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Test your basic knowledge |
CLEP General Mathematics: Probability And Statistics
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Study First
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. The standard deviation of a sampling distribution.
Seasonal effect
Block
Standard error
A data set
2. (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
Likert scale
The Expected value
Bias
Type II errors
3. 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.
Reliable measure
Variability
Probability density
Statistics
4. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.
Statistical dispersion
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Type II errors
Step 1 of a statistical experiment
5. 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
The variance of a random variable
Ratio measurements
A Statistical parameter
Step 1 of a statistical experiment
6. In number theory - scatter plots of data generated by a distribution function may be transformed with familiar tools used in statistics to reveal underlying patterns - which may then lead to
Statistical adjustment
Step 2 of a statistical experiment
Interval measurements
hypotheses
7. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.
Type 2 Error
A probability distribution
variance of X
An estimate of a parameter
8. 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
The variance of a random variable
Independence or Statistical independence
Sampling
Step 3 of a statistical experiment
9. Are usually written in upper case roman letters: X - Y - etc.
Random variables
Pairwise independence
Independent Selection
Step 1 of a statistical experiment
10. 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}.
applied statistics
The sample space
Variability
Statistical inference
11. Of a group of numbers is the center point of all those number values.
The average - or arithmetic mean
Step 2 of a statistical experiment
That is the median value
Joint distribution
12. 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
Probability and statistics
categorical variables
Joint distribution
hypothesis
13. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data
Posterior probability
Bias
A statistic
A population or statistical population
14. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
Cumulative distribution functions
Step 2 of a statistical experiment
Quantitative variable
Power of a test
15. A measure that is relevant or appropriate as a representation of that property.
the population variance
Valid measure
Correlation coefficient
Interval measurements
16. There are two major types of causal statistical studies: In both types of studies - the effect of differences of an independent variable (or variables) on the behavior of the dependent variable are observed. The difference between the two types lies
Greek letters
experimental studies and observational studies.
A Distribution function
A Random vector
17. Is its expected value. The mean (or sample mean of a data set is just the average value.
A Statistical parameter
The Mean of a random variable
the sample or population mean
Reliable measure
18. 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.
Sampling
Nominal measurements
the sample or population mean
A data set
19. 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.
Binary data
A data point
The average - or arithmetic mean
Nominal measurements
20. 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
Greek letters
Correlation
expected value of X
Residuals
21. 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.
The standard deviation
Trend
Independent Selection
Statistics
22. 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
Type 1 Error
Seasonal effect
observational study
23. Any specific experimental condition applied to the subjects
Count data
Residuals
Treatment
Marginal probability
24. A numerical measure that describes an aspect of a sample.
The standard deviation
Count data
Statistic
Standard error
25. Are simply two different terms for the same thing. Add the given values
That value is the median value
Average and arithmetic mean
Correlation coefficient
observational study
26. A group of individuals sharing some common features that might affect the treatment.
An Elementary event
The average - or arithmetic mean
the population correlation
Block
27. Probability of rejecting a true null hypothesis.
Law of Large Numbers
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Alpha value (Level of Significance)
Simpson's Paradox
28. A data value that falls outside the overall pattern of the graph.
A random variable
A population or statistical population
Outlier
the population variance
29. Is denoted by - pronounced 'x bar'.
A probability distribution
Parameter
the sample or population mean
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
30. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.
An estimate of a parameter
Prior probability
Probability and statistics
Credence
31. 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
Step 2 of a statistical experiment
the sample or population mean
Statistical dispersion
Particular realizations of a random variable
32. Describes a characteristic of an individual to be measured or observed.
Greek letters
hypothesis
Simpson's Paradox
Variable
33. Some commonly used symbols for population parameters
Ratio measurements
the population variance
the population mean
Descriptive
34. Have imprecise differences between consecutive values - but have a meaningful order to those values
Placebo effect
Atomic event
Ordinal measurements
the sample or population mean
35. Some commonly used symbols for sample statistics
The Mean of a random variable
A data set
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
A Statistical parameter
36. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).
Qualitative variable
Kurtosis
The standard deviation
Power of a test
37. Gives the probability of events in a probability space.
P-value
Marginal probability
The average - or arithmetic mean
A Probability measure
38. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.
Placebo effect
Conditional probability
Statistical dispersion
the sample or population mean
39. Descriptive statistics and inferential statistics (a.k.a. - predictive statistics) together comprise
applied statistics
Descriptive statistics
P-value
s-algebras
40. (or multivariate random variable) is a vector whose components are random variables on the same probability space.
A Random vector
Marginal distribution
Independence or Statistical independence
hypotheses
41. Data are gathered and correlations between predictors and response are investigated.
observational study
Correlation coefficient
hypotheses
An experimental study
42. Summarize the population data by describing what was observed in the sample numerically or graphically. Numerical descriptors include mean and standard deviation for continuous data types (like heights or weights) - while frequency and percentage are
The variance of a random variable
Sampling Distribution
Type I errors
Descriptive statistics
43. E[X] :
nominal - ordinal - interval - and ratio
Skewness
Atomic event
expected value of X
44. Statistics involve methods of using information from a sample to draw conclusions regarding the population.
Inferential
Prior probability
Divide the sum by the number of values.
the population mean
45. Is defined as the expected value of random variable (X -
the population correlation
The Covariance between two random variables X and Y - with expected values E(X) =
Standard error
Sampling
46. 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.
Step 1 of a statistical experiment
Variable
That value is the median value
Type I errors & Type II errors
47. Is a sample and the associated data points.
Skewness
A data set
Marginal distribution
Random variables
48. A variable describes an individual by placing the individual into a category or a group.
Quantitative variable
Qualitative variable
The Covariance between two random variables X and Y - with expected values E(X) =
Sample space
49. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).
Sampling Distribution
Joint distribution
The median value
Probability density functions
50. Changes over time that show a regular periodicity in the data where regular means over a fixed interval; the time between repetitions is called the period.
Simulation
Divide the sum by the number of values.
Seasonal effect
Random variables