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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. Is the length of the smallest interval which contains all the data.
The Range
Parameter
Joint probability
Type I errors & Type II errors
2. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
Quantitative variable
Individual
s-algebras
Null hypothesis
3. Have no meaningful rank order among values.
Nominal measurements
Interval measurements
An experimental study
Binomial experiment
4. A numerical measure that describes an aspect of a population.
The Covariance between two random variables X and Y - with expected values E(X) =
Parameter
Law of Parsimony
Divide the sum by the number of values.
5. Is a function that gives the probability of all elements in a given space: see List of probability distributions
A probability distribution
hypotheses
Cumulative distribution functions
the population mean
6. Var[X] :
A Random vector
Divide the sum by the number of values.
variance of X
Statistical adjustment
7. The standard deviation of a sampling distribution.
Standard error
A sampling distribution
methods of least squares
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
8. A variable describes an individual by placing the individual into a category or a group.
Law of Parsimony
Qualitative variable
Observational study
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
9. A subjective estimate of probability.
Credence
A data point
A likelihood function
A probability distribution
10. Rejecting a true null hypothesis.
s-algebras
Type 1 Error
A Random vector
Atomic event
11. Descriptive statistics and inferential statistics (a.k.a. - predictive statistics) together comprise
applied statistics
A population or statistical population
covariance of X and Y
Type 1 Error
12. Have imprecise differences between consecutive values - but have a meaningful order to those values
Divide the sum by the number of values.
Ordinal measurements
inferential statistics
An Elementary event
13. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Average and arithmetic mean
Probability
Greek letters
Pairwise independence
14. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.
the population mean
Statistical adjustment
The standard deviation
methods of least squares
15. Some commonly used symbols for sample statistics
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Kurtosis
Cumulative distribution functions
A data set
16. Is that part of a population which is actually observed.
A sample
Statistical dispersion
Statistics
Binomial experiment
17. 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 random variable
Trend
Simpson's Paradox
The median value
18. (cdfs) are denoted by upper case letters - e.g. F(x).
Cumulative distribution functions
Sampling Distribution
Estimator
Type 2 Error
19. Are simply two different terms for the same thing. Add the given values
Observational study
s-algebras
A data set
Average and arithmetic mean
20. ?r
The variance of a random variable
Average and arithmetic mean
the population cumulants
A statistic
21. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.
A statistic
Law of Large Numbers
the sample or population mean
Correlation coefficient
22. Describes a characteristic of an individual to be measured or observed.
inferential statistics
Cumulative distribution functions
Variable
Descriptive statistics
23. Data are gathered and correlations between predictors and response are investigated.
the population correlation
Binary data
observational study
The median value
24.
the population mean
s-algebras
That is the median value
Pairwise independence
25. 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).
Valid measure
Joint probability
Sample space
Statistical dispersion
26. Is a parameter that indexes a family of probability distributions.
Variable
Dependent Selection
A Statistical parameter
Parameter
27. 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 Distribution function
quantitative variables
Null hypothesis
The variance of a random variable
28. 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.
Seasonal effect
A population or statistical population
Variable
Sampling
29. 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
A sampling distribution
Confounded variables
Mutual independence
expected value of X
30. Error also refers to the extent to which individual observations in a sample differ from a central value - such as
the sample or population mean
methods of least squares
Experimental and observational studies
A likelihood function
31. 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
descriptive statistics
A probability density function
Skewness
A data point
32. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
Skewness
categorical variables
Probability density functions
Likert scale
33. Long-term upward or downward movement over time.
Ratio measurements
Trend
Correlation
Step 1 of a statistical experiment
34. 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.
Type 2 Error
Sampling Distribution
Credence
A data point
35. ?
A random variable
Dependent Selection
the population correlation
Sampling frame
36. To find the average - or arithmetic mean - of a set of numbers:
Divide the sum by the number of values.
A Distribution function
Correlation
s-algebras
37. A numerical facsimilie or representation of a real-world phenomenon.
Sampling frame
Simulation
Conditional probability
That is the median value
38. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.
Ratio measurements
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Simpson's Paradox
Sampling Distribution
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.
An estimate of a parameter
Step 1 of a statistical experiment
Independent Selection
Marginal distribution
40. (or atomic event) is an event with only one element. For example - when pulling a card out of a deck - 'getting the jack of spades' is an elementary event - while 'getting a king or an ace' is not.
An Elementary event
Pairwise independence
Variable
Average and arithmetic mean
41. There are four main levels of measurement used in statistics: Each of these have different degrees of usefulness in statistical research.
Joint probability
Marginal distribution
nominal - ordinal - interval - and ratio
Experimental and observational studies
42. 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
methods of least squares
Interval measurements
hypothesis
Random variables
43. A numerical measure that describes an aspect of a sample.
Divide the sum by the number of values.
Joint distribution
Statistic
Likert scale
44. A measure that is relevant or appropriate as a representation of that property.
Seasonal effect
Ordinal measurements
Valid measure
Power of a test
45. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.
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46. A data value that falls outside the overall pattern of the graph.
Type II errors
Dependent Selection
the population variance
Outlier
47. Where the null hypothesis is falsely rejected giving a 'false positive'.
That value is the median value
Type I errors
Count data
Atomic event
48. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as
quantitative variables
Placebo effect
A Statistical parameter
The variance of a random variable
49. 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
observational study
Descriptive statistics
A probability density function
Placebo effect
50. 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.
Simple random sample
Conditional distribution
Sampling
A population or statistical population