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Test your basic knowledge |
CLEP General Mathematics: Probability And Statistics
Start Test
Study First
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 a sample and the associated data points.
Placebo effect
nominal - ordinal - interval - and ratio
Bias
A data set
2. 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.
the sample or population mean
The Range
the population correlation
Marginal distribution
3. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.
A Distribution function
Independent Selection
Joint probability
A statistic
4. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.
5. 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 Expected value
Dependent Selection
The variance of a random variable
That value is the median value
6. 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
f(z) - and its cdf by F(z).
Sampling
the population variance
Observational study
7. 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
Trend
Confounded variables
Null hypothesis
Sampling frame
8. Any specific experimental condition applied to the subjects
hypotheses
Treatment
Nominal measurements
Skewness
9. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as
quantitative variables
Null hypothesis
The median value
A Distribution function
10. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as
experimental studies and observational studies.
Statistical dispersion
Outlier
categorical variables
11. Statistics involve methods of using information from a sample to draw conclusions regarding the population.
A data point
An estimate of a parameter
Type I errors
Inferential
12. E[X] :
covariance of X and Y
expected value of X
methods of least squares
Qualitative variable
13. Statistical methods can be used for summarizing or describing a collection of data; this is called
methods of least squares
Atomic event
Skewness
descriptive statistics
14. 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).
Count data
A Random vector
variance of X
Joint probability
15. Descriptive statistics and inferential statistics (a.k.a. - predictive statistics) together comprise
Probability
applied statistics
Variability
A likelihood function
16. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)
The Expected value
s-algebras
A data set
A probability distribution
17. Describes the spread in the values of the sample statistic when many samples are taken.
Parameter - or 'statistical parameter'
Variability
Coefficient of determination
Type 1 Error
18. 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
Statistics
Mutual independence
hypotheses
19. 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).
Experimental and observational studies
Placebo effect
Individual
An event
20. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Lurking variable
Standard error
Pairwise independence
the population mean
21. 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.
inferential statistics
The Expected value
Estimator
Lurking variable
22. Are simply two different terms for the same thing. Add the given values
Parameter
Average and arithmetic mean
Posterior probability
Law of Large Numbers
23. ?r
the population cumulants
Placebo effect
Probability density functions
Qualitative variable
24. 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
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Alpha value (Level of Significance)
The variance of a random variable
experimental studies and observational studies.
25. The proportion of the explained variation by a linear regression model in the total variation.
Alpha value (Level of Significance)
variance of X
Power of a test
Coefficient of determination
26. To prove the guiding theory further - these predictions are tested as well - as part of the scientific method. If the inference holds true - then the descriptive statistics of the new data increase the soundness of that
Quantitative variable
Statistical inference
Pairwise independence
hypothesis
27. Data are gathered and correlations between predictors and response are investigated.
observational study
Sampling frame
Probability
Step 1 of a statistical experiment
28. 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
Descriptive
Probability
Binomial experiment
Simpson's Paradox
29. 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 mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
A Distribution function
Treatment
hypotheses
30. 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.
A sampling distribution
Dependent Selection
Bias
Parameter - or 'statistical parameter'
31. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.
Null hypothesis
An estimate of a parameter
descriptive statistics
the population mean
32. A subjective estimate of probability.
Prior probability
An event
Law of Parsimony
Credence
33. Is data that can take only two values - usually represented by 0 and 1.
Binary data
The Range
Outlier
Coefficient of determination
34. When there is an even number of values...
Beta value
Correlation coefficient
Law of Parsimony
That is the median value
35. A measurement such that the random error is small
Probability and statistics
Reliable measure
quantitative variables
The Range
36. A numerical measure that describes an aspect of a sample.
Statistic
Block
An estimate of a parameter
Count data
37. Two variables such that their effects on the response variable cannot be distinguished from each other.
A population or statistical population
the population mean
Confounded variables
Joint distribution
38. A numerical measure that describes an aspect of a population.
Parameter
the population correlation
nominal - ordinal - interval - and ratio
Inferential
39. 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.
The variance of a random variable
Independent Selection
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
The Mean of a random variable
40. Gives the probability distribution for a continuous random variable.
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
A probability density function
the population variance
Joint probability
41. Is a parameter that indexes a family of probability distributions.
Power of a test
A Statistical parameter
A probability density function
Probability and statistics
42. Is the probability distribution - under repeated sampling of the population - of a given statistic.
Trend
methods of least squares
expected value of X
A sampling distribution
43. 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 Expected value
Probability density
Descriptive statistics
Pairwise independence
44. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
Probability density
Step 2 of a statistical experiment
Likert scale
Estimator
45. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively
Particular realizations of a random variable
the population mean
Law of Large Numbers
Residuals
46. The collection of all possible outcomes in an experiment.
Marginal distribution
Ordinal measurements
Independent Selection
Sample space
47. Is data arising from counting that can take only non-negative integer values.
An Elementary event
A Random vector
Atomic event
Count data
48. Is a function that gives the probability of all elements in a given space: see List of probability distributions
The Expected value
Variable
Power of a test
A probability distribution
49. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.
Seasonal effect
Parameter - or 'statistical parameter'
categorical variables
Particular realizations of a random variable
50. Is a process of selecting observations to obtain knowledge about a population. There are many methods to choose on which sample to do the observations.
Reliable measure
Sampling
A random variable
Independence or Statistical independence