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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. Some commonly used symbols for sample statistics
A data set
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Joint probability
2. The standard deviation of a sampling distribution.
Binomial experiment
Standard error
Count data
Independence or Statistical independence
3. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.
Descriptive statistics
Type II errors
Type 2 Error
Descriptive
4. Are usually written in upper case roman letters: X - Y - etc.
Random variables
Divide the sum by the number of values.
A random variable
The Mean of a random variable
5. Two variables such that their effects on the response variable cannot be distinguished from each other.
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
The Expected value
Confounded variables
The variance of a random variable
6. S^2
That is the median value
the population variance
Binomial experiment
Count data
7. Have no meaningful rank order among values.
Standard error
Treatment
Nominal measurements
Step 2 of a statistical experiment
8. A measure that is relevant or appropriate as a representation of that property.
applied statistics
Lurking variable
Observational study
Valid measure
9. Of a group of numbers is the center point of all those number values.
The average - or arithmetic mean
A likelihood function
Probability density
A probability distribution
10. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.
The Expected value
Credence
Sampling Distribution
Individual
11. To find the average - or arithmetic mean - of a set of numbers:
variance of X
Random variables
Placebo effect
Divide the sum by the number of values.
12. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
the population mean
Seasonal effect
Quantitative variable
Statistics
13. 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
Skewness
P-value
Step 3 of a statistical experiment
Greek letters
14. Is its expected value. The mean (or sample mean of a data set is just the average value.
Observational study
Statistical adjustment
The Mean of a random variable
Type 2 Error
15. Var[X] :
expected value of X
categorical variables
Binomial experiment
variance of X
16. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data
categorical variables
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Posterior probability
Type II errors
17. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.
Likert scale
Valid measure
covariance of X and Y
Prior probability
18. When you have two or more competing models - choose the simpler of the two models.
The Mean of a random variable
Trend
The standard deviation
Law of Parsimony
19. (cdfs) are denoted by upper case letters - e.g. F(x).
A statistic
A Statistical parameter
Sampling frame
Cumulative distribution functions
20. 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)
Interval measurements
Outlier
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Simple random sample
21. Describes a characteristic of an individual to be measured or observed.
A likelihood function
Sampling frame
Variable
Law of Parsimony
22. Where the null hypothesis is falsely rejected giving a 'false positive'.
Confounded variables
Type II errors
Average and arithmetic mean
Type I errors
23. 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}.
experimental studies and observational studies.
Alpha value (Level of Significance)
The sample space
covariance of X and Y
24. 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.
The median value
A random variable
descriptive statistics
Placebo effect
25. Rejecting a true null hypothesis.
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Type 1 Error
Independent Selection
That is the median value
26. The collection of all possible outcomes in an experiment.
Observational study
Sample space
Standard error
hypothesis
27. Data are gathered and correlations between predictors and response are investigated.
Seasonal effect
A Statistical parameter
The Covariance between two random variables X and Y - with expected values E(X) =
observational study
28. Some commonly used symbols for population parameters
categorical variables
Alpha value (Level of Significance)
the population mean
Coefficient of determination
29. 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
An Elementary event
Placebo effect
Sampling frame
Null hypothesis
30. 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
Independence or Statistical independence
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
The variance of a random variable
Variability
31. (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.
Individual
An Elementary event
A Distribution function
The sample space
32. 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.
Inferential statistics
Probability density functions
Outlier
Conditional distribution
33. 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
P-value
Probability density
Probability and statistics
methods of least squares
34. A variable describes an individual by placing the individual into a category or a group.
Qualitative variable
Descriptive
Conditional distribution
Statistical inference
35. Long-term upward or downward movement over time.
Trend
Skewness
Inferential statistics
Descriptive statistics
36. 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.
hypotheses
Estimator
Type 2 Error
A Distribution function
37. Gives the probability distribution for a continuous random variable.
Type 2 Error
A probability density function
Trend
Estimator
38. 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.
nominal - ordinal - interval - and ratio
Dependent Selection
Marginal probability
Statistical dispersion
39. Is a sample and the associated data points.
The average - or arithmetic mean
A Random vector
That value is the median value
A data set
40. Given two random variables X and Y - the joint distribution of X and Y is the probability distribution of X and Y together.
Nominal measurements
An Elementary event
Experimental and observational studies
Joint distribution
41. Are simply two different terms for the same thing. Add the given values
Average and arithmetic mean
Mutual independence
The Expected value
Step 2 of a statistical experiment
42. Is defined as the expected value of random variable (X -
Prior probability
Alpha value (Level of Significance)
An estimate of a parameter
The Covariance between two random variables X and Y - with expected values E(X) =
43. Is the probability distribution - under repeated sampling of the population - of a given statistic.
A sampling distribution
Conditional distribution
An estimate of a parameter
Type I errors
44. 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
The Mean of a random variable
Variable
Step 1 of a statistical experiment
45. Gives the probability of events in a probability space.
That value is the median value
Prior probability
A Probability measure
The Covariance between two random variables X and Y - with expected values E(X) =
46. 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.
Kurtosis
Independent Selection
the population cumulants
A probability distribution
47. Any specific experimental condition applied to the subjects
Treatment
Null hypothesis
Correlation coefficient
Seasonal effect
48. 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
That is the median value
Ratio measurements
Seasonal effect
The median value
49. 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.
P-value
Estimator
Statistics
Individual
50. 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.
Coefficient of determination
An experimental study
Statistics
inferential statistics
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