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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 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.
Block
Marginal distribution
Statistical inference
Atomic event
2. (cdfs) are denoted by upper case letters - e.g. F(x).
the population cumulants
Block
Cumulative distribution functions
nominal - ordinal - interval - and ratio
3. The collection of all possible outcomes in an experiment.
Sample space
Parameter
A probability distribution
Descriptive statistics
4. A numerical measure that describes an aspect of a population.
An estimate of a parameter
The sample space
Statistical inference
Parameter
5. Is data arising from counting that can take only non-negative integer values.
Parameter
Prior probability
Statistical adjustment
Count data
6. 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.
observational study
The Mean of a random variable
Likert scale
A Distribution function
7. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.
Bias
Treatment
That is the median value
An experimental study
8. 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.
variance of X
Experimental and observational studies
The median value
Probability
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.
Kurtosis
quantitative variables
Sampling Distribution
Probability and statistics
10. Is used to describe probability in a continuous probability distribution. For example - you can't say that the probability of a man being six feet tall is 20% - but you can say he has 20% of chances of being between five and six feet tall. Probabilit
Conditional distribution
Descriptive
Probability density
Type I errors
11. A numerical measure that describes an aspect of a sample.
Statistic
The sample space
Bias
Binomial experiment
12. Is that part of a population which is actually observed.
A data set
experimental studies and observational studies.
A sample
Variable
13.
the population mean
Simpson's Paradox
Probability density
Step 3 of a statistical experiment
14. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).
A Probability measure
Probability density functions
Divide the sum by the number of values.
f(z) - and its cdf by F(z).
15. The proportion of the explained variation by a linear regression model in the total variation.
The Mean of a random variable
Coefficient of determination
applied statistics
Step 1 of a statistical experiment
16. 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.
Statistics
Statistical adjustment
Type 2 Error
Marginal distribution
17. 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
Probability
Statistical inference
Block
hypothesis
18. 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
hypothesis
Step 1 of a statistical experiment
Binomial experiment
Experimental and observational studies
19. Is the probability of some event A - assuming event B. Conditional probability is written P(A|B) - and is read 'the probability of A - given B'
Estimator
Conditional probability
An Elementary event
Atomic event
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
Alpha value (Level of Significance)
Sampling frame
Bias
Step 3 of a statistical experiment
21. 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
The sample space
The Expected value
Skewness
Standard error
22. To find the average - or arithmetic mean - of a set of numbers:
Power of a test
Step 2 of a statistical experiment
Divide the sum by the number of values.
Binomial experiment
23. ?r
the population cumulants
That value is the median value
Prior probability
A probability space
24. 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
Correlation coefficient
Parameter
Observational study
The median value
25. ?
Independence or Statistical independence
Likert scale
the population correlation
Seasonal effect
26. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.
Type II errors
categorical variables
Statistics
Outlier
27. Have imprecise differences between consecutive values - but have a meaningful order to those values
variance of X
Ordinal measurements
Binomial experiment
The Mean of a random variable
28. Another name for elementary event.
Joint probability
Binomial experiment
Atomic event
An Elementary event
29. Involves taking measurements of the system under study - manipulating the system - and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements.
An experimental study
Estimator
Sample space
Confounded variables
30. When there is an even number of values...
Probability and statistics
A probability distribution
That is the median value
Null hypothesis
31. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
Quantitative variable
Joint probability
Residuals
Atomic event
32. Error also refers to the extent to which individual observations in a sample differ from a central value - such as
Independent Selection
Correlation coefficient
the sample or population mean
Pairwise independence
33. Is data that can take only two values - usually represented by 0 and 1.
Binary data
An event
Variability
Beta value
34. A numerical facsimilie or representation of a real-world phenomenon.
experimental studies and observational studies.
Coefficient of determination
The Mean of a random variable
Simulation
35. Where the null hypothesis is falsely rejected giving a 'false positive'.
Seasonal effect
Type I errors & Type II errors
Statistical inference
Type I errors
36. 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.
Bias
The variance of a random variable
f(z) - and its cdf by F(z).
Placebo effect
37. Gives the probability of events in a probability space.
Joint probability
A Probability measure
Cumulative distribution functions
The standard deviation
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).
Reliable measure
An event
Correlation
Sampling frame
39. Have no meaningful rank order among values.
Power of a test
Nominal measurements
Alpha value (Level of Significance)
Sample space
40. Is denoted by - pronounced 'x bar'.
Joint probability
A random variable
Inferential statistics
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
41. A numerical measure that assesses the strength of a linear relationship between two variables.
Correlation coefficient
Standard error
That is the median value
Variable
42. 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
Type II errors
A population or statistical population
Law of Parsimony
43. Is a set of entities about which statistical inferences are to be drawn - often based on random sampling. One can also talk about a population of measurements or values.
Bias
A population or statistical population
Statistical inference
Dependent Selection
44. A data value that falls outside the overall pattern of the graph.
Outlier
Probability
Probability density functions
the population mean
45. (or multivariate random variable) is a vector whose components are random variables on the same probability space.
Trend
Credence
Parameter
A Random vector
46. E[X] :
That value is the median value
Confounded variables
A population or statistical population
expected value of X
47. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.
Sampling frame
Statistical adjustment
Type 1 Error
Atomic event
48. Failing to reject a false null hypothesis.
Type 2 Error
hypothesis
Placebo effect
Independence or Statistical independence
49. Are usually written in upper case roman letters: X - Y - etc.
Random variables
An Elementary event
expected value of X
Inferential
50. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Sampling Distribution
f(z) - and its cdf by F(z).
Pairwise independence
Binomial experiment