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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. Uses patterns in the sample data to draw inferences about the population represented - accounting for randomness. These inferences may take the form of: answering yes/no questions about the data (hypothesis testing) - estimating numerical characteris
Inferential statistics
Inferential
the sample or population mean
A population or statistical population
2. Is a parameter that indexes a family of probability distributions.
Step 2 of a statistical experiment
The median value
The Range
A Statistical parameter
3. Long-term upward or downward movement over time.
hypotheses
Binomial experiment
Descriptive
Trend
4. Is denoted by - pronounced 'x bar'.
Greek letters
An event
A sample
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
5. The standard deviation of a sampling distribution.
Standard error
hypothesis
Ordinal measurements
Pairwise independence
6. 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
Seasonal effect
Statistic
Parameter
hypotheses
7. Is the length of the smallest interval which contains all the data.
nominal - ordinal - interval - and ratio
An experimental study
The Range
Statistical dispersion
8. Is data that can take only two values - usually represented by 0 and 1.
Ratio measurements
Valid measure
The standard deviation
Binary data
9. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.
Interval measurements
Correlation coefficient
Sampling Distribution
Type I errors
10. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
Inferential statistics
Observational study
Quantitative variable
Marginal probability
11. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.
A likelihood function
Placebo effect
Sampling
Inferential
12. 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.
Sampling Distribution
Parameter
Statistical inference
Probability density functions
13. 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
An experimental study
Variability
That is the median value
14. 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
Statistical adjustment
hypothesis
Particular realizations of a random variable
15. A variable describes an individual by placing the individual into a category or a group.
Step 2 of a statistical experiment
Coefficient of determination
Qualitative variable
A Statistical parameter
16. Probability of rejecting a true null hypothesis.
variance of X
Alpha value (Level of Significance)
Coefficient of determination
Sampling frame
17. Is a sample and the associated data points.
A data set
Independent Selection
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Treatment
18. Is defined as the expected value of random variable (X -
Correlation coefficient
Probability density functions
The Covariance between two random variables X and Y - with expected values E(X) =
Outlier
19. 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
Probability and statistics
Count data
Marginal probability
20. 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
descriptive statistics
A statistic
Sample space
21. Design of experiments - using blocking to reduce the influence of confounding variables - and randomized assignment of treatments to subjects to allow unbiased estimates of treatment effects and experimental error. At this stage - the experimenters a
Marginal probability
observational study
A likelihood function
Step 2 of a statistical experiment
22. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.
Bias
Residuals
Type II errors
Type 1 Error
23. There are four main levels of measurement used in statistics: Each of these have different degrees of usefulness in statistical research.
methods of least squares
nominal - ordinal - interval - and ratio
Null hypothesis
Independent Selection
24. Are simply two different terms for the same thing. Add the given values
Average and arithmetic mean
Statistics
Binomial experiment
The Mean of a random variable
25. 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
Skewness
Cumulative distribution functions
Atomic event
Null hypothesis
26. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.
Statistical adjustment
The Mean of a random variable
Correlation coefficient
Simple random sample
27. 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
The Mean of a random variable
expected value of X
Nominal measurements
28. Is the probability distribution - under repeated sampling of the population - of a given statistic.
f(z) - and its cdf by F(z).
the population variance
A sampling distribution
An Elementary event
29. A numerical measure that describes an aspect of a population.
Cumulative distribution functions
Parameter
Skewness
A likelihood function
30. Working from a null hypothesis two basic forms of error are recognized:
Outlier
A data set
Type I errors & Type II errors
Correlation
31. 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'
Independent Selection
Conditional probability
Power of a test
The sample space
32. Another name for elementary event.
Atomic event
Joint probability
Probability and statistics
Random variables
33. Statistics involve methods of using information from a sample to draw conclusions regarding the population.
Inferential
Kurtosis
Statistic
Random variables
34. 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
Statistical adjustment
the population variance
Simulation
Mutual independence
35. Describes a characteristic of an individual to be measured or observed.
covariance of X and Y
Binary data
Individual
Variable
36. When there is an even number of values...
The Covariance between two random variables X and Y - with expected values E(X) =
That is the median value
Statistics
Bias
37. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.
38. A list of individuals from which the sample is actually selected.
Sampling frame
Parameter - or 'statistical parameter'
Block
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
39. Can be - for example - the possible outcomes of a dice roll (but it is not assigned a value). The distribution function of a random variable gives the probability of different results. We can also derive the mean and variance of a random variable.
Ratio measurements
That value is the median value
A random variable
inferential statistics
40. Some commonly used symbols for sample statistics
Outlier
That value is the median value
An Elementary event
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
41. 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
variance of X
Outlier
Probability and statistics
Joint probability
42. 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.
That value is the median value
the population correlation
Probability
Type 1 Error
43. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.
Greek letters
Joint distribution
A statistic
The Mean of a random variable
44. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
An Elementary event
Residuals
Likert scale
experimental studies and observational studies.
45. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Independence or Statistical independence
Type 1 Error
Pairwise independence
Simpson's Paradox
46. Probability of accepting a false null hypothesis.
Beta value
Type I errors & Type II errors
Experimental and observational studies
the population correlation
47. 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 Mean of a random variable
Treatment
Probability density
the population mean
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
Statistical inference
A sample
Independent Selection
49. Is that part of a population which is actually observed.
A sample
Step 3 of a statistical experiment
Law of Large Numbers
Law of Parsimony
50. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as
Variability
Count data
categorical variables
Ratio measurements