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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. S^2
Interval measurements
Treatment
the population variance
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
f(z) - and its cdf by F(z).
Bias
Placebo effect
3. Is defined as the expected value of random variable (X -
Credence
Variability
The Covariance between two random variables X and Y - with expected values E(X) =
Treatment
4. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).
The median value
Random variables
Probability density functions
Type II errors
5. 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.
Variability
That value is the median value
Independent Selection
A Probability measure
6. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.
Prior probability
Simulation
Average and arithmetic mean
Standard error
7. A measure that is relevant or appropriate as a representation of that property.
Outlier
Kurtosis
Valid measure
Independent Selection
8. Some commonly used symbols for population parameters
applied statistics
A sample
the population mean
A Probability measure
9. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.
categorical variables
Sampling frame
Binomial experiment
variance of X
10. Where the null hypothesis is falsely rejected giving a 'false positive'.
An Elementary event
Type 1 Error
Type I errors
Posterior probability
11. 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
Block
The Mean of a random variable
Nominal measurements
Descriptive statistics
12. Is data arising from counting that can take only non-negative integer values.
Statistical dispersion
Probability
Count data
Binary data
13. Gives the probability of events in a probability space.
Quantitative variable
Descriptive statistics
Probability density
A Probability measure
14. E[X] :
Variability
Coefficient of determination
Independence or Statistical independence
expected value of X
15. 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).
Joint distribution
Skewness
Credence
An event
16. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.
Dependent Selection
An estimate of a parameter
A Random vector
Random variables
17. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.
Observational study
Prior probability
the population mean
Bias
18. (or multivariate random variable) is a vector whose components are random variables on the same probability space.
Residuals
hypothesis
A Random vector
Conditional probability
19. 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
An event
Probability density
Descriptive statistics
Type II errors
20. Is that part of a population which is actually observed.
A sample
The Mean of a random variable
A probability density function
Particular realizations of a random variable
21. 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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22. 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.
Placebo effect
Statistical inference
nominal - ordinal - interval - and ratio
Bias
23. Describes a characteristic of an individual to be measured or observed.
Average and arithmetic mean
variance of X
Null hypothesis
Variable
24. 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.
variance of X
Probability and statistics
A Distribution function
experimental studies and observational studies.
25. 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.
descriptive statistics
Seasonal effect
Quantitative variable
Binomial experiment
26. A numerical measure that describes an aspect of a sample.
Type I errors
Statistic
Prior probability
Simple random sample
27. A sample selected in such a way that each individual is equally likely to be selected as well as any group of size n is equally likely to be selected.
the population mean
experimental studies and observational studies.
Simple random sample
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
28. Describes the spread in the values of the sample statistic when many samples are taken.
variance of X
Conditional distribution
Variability
Experimental and observational studies
29. A numerical measure that assesses the strength of a linear relationship between two variables.
Joint probability
Correlation coefficient
Block
Binary data
30.
the population mean
A statistic
Cumulative distribution functions
Confounded variables
31. The collection of all possible outcomes in an experiment.
Sample space
Atomic event
Statistic
Variability
32. Is denoted by - pronounced 'x bar'.
Inferential
Variable
Conditional probability
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
33. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.
Particular realizations of a random variable
Observational study
Inferential statistics
Statistics
34. 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'
An experimental study
Ratio measurements
Conditional probability
Observational study
35. When you have two or more competing models - choose the simpler of the two models.
quantitative variables
Type II errors
Law of Parsimony
Alpha value (Level of Significance)
36. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively
Residuals
Correlation
An event
variance of X
37. (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
Nominal measurements
The Expected value
Sample space
Type II errors
38. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.
Residuals
Statistical dispersion
Qualitative variable
Independence or Statistical independence
39. Is the probability of two events occurring together. The joint probability of A and B is written P(A and B) or P(A - B).
Prior probability
Posterior probability
An Elementary event
Joint probability
40. Two variables such that their effects on the response variable cannot be distinguished from each other.
Null hypothesis
Sampling Distribution
Observational study
Confounded variables
41. 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
Step 3 of a statistical experiment
An event
hypotheses
Descriptive
42. When there is an even number of values...
Observational study
That is the median value
That value is the median value
expected value of X
43. Is the length of the smallest interval which contains all the data.
The Range
Probability
A probability space
Conditional distribution
44. Is data that can take only two values - usually represented by 0 and 1.
Binary data
Conditional probability
categorical variables
Statistic
45. Are simply two different terms for the same thing. Add the given values
Marginal distribution
Valid measure
Average and arithmetic mean
A Distribution function
46. Cov[X - Y] :
covariance of X and Y
the sample or population mean
Ordinal measurements
That value is the median value
47. Var[X] :
Beta value
variance of X
Type 1 Error
Correlation
48. 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.
Step 3 of a statistical experiment
Sampling
Coefficient of determination
Correlation
49. Is the probability distribution - under repeated sampling of the population - of a given statistic.
A sampling distribution
the population variance
Simpson's Paradox
A population or statistical population
50. Is a sample space over which a probability measure has been defined.
Independence or Statistical independence
A sample
An estimate of a parameter
A probability space