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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. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)
Divide the sum by the number of values.
Individual
That value is the median value
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
2. 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.
Count data
Greek letters
An experimental study
Cumulative distribution functions
3. Describes a characteristic of an individual to be measured or observed.
A probability density function
Observational study
Sample space
Variable
4. 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.
Bias
The median value
Step 1 of a statistical experiment
That value is the median value
5. 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
Standard error
Random variables
Mutual independence
the population variance
6. Is one that explores the correlation between smoking and lung cancer. This type of study typically uses a survey to collect observations about the area of interest and then performs statistical analysis. In this case - the researchers would collect o
variance of X
Seasonal effect
Observational study
Ratio measurements
7. The collection of all possible outcomes in an experiment.
Nominal measurements
A data set
Sample space
Skewness
8. 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.
Atomic event
Independent Selection
An experimental study
Statistics
9. A data value that falls outside the overall pattern of the graph.
Null hypothesis
Outlier
A probability distribution
Kurtosis
10. 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
Divide the sum by the number of values.
Prior probability
Descriptive statistics
11. When there is an even number of values...
the sample or population mean
That is the median value
Law of Large Numbers
Statistical adjustment
12. A measurement such that the random error is small
Valid measure
Reliable measure
covariance of X and Y
Step 3 of a statistical experiment
13. Patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations - and are then used for drawing inferences about the process or population being studied; this is called
Statistical dispersion
Bias
The variance of a random variable
inferential statistics
14. Is the length of the smallest interval which contains all the data.
Step 3 of a statistical experiment
The Range
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Simpson's Paradox
15. (cdfs) are denoted by upper case letters - e.g. F(x).
Dependent Selection
Probability density
Block
Cumulative distribution functions
16. Some commonly used symbols for population parameters
methods of least squares
the population mean
The Mean of a random variable
Observational study
17. 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
Sample space
Correlation
Simulation
Statistics
18. A list of individuals from which the sample is actually selected.
Type 1 Error
The variance of a random variable
Sampling frame
A probability space
19. 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
Null hypothesis
The Covariance between two random variables X and Y - with expected values E(X) =
Statistical inference
Correlation coefficient
20. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).
That value is the median value
Probability density
Probability density functions
Conditional probability
21. The standard deviation of a sampling distribution.
Standard error
Statistic
Observational study
Probability and statistics
22. 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.
the population mean
Marginal distribution
Independent Selection
P-value
23. Is the function that gives the probability distribution of a random variable. It cannot be negative - and its integral on the probability space is equal to 1.
Standard error
inferential statistics
A Distribution function
A probability density function
24. Is data that can take only two values - usually represented by 0 and 1.
The Mean of a random variable
Standard error
P-value
Binary data
25. Are usually written in upper case roman letters: X - Y - etc.
Cumulative distribution functions
A probability distribution
Random variables
P-value
26. 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
Block
Type 1 Error
Marginal distribution
Step 1 of a statistical experiment
27. (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.
Parameter
Bias
An Elementary event
Probability density functions
28. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data
categorical variables
Posterior probability
Reliable measure
observational study
29. Data are gathered and correlations between predictors and response are investigated.
A probability space
An estimate of a parameter
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
observational study
30. ?
Law of Large Numbers
the population correlation
Bias
That value is the median value
31. In particular - the pdf of the standard normal distribution is denoted by
That value is the median value
f(z) - and its cdf by F(z).
s-algebras
Power of a test
32. A variable describes an individual by placing the individual into a category or a group.
Qualitative variable
Probability density
Independent Selection
f(z) - and its cdf by F(z).
33. Var[X] :
variance of X
Estimator
Cumulative distribution functions
Sample space
34. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.
the population variance
A probability density function
The Range
Particular realizations of a random variable
35. (or multivariate random variable) is a vector whose components are random variables on the same probability space.
A statistic
An experimental study
A Random vector
Ordinal measurements
36. 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
Power of a test
hypothesis
Seasonal effect
The variance of a random variable
37. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.
A population or statistical population
Outlier
Marginal probability
Law of Large Numbers
38. Is its expected value. The mean (or sample mean of a data set is just the average value.
Probability and statistics
The Mean of a random variable
methods of least squares
Power of a test
39. 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).
Independence or Statistical independence
An event
Simulation
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
40. Can refer either to a sample not being representative of the population - or to the difference between the expected value of an estimator and the true value.
A data point
Bias
covariance of X and Y
Simple random sample
41. 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.
Statistical adjustment
Power of a test
hypothesis
Conditional distribution
42. When you have two or more competing models - choose the simpler of the two models.
Conditional probability
the population mean
That value is the median value
Law of Parsimony
43. A measure that is relevant or appropriate as a representation of that property.
Power of a test
The Covariance between two random variables X and Y - with expected values E(X) =
Valid measure
the population variance
44. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.
Block
Credence
P-value
Step 2 of a statistical experiment
45. ?r
the population cumulants
the sample or population mean
That is the median value
Prior probability
46. Is a parameter that indexes a family of probability distributions.
Statistic
A Statistical parameter
s-algebras
That value is the median value
47. 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.
Count data
Statistical inference
A likelihood function
categorical variables
48. Probability of rejecting a true null hypothesis.
Standard error
Type II errors
Alpha value (Level of Significance)
Binary data
49. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.
Experimental and observational studies
the population variance
A statistic
the population mean
50. Statistics involve methods of using information from a sample to draw conclusions regarding the population.
Qualitative variable
methods of least squares
hypothesis
Inferential