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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. Probability of rejecting a true null hypothesis.
An Elementary event
Alpha value (Level of Significance)
Likert scale
Step 1 of a statistical experiment
2. 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.
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3. Where the null hypothesis is falsely rejected giving a 'false positive'.
Experimental and observational studies
Marginal distribution
Type I errors
the population correlation
4. Some commonly used symbols for population parameters
the population mean
the population correlation
A sampling distribution
Interval measurements
5. Cov[X - Y] :
Probability and statistics
Conditional probability
covariance of X and Y
Marginal distribution
6. A measure that is relevant or appropriate as a representation of that property.
Conditional distribution
Standard error
Valid measure
Posterior probability
7. Is a sample and the associated data points.
A data set
methods of least squares
Type I errors
Reliable measure
8. Is a function of the known data that is used to estimate an unknown parameter; an estimate is the result from the actual application of the function to a particular set of data. The mean can be used as an estimator.
Block
methods of least squares
Coefficient of determination
Estimator
9. 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 sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Average and arithmetic mean
hypotheses
The sample space
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.
That value is the median value
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
A sampling distribution
the sample or population mean
11. Is a sample space over which a probability measure has been defined.
Parameter - or 'statistical parameter'
The Covariance between two random variables X and Y - with expected values E(X) =
The average - or arithmetic mean
A probability space
12. 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
Observational study
Conditional probability
Variability
Step 2 of a statistical experiment
13. (cdfs) are denoted by upper case letters - e.g. F(x).
the population cumulants
f(z) - and its cdf by F(z).
Observational study
Cumulative distribution functions
14. Many statistical methods seek to minimize the mean-squared error - and these are called
A Distribution function
Marginal distribution
That value is the median value
methods of least squares
15. A group of individuals sharing some common features that might affect the treatment.
A Probability measure
the sample or population mean
Beta value
Block
16. When you have two or more competing models - choose the simpler of the two models.
the population variance
f(z) - and its cdf by F(z).
Simulation
Law of Parsimony
17. Have no meaningful rank order among values.
Interval measurements
Bias
Particular realizations of a random variable
Nominal measurements
18. Is used in 'mathematical statistics' (alternatively - 'statistical theory') to study the sampling distributions of sample statistics and - more generally - the properties of statistical procedures. The use of any statistical method is valid when the
Placebo effect
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Probability
Coefficient of determination
19. Is that part of a population which is actually observed.
Mutual independence
Inferential
Dependent Selection
A sample
20. Performing the experiment following the experimental protocol and analyzing the data following the experimental protocol. 4. Further examining the data set in secondary analyses - to suggest new hypotheses for future study. 5. Documenting and present
Credence
Alpha value (Level of Significance)
Step 3 of a statistical experiment
Type II errors
21. 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 adjustment
inferential statistics
Prior probability
Standard error
22. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.
Parameter - or 'statistical parameter'
Independent Selection
f(z) - and its cdf by F(z).
P-value
23. A numerical measure that describes an aspect of a sample.
Greek letters
Statistic
experimental studies and observational studies.
Nominal measurements
24. Is a measure of the asymmetry of the probability distribution of a real-valued random variable. Roughly speaking - a distribution has positive skew (right-skewed) if the higher tail is longer and negative skew (left-skewed) if the lower tail is longe
categorical variables
Skewness
hypotheses
Conditional distribution
25. A numerical measure that describes an aspect of a population.
nominal - ordinal - interval - and ratio
Cumulative distribution functions
the population correlation
Parameter
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
Step 1 of a statistical experiment
Block
Divide the sum by the number of values.
Probability
27. A variable describes an individual by placing the individual into a category or a group.
Probability density
Ordinal measurements
Qualitative variable
Sampling
28. Working from a null hypothesis two basic forms of error are recognized:
Joint probability
An experimental study
The Range
Type I errors & Type II errors
29. The probability of correctly detecting a false null hypothesis.
Skewness
Null hypothesis
Power of a test
A statistic
30. 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.
Credence
The median value
Correlation
Step 2 of a statistical experiment
31. Describes a characteristic of an individual to be measured or observed.
Ratio measurements
Variable
Trend
Prior probability
32. 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
Parameter
Beta value
Correlation
Atomic event
33. Describes the spread in the values of the sample statistic when many samples are taken.
Placebo effect
Variability
applied statistics
the population mean
34. 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
Step 3 of a statistical experiment
Posterior probability
the population correlation
35. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as
categorical variables
f(z) - and its cdf by F(z).
hypothesis
Individual
36. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.
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37. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
experimental studies and observational studies.
applied statistics
Pairwise independence
Conditional probability
38. 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
A Statistical parameter
s-algebras
An experimental study
39. Another name for elementary event.
Atomic event
Marginal distribution
Prior probability
s-algebras
40. 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
Lurking variable
Bias
observational study
41. Rejecting a true null hypothesis.
A probability density function
Type 1 Error
Variability
Experimental and observational studies
42. Samples are drawn from two different populations such that there is a matching of the first sample data drawn and a corresponding data value in the second sample data.
the population cumulants
Variable
expected value of X
Dependent Selection
43. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.
Parameter - or 'statistical parameter'
A Distribution function
Descriptive
Law of Parsimony
44. Of a group of numbers is the center point of all those number values.
P-value
The average - or arithmetic mean
the population mean
Sampling frame
45. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.
A statistic
A probability space
Quantitative variable
A Probability measure
46. 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
An Elementary event
hypothesis
Estimator
Seasonal effect
47. A numerical measure that assesses the strength of a linear relationship between two variables.
Correlation coefficient
Skewness
Conditional probability
The median value
48. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.
Binomial experiment
Credence
Individual
Nominal measurements
49. Gives the probability of events in a probability space.
A Probability measure
A sampling distribution
the population cumulants
Random variables
50. ?r
Ratio measurements
the population cumulants
A probability distribution
Inferential statistics