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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. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.
Step 1 of a statistical experiment
Law of Large Numbers
the population variance
inferential statistics
2. Long-term upward or downward movement over time.
That is the median value
Trend
Ratio measurements
Credence
3. (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
An experimental study
Credence
Placebo effect
4. 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
Marginal distribution
An Elementary event
inferential statistics
Mutual independence
5. 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
Cumulative distribution functions
Pairwise independence
the population cumulants
Step 1 of a statistical experiment
6. Is a sample and the associated data points.
A data set
Inferential statistics
Posterior probability
Simpson's Paradox
7. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
A data point
Likert scale
the population mean
quantitative variables
8. 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 variance of a random variable
A Probability measure
Count data
9. Data are gathered and correlations between predictors and response are investigated.
quantitative variables
Probability density
observational study
the sample or population mean
10. Is data that can take only two values - usually represented by 0 and 1.
Type II errors
Probability density
Correlation
Binary data
11. In number theory - scatter plots of data generated by a distribution function may be transformed with familiar tools used in statistics to reveal underlying patterns - which may then lead to
The sample space
observational study
Law of Large Numbers
hypotheses
12. Var[X] :
Statistical adjustment
variance of X
Likert scale
Block
13. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).
Bias
Step 3 of a statistical experiment
Coefficient of determination
Probability density functions
14. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)
Individual
Parameter
Estimator
Probability
15. The standard deviation of a sampling distribution.
Trend
Standard error
quantitative variables
A Random vector
16. Is the length of the smallest interval which contains all the data.
An experimental study
Valid measure
The Range
The median value
17. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively
Type 2 Error
Residuals
Sampling Distribution
methods of least squares
18. A measure that is relevant or appropriate as a representation of that property.
s-algebras
Inferential
Valid measure
Quantitative variable
19. 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
Parameter
Sampling Distribution
20. Probability of accepting a false null hypothesis.
applied statistics
Type II errors
Beta value
Treatment
21. Gives the probability distribution for a continuous random variable.
Variable
Individual
Parameter - or 'statistical parameter'
A probability density function
22. A numerical measure that describes an aspect of a population.
Type II errors
Parameter
the population variance
Probability density
23. 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.
The Mean of a random variable
Reliable measure
Interval measurements
A data point
24. S^2
the population variance
An event
descriptive statistics
A statistic
25. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).
Random variables
Greek letters
Correlation coefficient
Statistics
26. 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.
Estimator
Prior probability
The median value
A population or statistical population
27. 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
the population correlation
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Statistical dispersion
28. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.
Confounded variables
Step 3 of a statistical experiment
Bias
the population variance
29. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)
Estimator
s-algebras
Nominal measurements
P-value
30. Given two random variables X and Y - the joint distribution of X and Y is the probability distribution of X and Y together.
Step 1 of a statistical experiment
Valid measure
Joint distribution
A Probability measure
31. Is a sample space over which a probability measure has been defined.
The average - or arithmetic mean
A probability space
Dependent Selection
descriptive statistics
32. Some commonly used symbols for population parameters
quantitative variables
the population mean
Step 1 of a statistical experiment
Quantitative variable
33. Is data arising from counting that can take only non-negative integer values.
Count data
Independence or Statistical independence
Statistical adjustment
applied statistics
34. Error also refers to the extent to which individual observations in a sample differ from a central value - such as
Parameter
Observational study
Variable
the sample or population mean
35. Describes the spread in the values of the sample statistic when many samples are taken.
variance of X
Interval measurements
Variability
hypotheses
36. Have meaningful distances between measurements defined - but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit)
Interval measurements
methods of least squares
Atomic event
the population correlation
37. To find the average - or arithmetic mean - of a set of numbers:
Step 3 of a statistical experiment
Divide the sum by the number of values.
f(z) - and its cdf by F(z).
s-algebras
38. Some commonly used symbols for sample statistics
Statistics
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
variance of X
s-algebras
39. Working from a null hypothesis two basic forms of error are recognized:
nominal - ordinal - interval - and ratio
the population cumulants
Type I errors & Type II errors
A probability density function
40. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.
observational study
Statistical adjustment
covariance of X and Y
Binary data
41. 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.
Kurtosis
Count data
Sampling Distribution
Estimator
42. 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'
Block
methods of least squares
Conditional probability
Standard error
43. 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
A likelihood function
Likert scale
Null hypothesis
Placebo effect
44. 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
Kurtosis
Sampling
Probability density
Pairwise independence
45. 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.
expected value of X
Count data
Type I errors
Statistics
46. Probability of rejecting a true null hypothesis.
methods of least squares
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Count data
Alpha value (Level of Significance)
47. Any specific experimental condition applied to the subjects
Treatment
Bias
The Covariance between two random variables X and Y - with expected values E(X) =
Binomial experiment
48. When you have two or more competing models - choose the simpler of the two models.
Law of Parsimony
Atomic event
Sample space
the population cumulants
49. 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
Step 3 of a statistical experiment
An experimental study
Statistical dispersion
50. A measurement such that the random error is small
Reliable measure
Type II errors
A Probability measure
Sampling Distribution