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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. Is that part of a population which is actually observed.
A likelihood function
A sample
the population cumulants
A statistic
2. Have both a meaningful zero value and the distances between different measurements defined; they provide the greatest flexibility in statistical methods that can be used for analyzing the data
Binomial experiment
The standard deviation
The median value
Ratio measurements
3. A common goal for a statistical research project is to investigate causality - and in particular to draw a conclusion on the effect of changes in the values of predictors or independent variables on dependent variables or response.
Experimental and observational studies
A sample
Posterior probability
An event
4. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.
Interval measurements
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Prior probability
Posterior probability
5. 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.
Descriptive
A data set
Parameter
That value is the median value
6. Statistical methods can be used for summarizing or describing a collection of data; this is called
A sampling distribution
Bias
the population cumulants
descriptive statistics
7. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.
Step 3 of a statistical experiment
P-value
Confounded variables
Interval measurements
8. The probability of correctly detecting a false null hypothesis.
Average and arithmetic mean
A Distribution function
Power of a test
f(z) - and its cdf by F(z).
9. 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.
Type II errors
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Parameter
Kurtosis
10. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.
Marginal probability
Sampling Distribution
Bias
A probability space
11. Data are gathered and correlations between predictors and response are investigated.
observational study
Dependent Selection
Sample space
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
12. Two variables such that their effects on the response variable cannot be distinguished from each other.
Qualitative variable
Confounded variables
Individual
Variable
13. Of a group of numbers is the center point of all those number values.
Confounded variables
The average - or arithmetic mean
covariance of X and Y
Type 1 Error
14. When you have two or more competing models - choose the simpler of the two models.
Law of Parsimony
nominal - ordinal - interval - and ratio
Correlation
Type 2 Error
15. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).
An event
Descriptive
Statistics
The standard deviation
16. A numerical facsimilie or representation of a real-world phenomenon.
Simulation
Probability and statistics
Skewness
observational study
17. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.
A data set
A probability distribution
Statistical adjustment
Outlier
18. 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.
observational study
The variance of a random variable
Binary data
Null hypothesis
19. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)
Divide the sum by the number of values.
Individual
Statistics
Null hypothesis
20. In particular - the pdf of the standard normal distribution is denoted by
f(z) - and its cdf by F(z).
The sample space
Random variables
Type II errors
21. There are four main levels of measurement used in statistics: Each of these have different degrees of usefulness in statistical research.
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
nominal - ordinal - interval - and ratio
Marginal probability
The Mean of a random variable
22. 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.
A probability density function
A probability space
Confounded variables
Statistics
23. ?r
the population cumulants
Marginal probability
Alpha value (Level of Significance)
Probability
24.
Power of a test
Type I errors & Type II errors
the population mean
Probability density
25. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
Qualitative variable
Quantitative variable
the population mean
A likelihood function
26. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).
Probability density functions
the population variance
Cumulative distribution functions
Seasonal effect
27. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).
Likert scale
covariance of X and Y
Greek letters
Descriptive statistics
28. Any specific experimental condition applied to the subjects
The Range
the population variance
Cumulative distribution functions
Treatment
29. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Pairwise independence
inferential statistics
Likert scale
Individual
30. (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.
Probability density functions
Beta value
An Elementary event
quantitative variables
31. Long-term upward or downward movement over time.
Marginal distribution
Trend
Probability
An event
32. 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.
The sample space
Bias
Ordinal measurements
Inferential
33. Error also refers to the extent to which individual observations in a sample differ from a central value - such as
the population correlation
Mutual independence
Individual
the sample or population mean
34. A numerical measure that assesses the strength of a linear relationship between two variables.
The Mean of a random variable
observational study
Correlation coefficient
experimental studies and observational studies.
35. Is denoted by - pronounced 'x bar'.
A random variable
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
A population or statistical population
Probability and statistics
36. Descriptive statistics and inferential statistics (a.k.a. - predictive statistics) together comprise
That is the median value
Simpson's Paradox
the population mean
applied statistics
37. (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
Binomial experiment
inferential statistics
variance of X
A likelihood function
38. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.
An estimate of a parameter
The standard deviation
Interval measurements
Coefficient of determination
39. Is data arising from counting that can take only non-negative integer values.
Dependent Selection
Sampling frame
An event
Count data
40. Is data that can take only two values - usually represented by 0 and 1.
Inferential
Binary data
A data point
Residuals
41. A numerical measure that describes an aspect of a sample.
Alpha value (Level of Significance)
Parameter
Statistic
Placebo effect
42. Probability of accepting a false null hypothesis.
Beta value
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
An estimate of a parameter
Sampling Distribution
43. 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).
quantitative variables
Joint probability
The median value
Sampling frame
44. Is a parameter that indexes a family of probability distributions.
That value is the median value
A Statistical parameter
Credence
Likert scale
45. Have imprecise differences between consecutive values - but have a meaningful order to those values
Correlation coefficient
Ordinal measurements
methods of least squares
experimental studies and observational studies.
46. Failing to reject a false null hypothesis.
Type 2 Error
Atomic event
hypotheses
expected value of X
47. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as
Correlation coefficient
Joint distribution
A probability space
categorical variables
48. A subjective estimate of probability.
Credence
Probability and statistics
Block
Type I errors
49. 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
A probability density function
Step 3 of a statistical experiment
Inferential statistics
An Elementary event
50. Another name for elementary event.
Atomic event
Cumulative distribution functions
Type II errors
Simple random sample