
30. 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
Probability
Residuals
An Elementary event
Simpson's Paradox
31. Is data arising from counting that can take only non-negative integer values.
Valid measure
Count data
Step 3 of a statistical experiment
quantitative variables
32. 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.
A sample
Outlier
The average - or arithmetic mean
Estimator
33. Error also refers to the extent to which individual observations in a sample differ from a central value - such as
A Distribution function
Simple random sample
the sample or population mean
A data set
34. 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.
That value is the median value
A sampling distribution
Qualitative variable
the population cumulants
35. Is its expected value. The mean (or sample mean of a data set is just the average value.
Simulation
Independent Selection
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
The Mean of a random variable
36. 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.
A Probability measure
Prior probability
Power of a test
The median value
37. A measurement such that the random error is small
Null hypothesis
Reliable measure
observational study
The Covariance between two random variables X and Y - with expected values E(X) =
38. A list of individuals from which the sample is actually selected.
P-value
nominal - ordinal - interval - and ratio
the population cumulants
Sampling frame
39. 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.
Marginal probability
Greek letters
Statistics
Placebo effect
40. When there is an even number of values...
That is the median value
the population cumulants
Block
Statistical dispersion
41. ?
Outlier
the population correlation
Qualitative variable
Step 2 of a statistical experiment
42. Is a parameter that indexes a family of probability distributions.
Residuals
A probability space
A Statistical parameter
Conditional distribution
43. Is inference about a population from a random sample drawn from it or - more generally - about a random process from its observed behavior during a finite period of time.
The Expected value
Statistical inference
An Elementary event
Inferential
44. Is the probability distribution - under repeated sampling of the population - of a given statistic.
the population variance
Outlier
Reliable measure
A sampling distribution
45. A collection of events is mutually independent if for any subset of the collection - the joint probability of all events occurring is equal to the product of the joint probabilities of the individual events. Think of the result of a series of coin-fl
Parameter
Binary data
Sampling
Mutual independence
46. To find the average - or arithmetic mean - of a set of numbers:
Simulation
A statistic
Divide the sum by the number of values.
Simpson's Paradox
47. 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
Parameter
Skewness
A probability space
Coefficient of determination
48. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
Particular realizations of a random variable
experimental studies and observational studies.
Joint distribution
Quantitative variable
49. Var[X] :
Type II errors
Placebo effect
Marginal probability
variance of X
50. Some commonly used symbols for population parameters
the population mean
Simpson's Paradox
Placebo effect
variance of X