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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. In particular - the pdf of the standard normal distribution is denoted by
The Mean of a random variable
f(z) - and its cdf by F(z).
descriptive statistics
covariance of X and Y
2. 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
Count data
Conditional distribution
f(z) - and its cdf by F(z).
experimental studies and observational studies.
3. A variable describes an individual by placing the individual into a category or a group.
Credence
observational study
Qualitative variable
Descriptive
4. The probability of correctly detecting a false null hypothesis.
Bias
A population or statistical population
Dependent Selection
Power of a test
5. 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
Residuals
Law of Parsimony
hypotheses
Step 1 of a statistical experiment
6. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.
Binary data
Prior probability
That is the median value
A statistic
7. (or just likelihood) is a conditional probability function considered a function of its second argument with its first argument held fixed. For example - imagine pulling a numbered ball with the number k from a bag of n balls - numbered 1 to n. Then
the population mean
That value is the median value
Sampling
A likelihood function
8. 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.
Bias
Qualitative variable
Conditional probability
The Mean of a random variable
9. Is a parameter that indexes a family of probability distributions.
Probability density
Bias
The standard deviation
A Statistical parameter
10. 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.
The Mean of a random variable
Marginal probability
Coefficient of determination
That value is the median value
11. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)
categorical variables
A data set
Individual
Seasonal effect
12. ?
Cumulative distribution functions
the population correlation
Step 1 of a statistical experiment
A sampling distribution
13. A group of individuals sharing some common features that might affect the treatment.
Alpha value (Level of Significance)
Conditional probability
Block
Inferential statistics
14. E[X] :
Power of a test
Seasonal effect
Simpson's Paradox
expected value of X
15. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
The Mean of a random variable
Likert scale
Credence
Law of Large Numbers
16. 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
experimental studies and observational studies.
An experimental study
Placebo effect
hypothesis
17. A measurement such that the random error is small
Ratio measurements
Pairwise independence
Reliable measure
observational study
18. 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.
Credence
The Mean of a random variable
A population or statistical population
Probability density functions
19. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.
A Statistical parameter
Type I errors
Bias
covariance of X and Y
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.
Dependent Selection
A Probability measure
the population mean
An Elementary event
21. Many statistical methods seek to minimize the mean-squared error - and these are called
Skewness
the population mean
methods of least squares
Kurtosis
22. 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
Random variables
the population cumulants
Inferential
23. 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
Block
Probability and statistics
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Sampling frame
24. Have meaningful distances between measurements defined - but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit)
Descriptive statistics
Interval measurements
Parameter - or 'statistical parameter'
Trend
25. Data are gathered and correlations between predictors and response are investigated.
A sampling distribution
Step 3 of a statistical experiment
A likelihood function
observational study
26. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.
Statistical adjustment
Variability
Confounded variables
observational study
27. Of a group of numbers is the center point of all those number values.
The average - or arithmetic mean
Residuals
Marginal probability
That value is the median value
28. 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.
Quantitative variable
A random variable
Qualitative variable
Likert scale
29. Cov[X - Y] :
covariance of X and Y
Law of Parsimony
An Elementary event
Marginal probability
30. Is that part of a population which is actually observed.
the population mean
The standard deviation
A sample
Sampling Distribution
31. Given two random variables X and Y - the joint distribution of X and Y is the probability distribution of X and Y together.
Treatment
applied statistics
Joint distribution
A Probability measure
32. S^2
A population or statistical population
the population variance
hypotheses
the population cumulants
33. Is data arising from counting that can take only non-negative integer values.
Simple random sample
quantitative variables
Count data
An event
34. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.
Statistical dispersion
Descriptive
Interval measurements
Kurtosis
35. (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 variance of a random variable
Type I errors & Type II errors
The Expected value
the population mean
36. Gives the probability of events in a probability space.
Step 1 of a statistical experiment
Statistic
A Probability measure
methods of least squares
37. The standard deviation of a sampling distribution.
Standard error
Type 1 Error
Variable
A population or statistical population
38. 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}.
Sampling frame
Marginal distribution
A Random vector
The sample space
39. Any specific experimental condition applied to the subjects
Treatment
Count data
A data point
A Statistical parameter
40. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
Descriptive statistics
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Quantitative variable
A population or statistical population
41. Two variables such that their effects on the response variable cannot be distinguished from each other.
Confounded variables
Cumulative distribution functions
Kurtosis
Marginal distribution
42. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.
A statistic
Independent Selection
The variance of a random variable
The standard deviation
43. 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'
Statistics
Conditional probability
the population cumulants
Sampling frame
44. 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).
Skewness
Joint probability
Marginal probability
A probability density function
45. Is its expected value. The mean (or sample mean of a data set is just the average value.
Simpson's Paradox
quantitative variables
Probability and statistics
The Mean of a random variable
46. Rejecting a true null hypothesis.
Interval measurements
Type 1 Error
Statistical dispersion
Sampling
47. A numerical facsimilie or representation of a real-world phenomenon.
Standard error
Simulation
Correlation coefficient
That is the median value
48. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.
Placebo effect
Lurking variable
Observational study
Ratio measurements
49. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively
Joint probability
The Expected value
Residuals
Independence or Statistical independence
50. Gives the probability distribution for a continuous random variable.
A probability density function
Power of a test
Mutual independence
Law of Parsimony