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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.
Binomial experiment
Statistical adjustment
Beta value
Statistics
2. Is a parameter that indexes a family of probability distributions.
Random variables
Joint probability
Mutual independence
A Statistical parameter
3. Is the probability of an event - ignoring any information about other events. The marginal probability of A is written P(A). Contrast with conditional probability.
Binomial experiment
hypotheses
Marginal probability
Descriptive statistics
4. Is a sample space over which a probability measure has been defined.
A probability space
The Expected value
Variability
The Mean of a random variable
5. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
Quantitative variable
Bias
the population cumulants
A probability density function
6. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as
Outlier
quantitative variables
the population cumulants
Statistical adjustment
7. Failing to reject a false null hypothesis.
Bias
Power of a test
Statistic
Type 2 Error
8. A group of individuals sharing some common features that might affect the treatment.
Inferential statistics
Block
experimental studies and observational studies.
Likert scale
9. 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
Dependent Selection
Power of a test
hypothesis
A Distribution function
10. (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
The Expected value
The standard deviation
Variable
Coefficient of determination
11. 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.
Interval measurements
A probability density function
A data point
Variable
12. ?r
Sample space
That is the median value
the population cumulants
Type I errors
13. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.
An estimate of a parameter
Null hypothesis
A Statistical parameter
Step 1 of a statistical experiment
14. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.
Law of Large Numbers
nominal - ordinal - interval - and ratio
Seasonal effect
Ratio measurements
15. Is defined as the expected value of random variable (X -
The Covariance between two random variables X and Y - with expected values E(X) =
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
An estimate of a parameter
Ordinal measurements
16. 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
Descriptive
Treatment
Observational study
17. Probability of rejecting a true null hypothesis.
Joint probability
Alpha value (Level of Significance)
Statistics
Power of a test
18. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)
An Elementary event
Reliable measure
s-algebras
expected value of X
19. Is its expected value. The mean (or sample mean of a data set is just the average value.
A sampling distribution
A probability distribution
The Mean of a random variable
Joint probability
20. A data value that falls outside the overall pattern of the graph.
The standard deviation
Statistical inference
Outlier
s-algebras
21. 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).
Dependent Selection
Power of a test
Joint probability
A probability distribution
22. 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.
Statistical inference
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Joint distribution
Quantitative variable
23. Also called correlation coefficient - is a numeric measure of the strength of linear relationship between two random variables (one can use it to quantify - for example - how shoe size and height are correlated in the population). An example is the P
The Mean of a random variable
Interval measurements
Parameter
Correlation
24. Gives the probability distribution for a continuous random variable.
Inferential statistics
The Range
s-algebras
A probability density function
25. Some commonly used symbols for population parameters
the population mean
Probability and statistics
nominal - ordinal - interval - and ratio
A sampling distribution
26. Is a function that gives the probability of all elements in a given space: see List of probability distributions
variance of X
A Random vector
Confounded variables
A probability distribution
27. (or multivariate random variable) is a vector whose components are random variables on the same probability space.
A probability space
A Random vector
Sampling Distribution
the sample or population mean
28. 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
A Random vector
Credence
Step 1 of a statistical experiment
The Covariance between two random variables X and Y - with expected values E(X) =
29. 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.
A probability density function
Step 3 of a statistical experiment
Conditional probability
That value is the median value
30. Error also refers to the extent to which individual observations in a sample differ from a central value - such as
Probability
hypotheses
the sample or population mean
quantitative variables
31. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.
Joint probability
Probability
Particular realizations of a random variable
Likert scale
32. Rejecting a true null hypothesis.
Residuals
quantitative variables
Type 1 Error
Simulation
33. 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
Descriptive statistics
Independent Selection
Independence or Statistical independence
34. Summarize the population data by describing what was observed in the sample numerically or graphically. Numerical descriptors include mean and standard deviation for continuous data types (like heights or weights) - while frequency and percentage are
Sampling
Descriptive
Step 1 of a statistical experiment
Descriptive statistics
35. 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
Average and arithmetic mean
s-algebras
Experimental and observational studies
Probability density
36. A numerical measure that assesses the strength of a linear relationship between two variables.
Correlation coefficient
Qualitative variable
hypothesis
Interval measurements
37. 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 population cumulants
An Elementary event
experimental studies and observational studies.
Conditional probability
38. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as
Treatment
categorical variables
Variability
expected value of X
39. 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.
That is the median value
Sampling Distribution
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Marginal distribution
40. To find the average - or arithmetic mean - of a set of numbers:
the population mean
Ordinal measurements
Variability
Divide the sum by the number of values.
41. 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.
Type I errors & Type II errors
Law of Parsimony
Atomic event
Seasonal effect
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
Residuals
Null hypothesis
quantitative variables
Particular realizations of a random variable
43. Many statistical methods seek to minimize the mean-squared error - and these are called
the population variance
methods of least squares
Joint probability
Confounded variables
44. Is a sample and the associated data points.
Statistical dispersion
Greek letters
A data set
Null hypothesis
45. When there is an even number of values...
That is the median value
Estimator
the population variance
Parameter
46. A measure that is relevant or appropriate as a representation of that property.
Valid measure
Marginal distribution
Block
Average and arithmetic mean
47. A numerical measure that describes an aspect of a sample.
Type I errors & Type II errors
Statistical inference
Statistic
Treatment
48. Is data arising from counting that can take only non-negative integer values.
Skewness
A Distribution function
Qualitative variable
Count data
49. 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).
An event
Nominal measurements
Random variables
Qualitative variable
50. The collection of all possible outcomes in an experiment.
Estimator
Probability density
Observational study
Sample space