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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. 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.
Reliable measure
Statistical adjustment
Correlation coefficient
Lurking variable
2. 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.
Bias
Statistics
Type 2 Error
the population variance
3. A measurement such that the random error is small
Simulation
applied statistics
Placebo effect
Reliable measure
4. ?
Average and arithmetic mean
Null hypothesis
the population correlation
the sample or population mean
5. Is defined as the expected value of random variable (X -
A random variable
Statistical inference
Independence or Statistical independence
The Covariance between two random variables X and Y - with expected values E(X) =
6. A numerical measure that describes an aspect of a population.
Law of Large Numbers
Parameter
Experimental and observational studies
Placebo effect
7. When you have two or more competing models - choose the simpler of the two models.
Law of Parsimony
the population cumulants
Treatment
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
8. Is the probability distribution - under repeated sampling of the population - of a given statistic.
A population or statistical population
A sampling distribution
Parameter - or 'statistical parameter'
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
9. Working from a null hypothesis two basic forms of error are recognized:
Marginal distribution
Variable
A Probability measure
Type I errors & Type II errors
10. Statistics involve methods of using information from a sample to draw conclusions regarding the population.
variance of X
Nominal measurements
Inferential
Count data
11. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.
12. Describes a characteristic of an individual to be measured or observed.
Type 1 Error
Skewness
Variable
Joint probability
13. Another name for elementary event.
Atomic event
nominal - ordinal - interval - and ratio
descriptive statistics
Step 1 of a statistical experiment
14. To find the average - or arithmetic mean - of a set of numbers:
Divide the sum by the number of values.
A population or statistical population
Null hypothesis
Binary data
15. Is a function that gives the probability of all elements in a given space: see List of probability distributions
A sampling distribution
Probability
A probability distribution
That value is the median value
16. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.
Statistical inference
The Range
P-value
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
17. Involves taking measurements of the system under study - manipulating the system - and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements.
An experimental study
Joint probability
Simple random sample
Conditional probability
18. 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.
inferential statistics
The median value
Inferential statistics
Atomic event
19. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.
P-value
applied statistics
Binary data
Law of Large Numbers
20. (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.
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Mutual independence
An Elementary event
the population variance
21. Have imprecise differences between consecutive values - but have a meaningful order to those values
Ordinal measurements
Seasonal effect
Type 2 Error
Random variables
22. Is that part of a population which is actually observed.
Independence or Statistical independence
A sample
Lurking variable
Statistical inference
23. Is data arising from counting that can take only non-negative integer values.
Count data
The Mean of a random variable
covariance of X and Y
Posterior probability
24. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data
Binary data
Dependent Selection
Simple random sample
Posterior probability
25. 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}.
The standard deviation
experimental studies and observational studies.
Seasonal effect
The sample space
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.
Interval measurements
f(z) - and its cdf by F(z).
A population or statistical population
Bias
27. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.
Trend
An estimate of a parameter
A random variable
Type II errors
28. A numerical measure that describes an aspect of a sample.
Statistic
An event
Average and arithmetic mean
Sample space
29. 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
experimental studies and observational studies.
Greek letters
Atomic event
30. Long-term upward or downward movement over time.
Confounded variables
Posterior probability
Trend
Individual
31. Can be a population parameter - a distribution parameter - an unobserved parameter (with different shades of meaning). In statistics - this is often a quantity to be estimated.
32. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).
Variability
Greek letters
Independent Selection
Parameter - or 'statistical parameter'
33. Statistical methods can be used for summarizing or describing a collection of data; this is called
Type I errors
descriptive statistics
Sampling
Sample space
34. Is the length of the smallest interval which contains all the data.
Type II errors
Step 1 of a statistical experiment
the population correlation
The Range
35. A sample selected in such a way that each individual is equally likely to be selected as well as any group of size n is equally likely to be selected.
Simple random sample
Correlation coefficient
The Range
The sample space
36. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)
s-algebras
Individual
Dependent Selection
An estimate of a parameter
37. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.
A Probability measure
That is the median value
Type II errors
Statistical adjustment
38. 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
Null hypothesis
hypotheses
Qualitative variable
f(z) - and its cdf by F(z).
39. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
Probability
Divide the sum by the number of values.
Random variables
Quantitative variable
40. Gives the probability of events in a probability space.
A Probability measure
An event
A probability space
Lurking variable
41. 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.
A random variable
The variance of a random variable
Greek letters
Law of Parsimony
42. 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
Estimator
Null hypothesis
Correlation
Statistical dispersion
43. Given two random variables X and Y - the joint distribution of X and Y is the probability distribution of X and Y together.
A Distribution function
Joint distribution
Standard error
Statistical adjustment
44. Is a parameter that indexes a family of probability distributions.
Correlation
A Statistical parameter
variance of X
Nominal measurements
45.
A data set
Conditional probability
the population mean
Nominal measurements
46. 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
A likelihood function
Probability density
quantitative variables
the sample or population mean
47. Some commonly used symbols for sample statistics
Placebo effect
Type I errors
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
The average - or arithmetic mean
48. 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.
An Elementary event
Marginal probability
The variance of a random variable
That value is the median value
49. Many statistical methods seek to minimize the mean-squared error - and these are called
Average and arithmetic mean
Trend
Power of a test
methods of least squares
50. 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.
Independent Selection
f(z) - and its cdf by F(z).
Variable
Kurtosis