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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.
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 a typed measurement - it can be a boolean value - a real number - a vector (in which case it's also called a data vector) - etc.
Null hypothesis
Probability density
Residuals
A data point
2. 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
Step 3 of a statistical experiment
Inferential
hypothesis
A Distribution function
3. 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
Correlation
Binomial experiment
Simpson's Paradox
Statistics
4. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.
A sample
A statistic
nominal - ordinal - interval - and ratio
Statistical dispersion
5. Is the probability of an event - ignoring any information about other events. The marginal probability of A is written P(A). Contrast with conditional probability.
the population correlation
nominal - ordinal - interval - and ratio
Marginal probability
Random variables
6. Descriptive statistics and inferential statistics (a.k.a. - predictive statistics) together comprise
A Probability measure
A population or statistical population
A Random vector
applied statistics
7. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Pairwise independence
Ratio measurements
categorical variables
Divide the sum by the number of values.
8. 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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9. A numerical measure that describes an aspect of a population.
An estimate of a parameter
Parameter
Descriptive
expected value of X
10. When there is an even number of values...
Type 2 Error
Inferential
That is the median value
Type 1 Error
11. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)
Type II errors
nominal - ordinal - interval - and ratio
s-algebras
A statistic
12. Another name for elementary event.
Type 1 Error
Simulation
Atomic event
experimental studies and observational studies.
13. 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
hypothesis
Standard error
Law of Parsimony
Observational study
14. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.
Type II errors
the population correlation
That value is the median value
Prior probability
15. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.
Individual
Type II errors
Atomic event
Probability density functions
16. Is defined as the expected value of random variable (X -
Marginal probability
A probability distribution
The Covariance between two random variables X and Y - with expected values E(X) =
s-algebras
17. The probability of correctly detecting a false null hypothesis.
Type 1 Error
Bias
Power of a test
experimental studies and observational studies.
18. A numerical facsimilie or representation of a real-world phenomenon.
Simulation
Null hypothesis
Coefficient of determination
Statistical adjustment
19. 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
the population mean
Prior probability
P-value
20. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as
Dependent Selection
quantitative variables
Average and arithmetic mean
Binary data
21. The collection of all possible outcomes in an experiment.
Sample space
Law of Parsimony
Estimator
Correlation coefficient
22. Of a group of numbers is the center point of all those number values.
Probability density functions
The average - or arithmetic mean
Random variables
Valid measure
23. Have imprecise differences between consecutive values - but have a meaningful order to those values
Ordinal measurements
Statistical inference
categorical variables
Observational study
24. 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 Distribution function
Null hypothesis
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
An experimental study
25. Two variables such that their effects on the response variable cannot be distinguished from each other.
A Probability measure
Sampling Distribution
Confounded variables
Divide the sum by the number of values.
26. 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 space
Type 1 Error
Type 2 Error
Kurtosis
27. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.
Qualitative variable
Statistics
Step 3 of a statistical experiment
Placebo effect
28. When you have two or more competing models - choose the simpler of the two models.
A statistic
nominal - ordinal - interval - and ratio
The variance of a random variable
Law of Parsimony
29. (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 Expected value
Block
covariance of X and Y
The sample space
30. 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.
Statistic
Statistical inference
hypotheses
methods of least squares
31. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.
nominal - ordinal - interval - and ratio
Probability density
An estimate of a parameter
Correlation
32. Where the null hypothesis is falsely rejected giving a 'false positive'.
Binomial experiment
Independent Selection
Type I errors
Statistic
33. Is the probability distribution - under repeated sampling of the population - of a given statistic.
An Elementary event
A sampling distribution
Joint probability
Coefficient of determination
34. Is data arising from counting that can take only non-negative integer values.
Count data
Law of Large Numbers
Statistic
Variable
35. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.
That is the median value
Step 3 of a statistical experiment
Binomial experiment
Probability and statistics
36. A numerical measure that assesses the strength of a linear relationship between two variables.
Type II errors
Step 3 of a statistical experiment
An experimental study
Correlation coefficient
37. Are usually written in upper case roman letters: X - Y - etc.
Statistical adjustment
Independent Selection
nominal - ordinal - interval - and ratio
Random variables
38. Long-term upward or downward movement over time.
A statistic
Posterior probability
An Elementary event
Trend
39. A data value that falls outside the overall pattern of the graph.
Individual
Type 1 Error
variance of X
Outlier
40. Describes the spread in the values of the sample statistic when many samples are taken.
s-algebras
Quantitative variable
Ordinal measurements
Variability
41. Any specific experimental condition applied to the subjects
A probability density function
Treatment
Nominal measurements
Trend
42. Is data that can take only two values - usually represented by 0 and 1.
Binary data
A data set
Simple random sample
Statistical adjustment
43. In particular - the pdf of the standard normal distribution is denoted by
An experimental study
A Distribution function
f(z) - and its cdf by F(z).
Independence or Statistical independence
44. 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.
Seasonal effect
Sampling Distribution
Kurtosis
nominal - ordinal - interval - and ratio
45. Is its expected value. The mean (or sample mean of a data set is just the average value.
A data set
The Mean of a random variable
Sample space
Placebo effect
46. 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)
Skewness
Coefficient of determination
Interval measurements
Descriptive
47. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data
Pairwise independence
nominal - ordinal - interval - and ratio
Inferential statistics
Posterior probability
48. 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.
Credence
Independent Selection
hypotheses
nominal - ordinal - interval - and ratio
49. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.
Parameter
Power of a test
Sampling Distribution
Simpson's Paradox
50. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.
P-value
Correlation coefficient
Conditional probability
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.