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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. 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.
nominal - ordinal - interval - and ratio
The Mean of a random variable
A data point
That is the median value
2. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.
descriptive statistics
Observational study
Estimator
Statistical adjustment
3. Is that part of a population which is actually observed.
Statistical adjustment
A Probability measure
Simulation
A sample
4. A group of individuals sharing some common features that might affect the treatment.
Statistic
Block
Sampling Distribution
Variability
5. 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.
A population or statistical population
Statistical inference
Type I errors & Type II errors
Seasonal effect
6. 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.
Estimator
Correlation
The Mean of a random variable
Marginal probability
7. 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'
P-value
Skewness
Conditional probability
Mutual independence
8. Another name for elementary event.
An estimate of a parameter
Correlation
categorical variables
Atomic event
9. Is a parameter that indexes a family of probability distributions.
A Statistical parameter
The Mean of a random variable
Type 1 Error
Quantitative variable
10. Describes the spread in the values of the sample statistic when many samples are taken.
Independent Selection
Variability
Simpson's Paradox
Reliable measure
11. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).
That is the median value
Statistical inference
Atomic event
Probability density functions
12. Is the set of possible outcomes of an experiment. For example - the sample space for rolling a six-sided die will be {1 - 2 - 3 - 4 - 5 - 6}.
P-value
the population variance
The sample space
Variability
13. In particular - the pdf of the standard normal distribution is denoted by
Divide the sum by the number of values.
f(z) - and its cdf by F(z).
Observational study
Kurtosis
14. A numerical facsimilie or representation of a real-world phenomenon.
Type I errors
the population correlation
Simulation
Probability and statistics
15. 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
Probability and statistics
the population mean
Type I errors
Statistic
16. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).
inferential statistics
Marginal distribution
The standard deviation
A sampling distribution
17. Have no meaningful rank order among values.
Dependent Selection
Bias
An event
Nominal measurements
18. 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.
Conditional distribution
A statistic
A Random vector
Independence or Statistical independence
19. Have imprecise differences between consecutive values - but have a meaningful order to those values
the population variance
methods of least squares
The average - or arithmetic mean
Ordinal measurements
20. To find the average - or arithmetic mean - of a set of numbers:
Placebo effect
Average and arithmetic mean
Divide the sum by the number of values.
Bias
21. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
the population mean
Quantitative variable
Conditional distribution
Standard error
22. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.
23. Data are gathered and correlations between predictors and response are investigated.
Credence
Nominal measurements
observational study
Type II errors
24. A data value that falls outside the overall pattern of the graph.
Type II errors
An experimental study
Outlier
the sample or population mean
25. A common goal for a statistical research project is to investigate causality - and in particular to draw a conclusion on the effect of changes in the values of predictors or independent variables on dependent variables or response.
Descriptive
Experimental and observational studies
A statistic
Standard error
26. (or expectation) of a random variable is the sum of the probability of each possible outcome of the experiment multiplied by its payoff ('value'). Thus - it represents the average amount one 'expects' to win per bet if bets with identical odds are re
Power of a test
expected value of X
The Expected value
Type 1 Error
27. 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
A data set
Probability and statistics
Probability
The Expected value
28. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.
That value is the median value
Ordinal measurements
P-value
Parameter - or 'statistical parameter'
29. 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)
Confounded variables
f(z) - and its cdf by F(z).
Interval measurements
Credence
30. Some commonly used symbols for population parameters
Observational study
the population mean
hypotheses
Skewness
31. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data
Posterior probability
Block
hypothesis
An event
32. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as
Skewness
A Probability measure
A probability density function
categorical variables
33. Failing to reject a false null hypothesis.
Law of Parsimony
Type 2 Error
A random variable
P-value
34. A numerical measure that describes an aspect of a sample.
Statistic
A statistic
Type I errors
Binomial experiment
35. 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.
Probability density
the population correlation
Descriptive
That value is the median value
36. Any specific experimental condition applied to the subjects
Step 1 of a statistical experiment
Ordinal measurements
Treatment
Bias
37. (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
A likelihood function
Count data
Joint distribution
Simple random sample
38. A measurement such that the random error is small
Qualitative variable
Law of Large Numbers
the population variance
Reliable measure
39. 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 Covariance between two random variables X and Y - with expected values E(X) =
categorical variables
Block
experimental studies and observational studies.
40. Is the probability distribution - under repeated sampling of the population - of a given statistic.
s-algebras
A sampling distribution
Prior probability
Credence
41. 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
Joint probability
Ratio measurements
Treatment
Binomial experiment
42. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)
Simulation
Lurking variable
the population variance
Individual
43. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.
Statistics
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Conditional distribution
Placebo effect
44. Changes over time that show a regular periodicity in the data where regular means over a fixed interval; the time between repetitions is called the period.
Lurking variable
Likert scale
s-algebras
Seasonal effect
45. S^2
the population variance
Alpha value (Level of Significance)
Joint distribution
Trend
46. Is a sample space over which a probability measure has been defined.
Simpson's Paradox
Coefficient of determination
Simple random sample
A probability space
47. 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.
That is the median value
Sampling frame
Count data
Independent Selection
48. 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.
Sampling
Power of a test
Variable
Bias
49. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).
Greek letters
Inferential
The variance of a random variable
Step 1 of a statistical experiment
50. Cov[X - Y] :
A Random vector
expected value of X
Marginal probability
covariance of X and Y