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Test your basic knowledge |
CLEP General Mathematics: Probability And Statistics
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clep
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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. Is used in 'mathematical statistics' (alternatively - 'statistical theory') to study the sampling distributions of sample statistics and - more generally - the properties of statistical procedures. The use of any statistical method is valid when the
A population or statistical population
Probability and statistics
Probability
An Elementary event
2. A numerical facsimilie or representation of a real-world phenomenon.
Ordinal measurements
Simulation
Quantitative variable
A Random vector
3. Is a sample and the associated data points.
A random variable
Variability
A data set
Individual
4. A group of individuals sharing some common features that might affect the treatment.
An estimate of a parameter
Alpha value (Level of Significance)
Block
s-algebras
5. There are four main levels of measurement used in statistics: Each of these have different degrees of usefulness in statistical research.
Inferential
nominal - ordinal - interval - and ratio
Treatment
The sample space
6. Are simply two different terms for the same thing. Add the given values
Average and arithmetic mean
The median value
The standard deviation
A population or statistical population
7. Var[X] :
The variance of a random variable
Binomial experiment
variance of X
Average and arithmetic mean
8. Some commonly used symbols for sample statistics
Probability density functions
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
the population correlation
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
9. Describes the spread in the values of the sample statistic when many samples are taken.
Placebo effect
Random variables
Variability
Marginal distribution
10. When there is an even number of values...
The average - or arithmetic mean
That is the median value
hypothesis
the sample or population mean
11. A variable that has an important effect on the response variable and the relationship among the variables in a study but is not one of the explanatory variables studied either because it is unknown or not measured.
Bias
s-algebras
Lurking variable
Ratio measurements
12. 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.
A data point
Divide the sum by the number of values.
the sample or population mean
Ratio measurements
13. E[X] :
Likert scale
expected value of X
f(z) - and its cdf by F(z).
Marginal probability
14. 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.
Descriptive
categorical variables
Statistical inference
Ratio measurements
15. Gives the probability distribution for a continuous random variable.
A probability density function
Mutual independence
nominal - ordinal - interval - and ratio
Statistical dispersion
16. 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.
Joint distribution
Sampling Distribution
Experimental and observational studies
Prior probability
17. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.
Placebo effect
Inferential
Joint distribution
Simulation
18. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.
Sampling Distribution
Greek letters
Prior probability
Probability
19. 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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20. Some commonly used symbols for population parameters
the population mean
Confounded variables
A data set
A statistic
21. In particular - the pdf of the standard normal distribution is denoted by
Correlation
Simpson's Paradox
A statistic
f(z) - and its cdf by F(z).
22. A numerical measure that describes an aspect of a population.
Statistical inference
Sampling frame
Greek letters
Parameter
23. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)
applied statistics
s-algebras
Alpha value (Level of Significance)
Independent Selection
24. Given two jointly distributed random variables X and Y - the marginal distribution of X is simply the probability distribution of X ignoring information about Y.
Marginal distribution
A data point
Greek letters
Skewness
25. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively
Sampling
Correlation
An estimate of a parameter
Residuals
26. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.
The Expected value
A probability distribution
Descriptive
Statistical adjustment
27. ?r
the population cumulants
Joint probability
Sampling Distribution
inferential statistics
28. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.
Parameter
Prior probability
observational study
categorical variables
29. S^2
Bias
the population variance
Dependent Selection
applied statistics
30. (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
observational study
Null hypothesis
That value is the median value
31. Many statistical methods seek to minimize the mean-squared error - and these are called
Sample space
Joint distribution
methods of least squares
A Distribution function
32. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).
Probability density functions
Quantitative variable
The standard deviation
experimental studies and observational studies.
33. Given two random variables X and Y - the joint distribution of X and Y is the probability distribution of X and Y together.
A data point
A data set
Descriptive
Joint distribution
34. 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
Pairwise independence
Parameter
Correlation
Interval measurements
35. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.
Joint probability
A sample
the population variance
Statistical adjustment
36. 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.
Prior probability
Kurtosis
A sample
Sampling
37. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as
Type I errors & Type II errors
categorical variables
Variability
The standard deviation
38. 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
Statistic
An estimate of a parameter
A Random vector
39. 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
Divide the sum by the number of values.
Interval measurements
the population mean
Probability density
40. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).
A probability space
The Range
The standard deviation
Particular realizations of a random variable
41. Have imprecise differences between consecutive values - but have a meaningful order to those values
The standard deviation
Estimator
An Elementary event
Ordinal measurements
42. Where the null hypothesis is falsely rejected giving a 'false positive'.
Type I errors
Sampling frame
applied statistics
Statistic
43. 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
nominal - ordinal - interval - and ratio
Simpson's Paradox
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Observational study
44. 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
Prior probability
hypotheses
Simulation
Treatment
45. Two variables such that their effects on the response variable cannot be distinguished from each other.
Confounded variables
Type I errors
Probability density
Sample space
46. Describes a characteristic of an individual to be measured or observed.
Binomial experiment
Sampling
Variable
Statistical dispersion
47. Is its expected value. The mean (or sample mean of a data set is just the average value.
Quantitative variable
The Mean of a random variable
Prior probability
A population or statistical population
48. To find the average - or arithmetic mean - of a set of numbers:
covariance of X and Y
That value is the median value
Statistic
Divide the sum by the number of values.
49. ?
A Statistical parameter
the population correlation
A sample
Null hypothesis
50. (or just likelihood) is a conditional probability function considered a function of its second argument with its first argument held fixed. For example - imagine pulling a numbered ball with the number k from a bag of n balls - numbered 1 to n. Then
the population cumulants
Skewness
A likelihood function
the population correlation