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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.
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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 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.
Nominal measurements
The variance of a random variable
Trend
A population or statistical population
2. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.
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3. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively
A random variable
An estimate of a parameter
Residuals
Coefficient of determination
4. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.
Independent Selection
A data point
Sampling Distribution
Divide the sum by the number of values.
5. A numerical measure that describes an aspect of a population.
An event
Individual
Statistical inference
Parameter
6. The proportion of the explained variation by a linear regression model in the total variation.
Statistic
A Distribution function
Coefficient of determination
A statistic
7. Is a sample and the associated data points.
A data set
Simple random sample
Block
the population correlation
8. Another name for elementary event.
the population mean
Atomic event
A probability distribution
Reliable measure
9. 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
Ratio measurements
An estimate of a parameter
Observational study
the population correlation
10. Is defined as the expected value of random variable (X -
An estimate of a parameter
The Covariance between two random variables X and Y - with expected values E(X) =
The Mean of a random variable
Step 1 of a statistical experiment
11. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data
experimental studies and observational studies.
A probability density function
Law of Parsimony
Posterior probability
12. 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
A sampling distribution
Step 2 of a statistical experiment
Parameter - or 'statistical parameter'
Type 1 Error
13. Of a group of numbers is the center point of all those number values.
The average - or arithmetic mean
Conditional probability
The standard deviation
A Distribution function
14. Is the probability distribution - under repeated sampling of the population - of a given statistic.
Statistical adjustment
A sampling distribution
Statistical inference
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
15. Have imprecise differences between consecutive values - but have a meaningful order to those values
Binary data
Ordinal measurements
Descriptive statistics
The Mean of a random variable
16. In particular - the pdf of the standard normal distribution is denoted by
f(z) - and its cdf by F(z).
Descriptive statistics
Beta value
A likelihood function
17. A variable describes an individual by placing the individual into a category or a group.
Marginal distribution
Coefficient of determination
Qualitative variable
That value is the median value
18. 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.
covariance of X and Y
An event
Dependent Selection
The Range
19. The collection of all possible outcomes in an experiment.
A Statistical parameter
Skewness
Law of Parsimony
Sample space
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.
s-algebras
Probability density
An Elementary event
Joint distribution
21. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
Divide the sum by the number of values.
Quantitative variable
Reliable measure
Likert scale
22. 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.
An Elementary event
Sampling
Atomic event
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
23. A group of individuals sharing some common features that might affect the treatment.
Block
variance of X
The Range
nominal - ordinal - interval - and ratio
24. Is a function that gives the probability of all elements in a given space: see List of probability distributions
nominal - ordinal - interval - and ratio
A probability distribution
Variable
Credence
25. 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
Descriptive statistics
Inferential statistics
Simulation
Interval measurements
26. Two events are independent if the outcome of one does not affect that of the other (for example - getting a 1 on one die roll does not affect the probability of getting a 1 on a second roll). Similarly - when we assert that two random variables are i
Conditional probability
Independence or Statistical independence
The median value
covariance of X and Y
27. Given two jointly distributed random variables X and Y - the marginal distribution of X is simply the probability distribution of X ignoring information about Y.
Marginal distribution
Correlation coefficient
Simple random sample
Conditional probability
28. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Pairwise independence
Qualitative variable
Statistical adjustment
quantitative variables
29. 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
A probability density function
Average and arithmetic mean
Step 3 of a statistical experiment
30. 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}.
That is the median value
Independent Selection
Marginal distribution
The sample space
31. Where the null hypothesis is falsely rejected giving a 'false positive'.
Statistical inference
A sample
Type I errors
Statistic
32. 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
The sample space
A probability density function
Observational study
Pairwise independence
33. Working from a null hypothesis two basic forms of error are recognized:
Sampling
Type I errors & Type II errors
Simulation
Greek letters
34. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.
Trend
A statistic
Valid measure
f(z) - and its cdf by F(z).
35. 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.
Dependent Selection
Probability and statistics
Independent Selection
Qualitative variable
36. 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.
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Kurtosis
Variable
Statistics
37. 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.
Statistical inference
Inferential
Sampling
A sampling distribution
38. 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
Null hypothesis
The Mean of a random variable
hypothesis
Skewness
39. A numerical facsimilie or representation of a real-world phenomenon.
applied statistics
Kurtosis
Simulation
A probability space
40. Are usually written in upper case roman letters: X - Y - etc.
Random variables
Statistical adjustment
Greek letters
A statistic
41. Statistics involve methods of using information from a sample to draw conclusions regarding the population.
Binomial experiment
Beta value
Inferential
A sample
42. Is that part of a population which is actually observed.
A sample
A probability distribution
the population mean
That is the median value
43. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.
Type II errors
A statistic
Valid measure
the population mean
44. To find the average - or arithmetic mean - of a set of numbers:
Random variables
Divide the sum by the number of values.
Type II errors
Quantitative variable
45. The standard deviation of a sampling distribution.
That is the median value
The average - or arithmetic mean
Standard error
The Covariance between two random variables X and Y - with expected values E(X) =
46. A measurement such that the random error is small
Binomial experiment
Block
Reliable measure
Variability
47. Many statistical methods seek to minimize the mean-squared error - and these are called
Outlier
Sampling
Binomial experiment
methods of least squares
48. Are simply two different terms for the same thing. Add the given values
Alpha value (Level of Significance)
Average and arithmetic mean
A data point
Law of Large Numbers
49. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.
Power of a test
Sampling frame
Particular realizations of a random variable
A sample
50. 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
A probability space
That is the median value
Null hypothesis
Parameter