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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 data that can take only two values - usually represented by 0 and 1.
A population or statistical population
Binary data
the population mean
Likert scale
2. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Pairwise independence
A probability space
Count data
An estimate of a parameter
3. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as
Random variables
An event
Confounded variables
categorical variables
4. Rejecting a true null hypothesis.
Quantitative variable
Descriptive statistics
Type 1 Error
Kurtosis
5. 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.
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
A probability distribution
Kurtosis
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
6. Two variables such that their effects on the response variable cannot be distinguished from each other.
Step 2 of a statistical experiment
Confounded variables
covariance of X and Y
Joint distribution
7. 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
The Range
Seasonal effect
Lurking variable
Observational study
8. 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.
s-algebras
Seasonal effect
An experimental study
Law of Parsimony
9. To find the average - or arithmetic mean - of a set of numbers:
Divide the sum by the number of values.
Independence or Statistical independence
Coefficient of determination
A likelihood function
10. 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
Simple random sample
A Statistical parameter
Parameter - or 'statistical parameter'
Correlation
11. A variable describes an individual by placing the individual into a category or a group.
Posterior probability
Sample space
A probability space
Qualitative variable
12. 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
A likelihood function
Step 1 of a statistical experiment
Skewness
P-value
13. Error also refers to the extent to which individual observations in a sample differ from a central value - such as
Type I errors & Type II errors
Parameter
Probability density
the sample or population mean
14. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.
Placebo effect
Law of Large Numbers
Probability and statistics
Variable
15. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
Quantitative variable
Random variables
A statistic
A probability distribution
16. A measure that is relevant or appropriate as a representation of that property.
Law of Large Numbers
Valid measure
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
the population correlation
17. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively
A sample
Placebo effect
Probability density functions
Residuals
18. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.
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19. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
s-algebras
Likert scale
A sampling distribution
An experimental study
20. A numerical facsimilie or representation of a real-world phenomenon.
Valid measure
nominal - ordinal - interval - and ratio
Simulation
A random variable
21. 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.
Random variables
Law of Parsimony
the population mean
A population or statistical population
22. A common goal for a statistical research project is to investigate causality - and in particular to draw a conclusion on the effect of changes in the values of predictors or independent variables on dependent variables or response.
Experimental and observational studies
Simpson's Paradox
Prior probability
An event
23. 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
A sample
Probability
Lurking variable
24. Gives the probability of events in a probability space.
Joint distribution
A Probability measure
A probability density function
The standard deviation
25. Statistics involve methods of using information from a sample to draw conclusions regarding the population.
An Elementary event
Step 3 of a statistical experiment
Law of Large Numbers
Inferential
26. There are four main levels of measurement used in statistics: Each of these have different degrees of usefulness in statistical research.
Bias
covariance of X and Y
nominal - ordinal - interval - and ratio
A Random vector
27. 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.
Probability density functions
Marginal probability
the population mean
Count data
28. Descriptive statistics and inferential statistics (a.k.a. - predictive statistics) together comprise
applied statistics
Simulation
Step 3 of a statistical experiment
Skewness
29. 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 population correlation
The sample space
Independent Selection
Inferential statistics
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.
Atomic event
expected value of X
Statistical inference
Law of Large Numbers
31. A numerical measure that describes an aspect of a sample.
Confounded variables
Statistic
experimental studies and observational studies.
A random variable
32. In particular - the pdf of the standard normal distribution is denoted by
Probability
A statistic
covariance of X and Y
f(z) - and its cdf by F(z).
33. 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'
Conditional probability
Type I errors
hypothesis
Sampling Distribution
34. Is defined as the expected value of random variable (X -
Count data
The Covariance between two random variables X and Y - with expected values E(X) =
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Joint probability
35.
Binomial experiment
the population mean
Dependent Selection
Quantitative variable
36. (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.
A Distribution function
An Elementary event
Block
Probability
37. A numerical measure that describes an aspect of a population.
Parameter
Interval measurements
Alpha value (Level of Significance)
An experimental study
38. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.
The standard deviation
Kurtosis
Block
Particular realizations of a random variable
39. Failing to reject a false null hypothesis.
Ratio measurements
the population mean
Type 2 Error
Inferential statistics
40. 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.
An estimate of a parameter
Quantitative variable
nominal - ordinal - interval - and ratio
That value is the median value
41. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.
Statistical adjustment
the sample or population mean
Block
Independent Selection
42. Describes the spread in the values of the sample statistic when many samples are taken.
The Expected value
Variable
Probability density functions
Variability
43. 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
inferential statistics
Lurking variable
experimental studies and observational studies.
Quantitative variable
44. 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.
An Elementary event
Step 3 of a statistical experiment
Simple random sample
Statistical inference
45. Of a group of numbers is the center point of all those number values.
Correlation
The average - or arithmetic mean
The median value
the population correlation
46. A numerical measure that assesses the strength of a linear relationship between two variables.
Sampling frame
Alpha value (Level of Significance)
Correlation coefficient
A sample
47. Long-term upward or downward movement over time.
Probability density
The Expected value
Trend
Statistical dispersion
48. S^2
Kurtosis
The Mean of a random variable
A probability density function
the population variance
49. The collection of all possible outcomes in an experiment.
Statistical dispersion
Simulation
Sample space
Step 1 of a statistical experiment
50. Is denoted by - pronounced 'x bar'.
An event
nominal - ordinal - interval - and ratio
Descriptive
The arithmetic mean of a set of numbers x1 - x2 - ... - xn